Computer Scoring

[001] Laslo Dinges, Marc-André Fiedler, Ayoub Al-Hamadi, Dmitri Bershadskyy, Joachim Weimann (2026)

Buyer–Seller-Deception-Game Dataset: A new comprehensive dataset for facial expression based deception detection in economic contexts

Intelligent Systems with Applications OpenFace-based AU features performed best on clean, controlled recordings while CNN-based predictors outperformed on challenging in-the-wild data with lower video quality. Multimodal approaches combining visual… Neuroimaging & New Technologies [002] Thi Bich Phuong Man, Thanh Ha Le, Luu Tu Nguyen, Thi Duyen Ngo (2025)

A Lightweight Visual Deception Detection Method Using Dynamic Images and a Customized SmallCNN–BiLSTM Architecture

2025 17th International Conference on Knowledge and System Engineering (KSE) The SmallCNN-BiLSTM architecture with dynamic images achieves competitive deception detection accuracy while offering substantial computational efficiency gains, making it suitable for real-world deployment in resource-constrained… Neuroimaging & New Technologies [003] Dmitry V. Belykh-Silaev (2025)

The Artificial Intelligence Application Concept in the System of Polygraph-Based Psychophysiological Lie Detection

Juridical Psychology The paper establishes a comprehensive conceptual framework defining AI application in polygraph systems, identifying implementation mechanisms, guiding principles, and operational forms, while systematically analyzing advantages,… AI & Machine Learning in Deception Detection [004] Anand Ashok Ingle, Jayant P. Mehare (2025)

Tetralet Attention Enabled Modified N-Adam Optimised Distributed Capsule Network for Lie Detection from Electroencephalogram Signals

International Journal of Biomedical Engineering and Technology Specific results unavailable due to inaccessibility of the full paper text. AI & Machine Learning in Deception Detection [005] Priyansh Bindroo, Rahi Bhuva, Shruti Savant, Pratik Kanani (2025)

DecepTech AI: Advancing Lie Detection Through Multimodal Nonverbal Behavior Analysis

Lecture Notes in Networks and Systems The system successfully integrated multiple nonverbal behavioral channels using machine learning to detect deception patterns, demonstrating capability for real-time processing and avoiding the intrusiveness of… AI & Machine Learning in Deception Detection [006] Abir Jaafar Hussain (2025)

Explainable AI for Unraveling the Significance of Visual Cues in High Stakes Deception Detection

IEEE Access Eyebrow movements emerged as the most reliable visual indicator of deception in high-stakes courtroom settings. The Multi-layer Perceptron model achieved 88% accuracy and 92.86% recall… AI & Machine Learning in Deception Detection [007] Astha Singh, Keerti Singh, Divya Kumar, Shiv Prakash (2025)

An Efficient Lie Detection with Movement Tracks of Larynx and Eye Flutters During Interrogation Using Machine Learning and Deep-Computing

Wireless Personal Communications The system successfully automated detection of micro-level eye and laryngeal movements invisible to the naked eye, demonstrating that non-verbal signals including blink patterns and swallowing… Neuroimaging & New Technologies [008] Radhika Thakkar, Dr. Sheshang Degadwala (2025)

Efficient Deception Detection Using Multimodal Facial and Audio Transcript Features

International Journal of Scientific Research in Science and Technology The Modified CNN model achieved 91.2% accuracy using multimodal fusion of facial action units, eye gaze, and audio prosodic features with attention-based feature fusion, outperforming… Neuroimaging & New Technologies [009] Yuanya Zhuo, Vishnu Monn Baskaran, Lillian Yee-Kiaw Wang, Raphaël C.-W. Phan (2025)

@LM DeceptionNet: A multimodal approach for efficient transfer learning-based deception detection

Knowledge-Based Systems The @LM DeceptionNet framework demonstrated consistent cross-scenario generalization with enhanced accuracy and robustness through adaptive multimodal fusion, achieving better computational efficiency with fewer parameters compared… Neuroimaging & New Technologies [010] Korean Research Team (2025 • DEEP LEARNING)

Development of a Deep-Learning-Based Computerized Scoring Algorithm for Polygraph Data

MDPI Journals Developed a Korean polygraph scoring system using deep neural networks. DNN-based algorithm outperformed both PolyScore and OSS-3 on test data by accounting for bio-signal nonlinearity. AI & Machine Learning in Deception Detection [011] Ayia A. S. A. Jabar (2025)

AN ENHANCED ALGORITHM TO IMPROVE THE ACCURACY OF LIE DETECTION SYSTEM BASED ON EEG SIGNAL

Kufa Journal of Engineering The enhanced signal processing pipeline achieved 86% accuracy on benchmark data and 78% accuracy on newly collected participant data, with a 23.2% improvement in signal-to-noise… Neuroimaging & New Technologies [012] Tien Nguyen, Faranak Abri, Akbar Siami Namin, Keith S. Jones (2025)

Multimodal Deception Detection Using Linguistic and Acoustic Features

Machine Learning, Deep Learning and AI for Cybersecurity A single-layer BiLSTM model achieved 93.57% accuracy and 94.48% F1 score on textual data from court testimony transcripts. ResNet50 performed best on audio data, and… AI & Machine Learning in Deception Detection [013] Jonathan Adkins, Ali Al Bataineh, Anthos Khanal (2025)

A psycholinguistic NLP framework for forensic text analysis of deception and emotion

Frontiers in Artificial Intelligence The researchers successfully identified both guilty parties from 18 suspects using combined entity correlation, deception scoring via Empath, emotion analysis through Hugging Face transformers, and… Verbal & Behavioral Deception Detection [014] Dana Rad, Csaba Kiss, Gavril Rad, Nicolae Paraschiv, Marius Bălaș (2025)

A multilayer perceptron neural network prediction approach to polygraph scoring

INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL The MLP neural network achieved 80% correct classification rate predicting deception levels in 400 offender examinations based on four psychophysiological indicators, with performance consistent with… AI & Machine Learning in Deception Detection [015] Gáspár Lukács (2025)

A Filtering Response Time Concealed Information Test for Searching for Relevant Concealed Items

Applied Cognitive Psychology The filtering RT-CIT protocol reduced testing time by approximately 59% (from 17 to 7 minutes) compared to conventional approaches while maintaining similar probe identification accuracy… Reaction Time & Cognitive Load Methods [016] Omar Osama Mohamed Shalash; Ahmed Métwalli; Mohamed Hany Sallam; Ehab Khatab (2025)

A Multimodal Polygraph Framework with Optimized Machine Learning for Robust Deception Detection

MDPI Journals The study addresses critical gaps by providing an open multimodal dataset and demonstrating improved generalization through PSO-enhanced machine learning approaches to physiological data fusion. AI & Machine Learning in Deception Detection [017] Dmitri Bershadskyy, Laslo Dinges, Marc-André Fiedler, Ayoub Al-Hamadi, Nina Ostermaier, Joachim Weimann (2024)

Experimental economics for machine learning—a methodological contribution on lie detection

PLOS ONE Machine learning algorithms trained on video data from an economic dice-rolling experiment achieved 67% lie detection accuracy when ground truth was verified through experimental design,… AI & Machine Learning in Deception Detection [018] Zhaoxu Li, Zitong Yu, Xun Lin, Nithish Muthuchamy Selvaraj, Xiaobao Guo, Bingquan Shen, Adams Wai-Kin Kong, Alex Kot (2024)

Flexible-Modal Deception Detection with Audio-Visual Adapter

2024 IEEE International Joint Conference on Biometrics (IJCB) The AVA framework achieved superior performance compared to other multi-modal fusion methods under flexible-modal settings, with audio modality generally outperforming vision-only approaches, while maintaining robust… AI & Machine Learning in Deception Detection [019] (2024)

LIE DETECTION USING FACIAL MICRO-EXPRESSION FEATURES WITH MACHINE LEARNING

MINAR International Journal of Applied Sciences and Technology The Sobel filter outperformed Canny edge detection, and mouth/nose regions proved more discriminative than eyes for lie detection, achieving F1-scores of 0.996 (truth) and 0.990… AI & Machine Learning in Deception Detection [020] Dainis A. Boumber, Fatima Zahra Qachfar, Rakesh Verma (2024)

Domain-Agnostic Adapter Architecture for Deception Detection: Extensive Evaluations with the DIFrauD Benchmark

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) The domain-agnostic adapter architecture achieved state-of-the-art performance on the DIFrauD benchmark across seven fraud domains, consistently outperforming all competing methods and revealing that representation quality… AI & Machine Learning in Deception Detection [021] Lucie SOUSEDIKOVA (2024)

Electrodermal Activity in Polygraph Testing

PRZEGLĄD ELEKTROTECHNICZNY The research details the 7-position EDA scoring framework (ranging from -3 to +3) with clear criteria distinguishing noticeable, significant, and dramatic differences between comparison and… Psychophysiology & Autonomic Responses [022] Binglei Duan, Danqi Hu, Hai Lu (2024)

Video-Based Deception Detection and Financial Fraud

SSRN Electronic Journal Visual deception scores derived from IPO roadshow videos significantly predict financial fraud. The effect is strongest for deception cues related to financial performance discussions, and… AI & Machine Learning in Deception Detection [023] Sharifa Alghowinem, Sabrina Caldwell, Ibrahim Radwan, Michael Wagner, Tom Gedeon (2024)

The Walk of Guilt: Multimodal Deception Detection from Nonverbal Motion Behaviour

Information Classification accuracy reached up to 88% through hybrid feature fusion, with visual signals showing highest single-modality performance followed by accelerometer and acoustic signals, averaging 60%… Verbal & Behavioral Deception Detection [024] Donald J. Krapohl; Donnie W. Dutton (2024 • COMPUTER SCORING FIELD)

Comparison of OSS-3 and PolyScore in Multi-Issue and Single-Issue Field Exams

Polygraph Compared computerized scoring algorithms on field data. OSS-3 correctly identified 71% truthful and 96% deceptive with 14% inconclusive rate, outperforming PolyScore on multiple-issue tests. Scoring & Test Data Analysis [025] Bicer, B., Dibeklioglu, H. (2024)

Automatic deceit detection through multimodal analysis of High-Stake Court-Trials

IEEE Transactions on Affective Computing The proposed architecture improved state-of-the-art performance on the Real-Life Trial dataset, with all classifiers achieving better results than measured human performance for deception detection. AI & Machine Learning in Deception Detection [026] Gáspár Lukács (2024)

No Practice Effect on the Classification Accuracy of the Response Time Concealed Information Test

Journal of Forensic Sciences Classification accuracy of the RT-CIT remained stable across repeated testing sessions with no significant practice effects, indicating the test maintains diagnostic validity even when examinees… Reaction Time & Cognitive Load Methods [027] Raphael Alper, Mordechai Guri (2024)

TrueWatch: Polygraph Examination With Smartwatches

IEEE Transactions on Information Forensics and Security Modern wearable smartwatches can detect lies in the Guilty Knowledge Test protocol, though their detection ability is comparatively weaker than conventional polygraph instruments. Neuroimaging & New Technologies [028] Xiaohong Lin, Hong Li, Tingwen Sheng, Genyue Fu, Liyang Sai (2024)

Combining recognition, conflict-monitoring and feedback-related ERPs to detect concealed autobiographical information

Three ERP indicators—conflict-monitoring N200, recognition P300, and feedback P300—significantly discriminated guilty from innocent participants, while FRN did not. Combining the three effective indicators achieved an… Concealed Information Test (CIT) [029] Dana RAD, Csaba KISS, Nicolae PARASCHIV, Valentina Emilia BALAS (2024)

Automated Comparative Predictive Analysis of Deception Detection in Convicted Offenders Using Polygraph with Random Forest, Support Vector Machine, and Artificial Neural Network Models

Studies in Informatics and Control Machine learning models successfully predicted deception from polygraph physiological data, with clustering analyses revealing important individual differences in response patterns. The findings demonstrate potential for… AI & Machine Learning in Deception Detection [030] Maria Petrescu, Haya Ajjan, Dana L. Harrison (2023)

Man vs machine – Detecting deception in online reviews

Journal of Business Research Automated text analysis methods show complementary strengths in detecting deceptive reviews, with incentivized reviews exhibiting linguistic patterns similar to unverified content. Multi-method integration analyzing quantity,… Verbal & Behavioral Deception Detection [031] Mircea Zloteanu, Matti Vuorre (2023)

Bayesian Generalized Linear Mixed Effects Models for Deception Detection Analyses

The SDT GLMM approach separates true discriminability (d-prime) from response bias (criterion), incorporates individual differences through random effects, and reveals substantially greater uncertainty in effect… Scoring & Test Data Analysis [032] Shanjita Akter Prome, Md Rafiqul Islam, David Asirvatham, Md. Kowsar Hossain Sakib, Neethiahnanthan Ari Ragavan (2023)

LieVis: A Visual Interactive Dashboard for Lie Detection Using Machine Learning and Deep Learning Techniques

2023 26th International Conference on Computer and Information Technology (ICCIT) BERT deep learning model, along with logistic regression and K-Nearest Neighbors, achieved 84% accuracy in detecting deception from courtroom testimony transcripts, outperforming traditional machine learning… AI & Machine Learning in Deception Detection [033] Krishnamurthy, G., Majumder, N., Poria, S., Cambria, E. (2023)

A Deep Learning Approach for Multimodal Deception Detection

Lecture Notes in Computer Science The multimodal deep learning approach achieved 96.14% accuracy and 0.98 ROC-AUC, significantly outperforming prior automated methods (77-92% AUC) and human performance (60-81% AUC). AI & Machine Learning in Deception Detection [034] Philipp Sprengholz, Franziska Schreckenbach, Carina G. Giesen, Nicolas Koranyi, Klaus Rothermund (2023)

Guilty on the Go: Uncovering Concealed Information by Assessing Response Preparation Processes in a Go-Nogo-Paradigm

Collabra: Psychology The paradigm detected both familiarity effects and response preparation processes in guilty participants, with reduced error rates for crime-related probes when preceded by matching prime… Concealed Information Test (CIT) [035] Dmitri Asonov; Mikhail Krylov; Vladislav Omelyusik; Anastasiya Ryabikina; Evgeny Litvinov; Mikhail Mitrofanov; Mikhail Mikhailov; Albert Efimov (2023)

Building a second-opinion tool for classical polygraph

Nature Scientific Reports The study successfully created a system that can catch mistakes in historical polygraph records by identifying examiner errors in interpreting raw physiological data. AI & Machine Learning in Deception Detection [036] Philip R. Corlett, Rosa Rossi-Goldthorpe (2023)

Choosing to Lie: Strategic and Pathological Deception

Competition context produced significantly elevated deception compared to control conditions (Cohen's d > 1.0, p < 2.2e-16), with most participants showing no deception in neutral… Verbal & Behavioral Deception Detection [037] Daniel Rad; Nicoleta Paraschiv; Csaba Kiss (2023)

Neural network applications in polygraph scoring — A scoping review

MDPI Journals Neural networks, particularly feedforward and convolutional architectures, show promise in improving polygraph accuracy over traditional methods, though further validation research is needed to determine optimal… AI & Machine Learning in Deception Detection [038] Anastasis Stathopoulos, Ligong Han, Norah Dunbar, Judee K. Burgoon, Dimitris Metaxas (2023)

Deception Detection in Videos Using Robust Facial Features with Attention Feedback

Handbook of Dynamic Data Driven Applications Systems The Bayesian neural network model achieved 92.36% accuracy detecting deception from facial features alone, with an attention mechanism that identifies key behavioral moments and enables… AI & Machine Learning in Deception Detection [039] Alex V. Mbaziira, Maha F. Sabir, Micheline Al Harrack (2022)

Lying trolls: Detecting deception and text-based disinformation using machine learning

Cybersecurity and Cognitive Science Hybrid models combining disinformation training data with other cybercrime text datasets achieved detection accuracies of 60-100%, substantially outperforming singleton models and demonstrating cross-domain transferability of… AI & Machine Learning in Deception Detection [040] (2022)

Looking for Lies: An Exploratory Analysis for Automated Detection of Deception

Word count-based machine learning models were most accurate at detecting deception (76% accuracy), with similar performance across video and text-based interviews, though significant gender bias… AI & Machine Learning in Deception Detection [041] Israa J. Mohammed, Dr. Loay E. George (2022)

Lie Detection: Truth Identification from EEG Signal Using Frequency and Time Features with SVM Classifier

Wasit Journal of Computer and Mathematics Science The system achieved 83% overall accuracy, with specific channels (8 and 12) reaching 100% accuracy when using 16-block segmentation and statistical moment features with SVM… Neuroimaging & New Technologies [042] Shaimaa Hameed Abd, Ivan A. Hashim, Ali Sadeq Abdulhadi Jalal (2022)

Automatic deception detection system based on hybrid feature extraction techniques

Indonesian Journal of Electrical Engineering and Computer Science The hybrid deception detection system achieved 88.06% classification accuracy by combining FACS-based action units, head movement patterns, and eye gaze directional features from video recordings… AI & Machine Learning in Deception Detection [043] Shun-Wen Hsiao, Cheng-Yuan Sun (2022)

Attention-Aware Multi-modal RNN for Deception Detection

2022 IEEE International Conference on Big Data (Big Data) The attention-aware multimodal RNN achieved 96% accuracy on the Real-Life Trial dataset, substantially exceeding human performance (50%) and earlier multimodal systems (83%), while providing interpretable… AI & Machine Learning in Deception Detection [044] Lev A. Derevyagin; Veniamin V. Makarov; Andrey Yuryevich Molchanov; Vladimir I. Tsurkov; Andrey N. Yakovlev (2022)

Applying Neural Networks in Polygraph Testing

Journal of Computer and Systems Sciences International The voting ensemble neural network approach demonstrated increased efficiency in polygraph testing and decreased erroneous conclusions by combining multiple classifier predictions to analyze standard psychophysiological… AI & Machine Learning in Deception Detection [045] Manon Schutte, Glynis Bogaard, Erik Mac Giolla, Lara Warmelink, Bennett Kleinberg, Bruno Verschuere (2021)

Man versus Machine: Comparing manual with LIWC coding of perceptual and contextual details for verbal lie detection

When set to the same metric, neither manual nor LIWC coding outperformed the other in discriminating truthful from deceptive statements (effect sizes ranged from d… Verbal & Behavioral Deception Detection [046] Xuecheng Zhang, Xuanying Zhu (2021)

Explaining Neural Network Results by Sensitivity Analysis for Deception Detection

Communications in Computer and Information Science Neural networks analyzing observer physiological responses achieved 62% deception detection accuracy, exceeding typical human performance of 54%. Sensitivity analysis combined with genetic algorithms successfully extracted… AI & Machine Learning in Deception Detection [047] (2021)

Hybrid Polygraph and Ocular-Motor Deception Tests for Screening and Specific-Incident Investigations

Psychology Applications & Developments VII The hybrid DLC protocol achieved 88% accuracy for specific-incident testing, while the hybrid MCT protocol achieved 91% accuracy for multi-issue screening, demonstrating that combining eye-tracking… Neuroimaging & New Technologies [048] Huang-Cheng Chou, Yi-Wen Liu, Chi-Chun Lee (2021)

Automatic Deception Detection using Multiple Speech and Language Communicative Descriptors in Dialogs

APSIPA Transactions on Signal and Information Processing The multi-modal model achieved 80.61% accuracy detecting deception in Mandarin dialogs, with analysis revealing that deceiver behaviors can be observed through interrogator responses in conversational… AI & Machine Learning in Deception Detection [049] Le Minh Ngo, Wei Wang, Burak Mandira, Sezer Karaoglu, Henri Bouma, Hamdi Dibeklioglu, Theo Gevers (2021)

Identity Unbiased Deception Detection by 2D-to-3D Face Reconstruction

2021 IEEE Winter Conference on Applications of Computer Vision (WACV) The identity-unbiased approach achieved 68% accuracy on high-stakes courtroom deception detection with 0.72 recall, demonstrating improved generalization by separating temporal behavioral cues from person-specific facial… Neuroimaging & New Technologies [050] Sinead V. Fernandes, Muhammad S. Ullah (2020)

Phychoacoustic Masking of Delta and Time -Difference Cepstrum Features for Deception Detection

2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Delta cepstrum and time-difference cepstrum features extracted using psychoacoustic masking principles and triangular critical band filters successfully distinguished truthful from deceptive speech in a real… Voice Stress Analysis [051] Donnie W. Dutton (2020)

Best Practices in Polygraph Examination

Polygraph & Forensic Credibility Assessment Monte Carlo simulations based on 299 subtotal scores provided the first systematic criterion accuracy estimates and confidence intervals for two-relevant-question multi-issue examinations, confirming that each… Scoring & Test Data Analysis [052] Wasiq Khan (2020)

Deception in the eyes of deceiver: A computer vision and machine learning based automated deception detection

Expert Systems with Applications Eye movements emerged as the most significant predictors of deception, with Random Forest classification achieving 78% accuracy using the 24 most important behavioral features extracted… AI & Machine Learning in Deception Detection [053] Wasiq Khan (2020)

Automated deception detection of males and females from non-verbal facial micro-gestures

IEEE World Congress on Computational Intelligence - IJCNN 2020 Both males and females showed reduced deception detection accuracy when classified by mixed-gender trained models rather than gender-specific classifiers, revealing distinct nonverbal behavioral patterns between… AI & Machine Learning in Deception Detection [054] Gazi Naven, Taylan Sen, Luke Gerstner, Kurtis Haut, Melissa Wen, Ehsan Hoque (2020)

Leveraging Shared and Divergent Facial Expression Behavior Between Genders in Deception Detection

2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) GAHL outperformed logistic regression, decision trees, and SVM models in small-sample deception detection tasks (N<75), successfully balancing the use of full datasets for shared behavioral… Neuroimaging & New Technologies [055] Gáspár Lukács (2020)

Dispersion matters: Diagnostics and control data computer simulation in Concealed Information Test studies

PLoS One Standard deviation substantially influences classification efficiency to the point that methods with lower mean differences can achieve superior AUC values (.858 vs .813) when dispersion… Meta-Analyses & Systematic Reviews [056] Derakhsan, A., Mikaelli, M., Gedeon, T., Nasrabadi, A. M. (2020)

Identifying the optimal features in multimodal deception detection

Multimodal Technologies and Interaction Thermal imaging achieved 90.1% accuracy in mock crime scenarios compared to 70.9% for traditional GSR/PPG measures. Perinasal and cheek regions showed superior discriminatory power, and… Neuroimaging & New Technologies [057] Mohamad Amin Younessi Heravi, Morteza Pishghadam, Hosnieh Raoufian, Akram Gazerani (2020)

RECURRENCE QUANTIFICATION ANALYSIS OF ELECTROOCULOGRAPHY SIGNAL TO A CONTROL QUESTION TEST: A NEW APPROACH FOR THE DETECTION OF DECEPTION

Biomedical Engineering: Applications, Basis and Communications Lmax and DET parameters decreased significantly for relevant questions in vertical EOG signals, while all RQA parameters except RR decreased significantly in horizontal EOG signals,… Neuroimaging & New Technologies [058] Donnie W. Dutton (2019)

Literature Survey of Structural Weighting of Polygraph Signals

Polygraph & Forensic Credibility Assessment EDA contributes over 60% of diagnostic information in polygraph testing, with cardiovascular responses accounting for approximately 34% and respiration contributing the remainder. Meta-Analyses & Systematic Reviews [059] Mingyu Ding, An Zhao, Zhiwu Lu, Tao Xiang, Ji-Rong Wen (2019)

Face-Focused Cross-Stream Network for Deception Detection in Videos

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) The FFCSN achieved state-of-the-art performance on real-life courtroom trial videos (104 videos, 58 subjects) by explicitly detecting faces in the spatial stream and performing cross-stream… Neuroimaging & New Technologies [060] Aleksandr S. Ognev, Vladimir A. Zernov, Elvira V. Likhacheva, Lyubov P. Nikolaeva, Mikhail Y. Rudenko, Aleksey A. Tyrtyshny, Denis S. Yesenin, Polina A. Maslennikova, Nikita V. Mizin (2019)

Use of cardiometry and oculography in concealed information detection

Cardiometry The study demonstrated that combined cardiometric and oculographic assessment of emotional-cognitive states in response to visual and auditory stimuli can be successfully used for concealed… Neuroimaging & New Technologies [061] Benjamin L. Blalock (2019)

How To: A Step-by-Step Worksheet for the Multinomial ESS

Poligrafia The paper provides comprehensive implementation tools including a structured ESS-M Analysis Worksheet, multinomial reference tables for various test formats (3-5 iterations of 2-4 relevant questions),… Scoring & Test Data Analysis [062] Huawei Tao, Peizhi Lei, Mengzhe Wang, Jie Wang, Hongliang Fu (2019)

Speech Deception Detection Algorithm Based on SVM and Acoustic Features

2019 IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT) The AF-SVM algorithm successfully demonstrated automated deception detection from speech using Support Vector Machine classification of acoustic features, validating the feasibility of machine learning approaches… AI & Machine Learning in Deception Detection [063] Chongyang Bai, Maksim Bolonkin, Judee Burgoon, Chao Chen, Norah Dunbar, Bharat Singh, V. S. Subrahmanian, Zhe Wu (2019)

Automatic Long-Term Deception Detection in Group Interaction Videos

2019 IEEE International Conference on Multimedia and Expo (ICME) The system achieved AUCs over 0.70 for identifying spies in extended group interactions. Low-level and high-level video features alone were insufficient; combining them with LiarRank… Neuroimaging & New Technologies [064] Soldner, F., Pérez-Rosas, V., Mihalcea, R. (2019)

Box of Lies: Multimodal deception detection in dialogues

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Multimodal machine learning classification achieved 69% accuracy in detecting conversational deception, exceeding both random baseline (50%) and human performance, with dialogue features providing unique predictive… AI & Machine Learning in Deception Detection [065] Sushma Venkatesh, Raghavendra Ramachandra, Patrick Bours (2019)

Robust Algorithm for Multimodal Deception Detection

2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) The multimodal system combining audio (cepstral coefficients with SRKDA), text (bag-of-n-grams with SVM), and non-verbal features (AdaBoost classifier) achieved 97% deception detection accuracy through majority… Neuroimaging & New Technologies [066] Avola, D., Cinque, L., Foresti, G.L., Pannone, D. (2019)

Automatic deception detection in RGB videos using facial action units

Proceedings of the 13th International Conference on Distributed Smart Cameras (ICDSC) The automated facial analysis system achieved 76.84% accuracy in deception detection using only facial Action Units, demonstrating the potential of non-invasive video-based deception detection. AI & Machine Learning in Deception Detection [067] Handler, M., Hernandez, N. (2019)

Introduction to the NCCA ASCII standard

Polygraph & Forensic Credibility Assessment: A Journal of Science and Field Practice The NCCA ASCII Standard successfully established a universal, human-readable text-based format for polygraph data that captures all hardware, software, physiological data, timing, and question information… Training, Standards & Professional Practice [068] Donnie W. Dutton (2018)

Reducing Inconclusive Results: A Descriptive Analysis of Decision Rules, Weighted Electrodermal Scores and Multinomial Cut-Scores

Polygraph & Forensic Credibility Assessment Weighted EDA scores alone reduced inconclusive results by 49%, while combining EDA weighting with multinomial cut-scores achieved a 72% reduction in inconclusive outcomes. Scoring & Test Data Analysis [069] Borza, D., Itu, R., Danescu, R. (2018)

Using Blink Rate to Detect Deception: A Study to Validate an Automatic Blink Detector and a New Dataset of Videos from Liars and Truth-Tellers

Journal of Imaging The automated system achieved 96.15% accuracy in classifying deceptive versus truthful responses based on blink rate patterns, with 99.3% accuracy in detecting individual blinks on… AI & Machine Learning in Deception Detection [070] Lai, Y.-F., Chen, M.-Y., Chiang, H.-S. (2018)

Constructing the lie detection system with fuzzy reasoning approach

Granular Computing The fuzzy reasoning approach achieved 89.5% lie detection accuracy and successfully identified specific EEG frequency bands associated with deception, comparing favorably to other data mining… Neuroimaging & New Technologies [071] Minakova, N.N., Bozhich, E.V. (2018)

Multivariate data analysis of polygraph charts for assessment of biophysical characteristics

Izv. AltGU Both PCA and PLS methods successfully analyzed polygraph data to assess human biophysical characteristics and identify physiological response anomalies, with potential applications in insider threat… AI & Machine Learning in Deception Detection [072] Aabad Ayoub, Farwa Rizvi, Saba Akram, Muhammad A. Tahir (2018)

The Polygraph and Lie Detection: A Case Study

Arab Journal of Forensic Sciences & Forensic Medicine Polygraph testing successfully identified deception by the victim who confessed after examination, while all suspects were found truthful. The case demonstrated successful adaptation of sensor… Comparison Question Test (CQT) [073] Kalafati, A., Krapohl, D.J. (2018)

The difference between the manual and automatic settings for the electrodermal channel and a potential effect on manual scoring

Polygraph & Forensic Credibility Assessment: A Journal of Science and Field Practice Manual and automatic EDA modes produce substantially similar aggregate outcomes but may diverge in individual scoring decisions, with automatic mode retaining approximately 90% of data… Scoring & Test Data Analysis [074] Wasiq Khan (2018)

Intelligent Deception Detection through Machine Based Interviewing

IEEE International Joint Conference on Neural Networks (IJCNN) Neural network classifiers successfully distinguished truthful from deceptive behavior in avatar interview scenarios, demonstrating that machine-based interviewing can elicit analyzable behavioral data for credibility assessment. AI & Machine Learning in Deception Detection [075] Raymond Nelson (2018)

Practical Polygraph: A Survey and Description of Decision Rules

APA Magazine Comprehensive survey of decision rules used in modern polygraph testing. Documented the evolution from subjective to objective decision criteria and their impact on reliability and… Scoring & Test Data Analysis [076] Alena Velichko, Viktor Budkov, Ildar Kagirov, Alexey Karpov (2018)

Comparative Analysis of Classification Methods for Automatic Deception Detection in Speech

Lecture Notes in Computer Science Random Forest achieved the highest performance with 79.3% UAR, while k-Nearest Neighbor combined with ensemble methods reached 76.3% UAR, substantially exceeding chance-level performance. AI & Machine Learning in Deception Detection [077] Nelson, R. (2018)

Electrodermal signal processing: a correlation study of auto-centered EDA and manually-centered EDA with the Criterion State of Deception and Truth-telling

Polygraph & Forensic Credibility Assessment Optimized auto-centered EDA filters equaled or exceeded the criterion correlation of manually-centered EDA, with a coefficient of determination (r²) of 0.49. Automatic processing retained approximately… Scoring & Test Data Analysis [078] Aaron C. Elkins, Jeffrey G. Proudfoot, Nathan Twyman, Judee K. Burgoon, Jay F. Nunamaker (2018)

Embodied Conversational Agent-Based Deception Detection

Lecture Notes in Networks and Systems Electrodermal activity successfully confirmed the presence of arousal during agent-based interviews, demonstrating that automated avatar systems can elicit valid physiological responses for detecting guilty knowledge… Neuroimaging & New Technologies [079] Nelson, R. (2017)

Updated numerical distributions for the Empirical Scoring System: An accuracy demonstration with archival datasets with and without the Vasomotor Sensor

Polygraph & Forensic Credibility Assessment The updated ESS-M maintained diagnostic accuracy equal to or exceeding the original ESS while successfully incorporating vasomotor sensor data that was previously excluded from scoring… Scoring & Test Data Analysis [080] Fatih Veysel Nurçin, Elbrus Imanov, Ali Işın, Dilber Uzun Ozsahin (2017)

Lie detection on pupil size by back propagation neural network

Procedia Computer Science The neural network with 10 hidden neurons achieved 100% accuracy in classifying pupil images during training, though results were not validated on independent test data… Neuroimaging & New Technologies [081] Judee K. Burgoon, Dimitris Metaxas, Thirimachos Bourlai, Aaron Elkins (2017)

Social Signals of Deception and Dishonesty

Social Signal Processing Automated systems analyzing constellations of nonverbal behavioral cues can classify deception and truth more accurately than many human observers, with eye movements, kinesic patterns, and… Verbal & Behavioral Deception Detection [082] Kleinberg, B., Mozes, M., Arntz, A., Verschuere, B. (2017)

Using named entities for computer-automated verbal deception detection

Journal of Forensic Sciences Named entities discriminated truthful from deceptive hotel reviews with AUC values of 0.59-0.63, outperforming lexicon-based word counting (LIWC) and sentence specificity measures. Dates, money references,… Verbal & Behavioral Deception Detection [083] Nelson, R. (2017)

Multinomial reference distributions for the Empirical Scoring System

Polygraph & Forensic Credibility Assessment The study successfully produced theoretical multinomial reference distributions that showed virtually perfect concordance with Monte Carlo simulations, enabling Bayesian classification that reduced inconclusive results by… Scoring & Test Data Analysis [084] Abouelenien, M., Pérez-Rosas, V., Mihalcea, R., Burzo, M. (2017)

Detecting deceptive behavior via integration of discriminative features from multiple modalities

IEEE Transactions on Information Forensics and Security The combination of thermal and linguistic modalities exceeded 70% accuracy in detecting deception, with forehead thermal features and combined unigram-LIWC linguistic features providing the strongest… AI & Machine Learning in Deception Detection [085] Jay F. Nunamaker, Judee K. Burgoon, Justin Scott Giboney (2016)

Special Issue: Information Systems for Deception Detection

Journal of Management Information Systems The featured research demonstrates that computational approaches combining verbal, nonverbal, behavioral, and physiological cues significantly outperform human judgment in detecting deception across multiple domains, from… Neuroimaging & New Technologies [086] Mariana Serras Pereira, Reinier Cozijn, Eric Postma, Suleman Shahid, Marc Swerts (2016)

Comparing a Perceptual and an Automated Vision-Based Method for Lie Detection in Younger Children

Frontiers in Psychology Judges detected lies above chance level but with modest accuracy. Increased movement was correlated with perception of lies, though automated analysis found no actual movement… Neuroimaging & New Technologies [087] Raymond Nelson; Benjamin L. Blalock (2016 • ESS EXTENDED ANALYSIS)

Extended Analysis with ESS and OSS-3 on USAF-MGQT Examination Data

Polygraph Applied ESS and OSS-3 to USAF examination data. Found ESS component weighting achieved superior diagnostic extraction compared to simpler three-position scoring models. Scoring & Test Data Analysis [088] Bennett Kleinberg, Galit Nahari, Bruno Verschuere (2016)

Using the verifiability of details as a test of deception: A conceptual framework for the automation of the verifiability approach

Proceedings of the Second Workshop on Computational Approaches to Deception Detection The paper provides theoretical and methodological blueprints for automating verifiability coding through LIWC-based linguistic analysis and rule-based named entity recognition, establishing a foundation for computational… Verbal & Behavioral Deception Detection [089] Stephan Ludwig, Tom van Laer, Ko de Ruyter, Mike Friedman (2016)

Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

Journal of Management Information Systems The automated detection algorithm achieved 70% accuracy in identifying deception, substantially outperforming the 54% accuracy of human judges. Deceivers minimized referencing and self-deprecation, included more… AI & Machine Learning in Deception Detection [090] Cati Brown-Johnson, Donald Rubin (2015)

A corpus-based analysis of potential linguistic indicators of corporate deception in tobacco industry documents

Cognitive-emotional verbs (believe, think, seem, feel) were strongly associated with likely deception and most prevalent in external audience documents and materials from the Tobacco Institute… Verbal & Behavioral Deception Detection [091] Raymond Nelson (2015 • META-ANALYTIC UPDATE)

Updated Meta-Analytic Survey of Validated Polygraph Techniques

Polygraph Extension of the 2011 APA meta-analytic survey with additional validated techniques. Confirmed mean accuracy rates of approximately 89% for event-specific tests and documented ESS/OSS scoring… Meta-Analyses & Systematic Reviews [092] Charles Robert Honts; Racheal Reavy (2015 • EXPERIMENTAL)

The Comparison Question Polygraph Test: A Contrast of Methods and Scoring

Physiology & Behavior Mock crime experiment with 250 paid participants contrasting probable-lie and directed-lie CQT variants. Found substantial main effects of guilt in both OSS2 computer and human… Laboratory & Analog Studies [093] Jinie Pak, Lina Zhou (2015)

A comparison of features for automatic deception detection in synchronous computer-mediated communication

2015 IEEE International Conference on Intelligence and Security Informatics (ISI) Structural features were independently effective in detecting deception, and combining structural features with linguistic features significantly improved deception detection performance compared to using linguistic features… AI & Machine Learning in Deception Detection [094] Michael C. Gougler (2015)

The Vasomotor Response in the Comparison Question Test

Polygraph Vasomotor responses were found to be highly useful in discriminating deception, with large main effects of guilt detected by both the OSS2 algorithm (η²p =… Laboratory & Analog Studies [095] Hauch, V., Blandon-Gitlin, I., Masip, J., Sporer, S.L. (2015)

Are computers effective lie detectors? A meta-analysis of linguistic cues to deception

Personality and Social Psychology Review Relative to truth-tellers, liars showed greater cognitive load, expressed more negative emotions, distanced themselves more from events, used fewer sensory-perceptual words, and referred less to… Meta-Analyses & Systematic Reviews [096] Donald J. Krapohl; Walt Goodson (2015)

Decision Accuracy for the Relevant-Irrelevant Screening Test: Influence of an Algorithm on Human Decision-Making

European Polygraph The study addressed the poor interrater reliability problem that has plagued RI screening tests, investigating whether algorithmic support could resolve fundamental reliability issues that undermine… Scoring & Test Data Analysis [097] Pérez-Rosas, V., Abouelenien, M., Mihalcea, R., Xiao, Y., Linton, C.J., Burzo, M. (2015)

Deception Detection using Real-life Trial Data

Proceedings of the 2015 ACM on International Conference on Multimodal Interaction Multimodal fusion of linguistic and gesture features achieved 60-75% accuracy in detecting deception from real courtroom footage, outperforming human judgment which showed only slight inter-rater… AI & Machine Learning in Deception Detection [098] Kleinberg, B., Verschuere, B. (2015)

Memory Detection 2.0: The First Web-Based Memory Detection Test

PLoS One Reaction times successfully detected concealed autobiographical information with accuracy well above chance, performing better than error rates. Memory detection was significantly more successful for high… Reaction Time & Cognitive Load Methods [099] Charles Robert Honts; Mark Handler; Pamela K. Shaw; Michael C. Gougler (2015)

Directed Lie Comparison Questions and Countermeasure Resistance

Various Publications Examined whether directed-lie comparison questions offer better countermeasure resistance. Research suggests that modern testing formats with directed lies may be more robust against deliberate manipulation… Countermeasures Research [100] Kirill Leontiev, Sergey Panin, Yuri Kholodniy (2014)

Polygraph Test Results Assessment by Regression Analysis Methods

Science and Education of the Bauman MSTU The study demonstrated that regression-based statistical methods could provide systematic evaluation of polygraph data, reducing examiner subjectivity and establishing quantifiable decision rules for deception detection… Scoring & Test Data Analysis [101] Banerjee, R., Feng, S., Kang, J.S., Choi, Y. (2014)

Keystroke Patterns as Prosody in Digital Writings: A Case Study with Deceptive Reviews and Essays

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) Combined keystroke features with stylometry achieved over 90% classification accuracy, with deceptive writers showing increased pauses and revisions, particularly spending more time on first-person pronouns,… AI & Machine Learning in Deception Detection [102] Ade Adi Wibowo, Zarina Shukur, Rozmi Ismail (2014)

Measurement Model for Deception Detection in Online Chat Software

Information Technology Journal The software analysis produced an average deception probability of 11.36% across participants, and users' trust in the analysis affected their decision-making during chat interactions. Verbal & Behavioral Deception Detection [103] Bartosz Wojciech Wojciechowski (2014)

Content analysis algorithms: an innovative and accurate approach to statement veracity assessment

European Polygraph MASAM with decision algorithms achieved 96.87% accuracy for truthful statements and 69.23% for false statements, dramatically outperforming traditional SVA, RM, and SCAN techniques which performed… AI & Machine Learning in Deception Detection [104] Nathan W. Twyman, Aaron C. Elkins, Judee K. Burgoon, Jay F. Nunamaker (2014)

A Rigidity Detection System for Automated Credibility Assessment

Journal of Management Information Systems The system successfully detected kinesic rigidity in real-time during concealed information tests, confirming rigidity as a viable automated deception indicator and providing new theoretical insights… Neuroimaging & New Technologies [105] Gao, J., Tian, H., Yang, Y., Yu, X., Li, C., Rao, N. (2014)

A Novel Algorithm to Enhance P300 in Single Trials: Application to Lie Detection Using F-Score and SVM

PLoS ONE The F-score_SVM model combining spatial denoising with optimized feature selection achieved over 96% accuracy in classifying guilty versus innocent subjects based on P300 responses to… Neuroimaging & New Technologies [106] Yijun Xiong, Yu Luo, Wentao Huang, Wenjia Zhang, Yong Yang, Junfeng Gao (2014)

A novel classification method based on ICA and ELM: a case study in lie detection

Bio-Medical Materials and Engineering The ICA_ELM method achieved 95.40% classification accuracy with dramatically reduced computational time compared to backpropagation neural networks and support vector machines, demonstrating both high accuracy… Neuroimaging & New Technologies [107] Erin Crabb (2014)

“Time for Some Traffic Problems”: Enhancing E-Discovery and Big Data Processing Tools with Linguistic Methods for Deception Detection

Journal of Digital Forensics, Security and Law The linguistic classifier successfully demonstrated capability to stratify the large Enron Email Dataset and identify potentially deceptive records by analyzing linguistic feature distributions while avoiding… Verbal & Behavioral Deception Detection [108] Erica J. Briscoe, D. Scott Appling, Heather Hayes (2014)

Cues to Deception in Social Media Communications

2014 47th Hawaii International Conference on System Sciences Machine learning classifiers achieved 90% average accuracy in detecting deception using linguistic features including sentence complexity, sentiment, emoticon usage, and informality markers, with mean precision… Verbal & Behavioral Deception Detection [109] Elias Ebrahimzadeh, Seyed Mohammad Alavi, Ahmad Bijar, Alireza Pakkhesal (2013)

A novel approach for detection of deception using Smoothed Pseudo Wigner-Ville Distribution (SPWVD)

Journal of Biomedical Science and Engineering The SPWVD approach achieved 89.73% accuracy in P300-based deception detection, surpassing earlier methods by providing enhanced time-frequency resolution while suppressing cross-term interference in EEG signal… Neuroimaging & New Technologies [110] Junfeng Gao, Zhao Wang, Yong Yang, Wenjia Zhang, Chunyi Tao, Jinan Guan, Nini Rao (2013)

A Novel Approach for Lie Detection Based on F-Score and Extreme Learning Machine

PLoS ONE The F-score_ELM method achieved exceptional testing accuracies of 99.27% sensitivity and 98.17% specificity in classifying guilty versus innocent subjects, outperforming traditional PCA-based approaches while requiring… AI & Machine Learning in Deception Detection [111] Samreen Amir, Nimrah Ahmed, Bhawani Shankar Chowdhry (2013)

Lie detection in interrogations using digital signal processing of brain waves

2013 3rd International Conference on Instrumentation, Communications, Information Technology and Biomedical Engineering (ICICI-BME) Initial results showed good reliability in the hardware-implemented DSP-based lie detection system, though the researchers acknowledged that further testing on additional subjects was required to… Neuroimaging & New Technologies [112] Hugo Plácido da Silva, Ana Priscila Alves, André Lourenço, Ana Fred, Inês Montalvão, Leonel Alegre (2013)

Towards the Detection of Deception in Interactive Multimedia Environments

Lecture Notes in Computer Science The study successfully demonstrated deception detection using non-intrusive off-the-person sensors in an interactive game-based environment, providing useful guidelines for future work while engaging public audiences… Laboratory & Analog Studies [113] S. Rajkumar, V. Narayani, Dr. S.P. Victor (2012)

Unification Of Randomized Anomaly In Deception Detection Using Fuzzy Logic Under Uncertainty

International Journal of Research in Computer Science Fuzzy logic outperformed randomness by approximately 45% and uncertainty methods by 55% in maximum deception detection scenarios, demonstrating that graded membership functions capture the ambiguous… AI & Machine Learning in Deception Detection [114] Breska, A., Ben-Shakhar, G., Gronau, N. (2012)

Algorithms for detecting concealed knowledge among groups when the critical information is unavailable

Journal of Experimental Psychology: Applied Reanalysis of three datasets showed that both averaging and PCA-based algorithms successfully detected critical items and differentiated knowledgeable from unknowledgeable subjects with efficiency approaching standard… Concealed Information Test (CIT) [115] Kircher, J. C., Kristjansson, S., Gardner, M. K., Webb, A. K. (2012)

Human and computer decision-making in the psychophysiological detection of deception

Polygraph Only electrodermal response amplitude, cardiograph baseline increase, and respiration line length proved valid and reliable indicators of deception across all independent samples. Examiners showed systematic… Scoring & Test Data Analysis [116] Raymond Nelson (2012 • MONTE CARLO)

Monte Carlo Study of Criterion Validity for Two-Question Zone Comparison Tests with the ESS

Polygraph Used Monte Carlo simulation methods to establish statistical confidence intervals for ESS scoring across various test formats and decision rules. Provided robust normative data. Scoring & Test Data Analysis [117] Valerie Hauch, Iris Blandon-Gitlin, Jaume Masip, Siegfried L. Sporer (2012)

Linguistic Cues to Deception Assessed by Computer Programs: A Meta-Analysis

PsycEXTRA Dataset Computer-analyzed linguistic cues reliably differentiate lies from truths, with liars showing increased cognitive load, more negative emotion, greater psychological distancing, fewer sensory details, and reduced… Verbal & Behavioral Deception Detection [118] Junfeng Gao, NiNi Rao, Yong Yang, Wenming Wei (2012)

A New Lie Detection Method Based on Small-number of P300 Responses

2012 International Conference on Biomedical Engineering and Biotechnology The method achieved 82.45% balanced accuracy in distinguishing guilty from innocent subjects using reduced stimulus presentations, demonstrating that reliable P300-based lie detection could be implemented… Concealed Information Test (CIT) [119] Pamela K. Shaw (2011)

Using the Empirical Scoring System

Polygraph Validation data across 13 dimensions of criterion accuracy from 5,192 scored results of 732 confirmed ZCT examinations demonstrated strong performance by both experienced and inexperienced… Scoring & Test Data Analysis [120] Christie M. Fuller, David P. Biros, Dursun Delen (2011)

An investigation of data and text mining methods for real world deception detection

Expert Systems with Applications Information fusion ensemble models achieved >74% classification accuracy in detecting deception in authentic criminal investigation statements, outperforming artificial neural networks (73.46%) and decision trees (71.60%),… AI & Machine Learning in Deception Detection [121] Matthew L. Jensen, Paul Benjamin Lowry, Jeffrey L. Jenkins (2011)

Effects of Automated and Participative Decision Support in Computer-Aided Credibility Assessment

Journal of Management Information Systems Decision aids that collect both automated linguistic cues and human perceptual observations perform better than systems relying on only one type of cue, while participatory… Verbal & Behavioral Deception Detection [122] Benjamin L. Blalock (2011)

Criterion validity of the Empirical Scoring System and the Objective Scoring System, version 3 with the USAF Modified General Question Technique

Polygraph Manual ESS achieved 88.2% unweighted accuracy, automated ESS achieved 89.7%, and the OSS-3 computer algorithm reached 90.2% correct decisions, with Pearson correlations between scoring models… Scoring & Test Data Analysis [123] Varlamov, V., Varlamov, G. (2010)

Lie Detection with Computer

Computerized scoring systems can apply consistent measurement standards across variable field conditions, and examinees must maintain an optimal stress level (inverted-U relationship) to produce interpretable… Scoring & Test Data Analysis [124] Pan Xiaogang, Cai Luyuan, Wang Zhaobin, Bai Xiao (2010)

A New Computer Vision Based Polygraph System

Recent Patents on Computer Science The authors reported experimental validation of a computer vision system that successfully detected deception through automated pupil size measurement, claiming it represented the best computer… Neuroimaging & New Technologies [125] Tuvia Shurany; Fabiola Chaves (2010)

The Integrated Zone Comparison Technique and ASIT PolySuite Algorithm: A Field Validity Study

European Polygraph IZCT with ASIT PolySuite achieved 98.73% accuracy excluding inconclusives (92.9% including them), while manual 3-point scoring achieved 98.71% accuracy excluding inconclusives (91.7% including them), demonstrating… Field Validity Studies [126] Bashar A. Rajoub (2010)

Facial image processing for facial analysis

Conference proceedings Color-space pre-processing of visible images via Chrominance and Hue segmentation increased face detection rates and reduced false positives compared to standard Haar Classifiers, and enabled… AI & Machine Learning in Deception Detection [127] Izumi Matsuda, Hiroshi Nittono, Tokihiro Ogawa (2010)

Discrimination performance of event-related potentials in the autonomic-based Concealed Information Test

International Journal of Psychophysiology ERP measures detected participants missed by autonomic measures alone, and combining ERP with autonomic measures significantly improved discrimination performance. The peak amplitude of ERP difference… Neuroimaging & New Technologies [128] Eugene Santos, Deqing Li (2010)

On Deception Detection in Multiagent Systems

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans The correlation-based approach successfully detected deception in multi-agent systems by predicting agent responses and flagging statistically significant deviations, demonstrating that computational analysis of reasoning consistency… Verbal & Behavioral Deception Detection [129] Nelson, R., Handler, M. (2010)

Empirical Scoring System: NPC Quick Reference

Inexperienced examiners using ESS achieved mean accuracy of 90.1% (95% CI = 83.8% to 95.8%) with only 3.3% inconclusives, and demonstrated 85% inter-rater agreement, indicating… Scoring & Test Data Analysis [130] Nicholas Michael, Mark Dilsizian, Dimitris Metaxas, Judee K. Burgoon (2010)

Motion Profiles for Deception Detection Using Visual Cues

Lecture Notes in Computer Science The motion profile Nearest Neighbor models achieved 81.6% accuracy in detecting deception using only visual behavioral cues. Subject-specific models significantly outperformed general models, indicating that… Neuroimaging & New Technologies [131] Meredith G. Cunha, Alissa C. Clarke, Jennifer Z. Martin, Jason R. Beauregard, Andrea K. Webb, Asher A. Hensley, Nirmal Q. Keshava, Daniel J. Martin (2010)

Detection of deception in structured interviews using sensors and algorithms

SPIE Proceedings Automated algorithms successfully detected deception from physiological features extracted during honest and deceptive interview intervals, with detection performance varying by interview style and reported through… Neuroimaging & New Technologies [132] Dean A. Pollina; Frank S. Horvath; John W. Denver; Andrew Belvin Dollins; Troy E. Brown (2009)

Development of Technologies and Test Formats for Credibility Assessment

European Polygraph The paper likely presented validation data for novel technological approaches including thermal imaging systems and computerized scoring methods that could supplement or enhance traditional polygraph… Neuroimaging & New Technologies [133] Izumi MATSUDA, Akihisa HIROTA, Tokihiro OGAWA, Noriyoshi TAKASAWA, Kazuo SHIGEMASU (2009)

Statistical discrimination methods for the polygraph test

Japanese Journal of Physiological Psychology and Psychophysiology The latent class discrimination method (database-based) and hidden Markov discrimination method (within-individual) both demonstrated higher discrimination performance than conventional logistic regression and discriminant analysis methods… Scoring & Test Data Analysis [134] Department of Defense Polygraph Institute (2009)

Comparison of the Objective Scoring System and Probability Analysis

NCJRS (US Government) Both the Objective Scoring System and Probability Analysis demonstrated equivalent accuracy with no significant differences in area under the ROC curve for either Zone Comparison… Scoring & Test Data Analysis [135] Harris, J.C., McQuarrie, A.D. (2009)

The Preliminary Credibility Assessment System Embedded Algorithm Description and Validation Results

Johns Hopkins University Applied Physics Laboratory Validation studies showed 80% accuracy when inconclusives were excluded, with 23% inconclusive rates. When inconclusives were included, accuracy dropped to 63-79%. The algorithm was deliberately… Neuroimaging & New Technologies [136] Nelson, R., Krapohl, D., Handler, M. (2008)

Brute-force comparison: A Monte Carlo study of the Objective Scoring System version 3 (OSS-3) and human polygraph scorers

Polygraph OSS-3 exceeded the decision accuracy of 10 human scorers and 9 out of 10 individual scorers across six accuracy dimensions. The algorithm demonstrated perfect reliability… Scoring & Test Data Analysis [137] Nelson, R., Handler, M., Krapohl, D. (2008)

Development and validation of the Objective Scoring System version 3

Polygraph OSS-3 achieved 88% average decision accuracy with balanced sensitivity and specificity, with computer algorithms providing perfect interrater reliability compared to human scorers (κ = .58–.61)… Scoring & Test Data Analysis [138] Raymond Nelson; Mark Handler; Donald J. Krapohl (2008 • OSS-3 DEVELOPMENT)

Objective Scoring System, Version 3 (OSS-3): Development and Validation

Polygraph Described the OSS-3 algorithm and used brute-force methods to compare accuracy against previous versions and human examiners. OSS-3 demonstrated balanced sensitivity/specificity and outperformed 10 human… Scoring & Test Data Analysis [139] Matthew L. Jensen, Judee K. Burgoon, Jay F. Nunamaker (2008)

User experiences with an unobtrusive decision aid for deception detection

2008 42nd Annual IEEE International Carnahan Conference on Security Technology Novice lie-catchers using the decision aid experienced improved deception detection accuracy, but users who incorporated more system recommendations performed better. Novices primarily turned to the… Verbal & Behavioral Deception Detection [140] Christie M. Fuller, David P. Biros, Dursun Delen (2008)

Exploration of Feature Selection and Advanced Classification Models for High-Stakes Deception Detection

Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008) The study achieved 76% accuracy in distinguishing truthful from deceptive statements, demonstrating that careful feature selection could improve classification performance while preventing model overfitting. AI & Machine Learning in Deception Detection [141] Matthew L. Jensen, Thomas O. Meservy, Judee K. Burgoon, Jay F. Nunamaker (2008)

Video-Based Deception Detection

Studies in Computational Intelligence The automated system extracted behavioral features from video that performed comparably to human-coded perceptions in detecting deception, identifying behavioral profiles including agitated, over-controlled, and relaxed… Neuroimaging & New Technologies [142] Tiantian Qin, Judee K. Burgoon (2007)

An Investigation of Heuristics of Human Judgment in Detecting Deception and Potential Implications in Countering Social Engineering

2007 IEEE Intelligence and Security Informatics An automated system using discriminant analysis significantly outperformed human judges in detecting deception, validating the potential of computational tools to overcome inherent human cognitive biases… Verbal & Behavioral Deception Detection [143] Tsiamyrtzis, P., Dowdall, J., Shastri, D., Pavlidis, I., Frank, M., Ekman, P. (2007)

Lie detection - recovery of the periorbital signal through tandem tracking and noise suppression in thermal facial video

International Journal of Computer Vision The tandem CONDENSATION tracker-based system achieved 87.2% accuracy in classifying deceptive versus truthful subjects, matching the performance of highly trained polygraph experts while operating in… Neuroimaging & New Technologies [144] Raymond Nelson; Mark Handler; Donald J. Krapohl; Raymond Nelson; Donald J. Krapohl; Mark Handler; Raymond Nelson (2007 – 2011)

Development of the Objective Scoring System (OSS) and Empirical Scoring System (ESS)

Polygraph Developed and validated the OSS and ESS computerized scoring methods, resulting in more objective and stable analysis of psychophysiological outcomes. These systems replaced subjective hand-scoring… Scoring & Test Data Analysis [145] S. Gupta, D. B. Skillicorn (2006)

Improving a textual deception detection model

Proceedings of the 2006 conference of the Center for Advanced Studies on Collaborative research - CASCON '06 The study revealed that each of the four kinds of words in the Pennebaker model acts as a separate latent factor for deception, rather than… Verbal & Behavioral Deception Detection [146] Rothwell, J., Bandar, Z., O'Shea, J., McLean, D. (2006)

Silent talker: a new computer-based system for the analysis of facial cues to deception

Applied Cognitive Psychology The Silent Talker system achieved 74% accuracy (p < 0.001) classifying individual deceptive responses and 80% accuracy (p = 0.035) for overall interview classifications in… AI & Machine Learning in Deception Detection [147] De Clercq, A., Verschuere, B., De Vlieger, P., Crombez, G. (2006)

Psychophysiological analysis (PSPHA): A modular script based program for analyzing psychophysiological data

Behavior Research Methods PSPHA successfully provides a free, flexible platform for analyzing biosignals including skin conductance, ECG, respiration, and EMG with VBScript-based modularity allowing user customization for specific… Scoring & Test Data Analysis [148] Xiangdong An, Dawn Jutla, Nick Cercone (2006)

Temporal Context Lie Detection and Generation

Lecture Notes in Computer Science The research demonstrated that Dynamic Bayesian Networks can effectively model both the detection and generation of lies in temporal context systems by exploiting dependencies between… AI & Machine Learning in Deception Detection [149] Nathan J. Gordon; Feroze B. Mohamed; Scott H. Faro; Steven M. Platek; Harris Ahmad; J. Michael Williams (2006)

Integrated zone comparison polygraph technique accuracy with scoring algorithms

Physiology & Behavior All three algorithms achieved 100% accuracy when inconclusive results were excluded. When inconclusives were counted as errors, ASIT Poly Suite achieved 90% accuracy while PolyScore… Scoring & Test Data Analysis [150] Stuart M. Senter (2005)

An Exploration of Methods for the Analysis of Multiple-Issue Relevant/Irrelevant Screening Data

Polygraph Different scoring and analytical methods produce meaningfully different accuracy and inconclusive rates on Multiple-Issue R/I data, with structured numerical scoring demonstrating superior consistency over subjective… Scoring & Test Data Analysis [151] Bond, G. D., Lee, A. Y. (2005)

Language of lies in prison: Linguistic classification of inmates' truthful and deceptive natural language

Applied Cognitive Psychology Automated linguistic analysis achieved 69.7-71.1% accuracy in classifying prisoner statements, with software showing unbiased criteria while human judges (especially younger prisoners) exhibited decision bias. Spatial… Verbal & Behavioral Deception Detection [152] Shan Lu, G. Tsechpenakis, D.N. Metaxas, M.L. Jensen, J. Kruse (2005)

Blob Analysis of the Head and Hands: A Method for Deception Detection

Proceedings of the 38th Annual Hawaii International Conference on System Sciences The study successfully validated automated blob analysis for tracking head and hand movements across diverse skin tones, demonstrating the technical feasibility of using computer vision… Neuroimaging & New Technologies [153] L. Zhou (2005)

An Empirical Investigation of Deception Behaviorin Instant Messaging

IEEE Transactions on Professional Communication Three types of nonverbal behaviors and three types of verbal behaviors significantly differentiated deceivers from truth tellers, including greater word count, more turn-taking, increased negative… Verbal & Behavioral Deception Detection [154] Mary T. Dzindolet, Linda G. Pierce (2005)

Using a linguistic analysis tool to detect deception

PsycEXTRA Dataset Technological tools showed promise for detecting deception through linguistic analysis, but effectiveness varied significantly based on communication medium and personal investment in the topic, demonstrating… Verbal & Behavioral Deception Detection [155] Judee K. Burgoon, Jay F. Nunamaker (2004)

Computer-Aided Support of the Detection of Deception

Group Decision and Negotiation The research program demonstrated that automated detection systems achieved 70-92% accuracy compared to 54% for human judgment, with multimodal approaches combining kinesic, vocal, and linguistic… Neuroimaging & New Technologies [156] Tiantian Qin, J. Burgoon, J.F. Nunamaker (2004)

An exploratory study on promising cues in deception detection and application of decision tree

37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the Five comparative experiments demonstrated that decision tree performance — including both accuracy rates and model complexity — was dramatically improved by statistically and semantically selecting… AI & Machine Learning in Deception Detection [157] J.F. Nunamaker (2004)

Detection of deception: collaboration systems and technology

37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the The paper established collaboration systems as platforms for embedded credibility assessment, framing research showing that technology-enabled multimodal analysis of verbal, vocal, and behavioral cues could… Neuroimaging & New Technologies [158] Aleksandra Slavkovic (2003)

Automated Scoring of Polygraph Data

Statistical Data Mining and Knowledge Discovery With a simplified logistic regression approach using carefully selected features from electrodermal, cardiovascular, and respiratory channels, the study achieved classification accuracy rates comparable to more… Scoring & Test Data Analysis [159] Kircher, J.C., Raskin, D.C. (2002)

Computerized Polygraph System

Journal of Forensic Sciences The CPS algorithm demonstrated accuracy rates of 95-96% on confirmed truthful cases and 85-95% on deceptive cases in field validation studies, performing comparably to or… Scoring & Test Data Analysis [160] Donnie W. Dutton (2001)

The Rank Order Scoring System: Replication and Extension with Field Data

Polygraph ROSS achieved 80.3% accuracy with inconclusives and 91.6% without them in a 300-case field sample, showing no statistically significant difference in accuracy compared to traditional… Scoring & Test Data Analysis [161] Stuart M. Senter (2001)

New Decision Rule Development: Exploration of a Two-Stage Approach

DoDPI Research Reports The Two-Stage Rule (TSR) successfully reduced the proportion of inconclusive polygraph test results while maintaining classification accuracy equivalent to the Grand Total Rule alone, with… Scoring & Test Data Analysis [162] Donnie W. Dutton (2000)

Guide for Performing the Objective Scoring System

Polygraph Dutton's guide demonstrated that all OSS scoring decisions can be derived entirely from direct physical measurement of three Kircher physiological features, eliminating subjective chart interpretation… Scoring & Test Data Analysis [163] Stanley Abrams (2000)

Polygraph Validity in the New Millennium

Polygraph The 7-position scale with +/-6 cutoff achieved highest accuracy with elevated inconclusive rates; accuracy was higher for truthful than deceptive subjects (reversing prior findings); electrodermal… Field Validity Studies [164] Dollins, A.B., Krapohl, D.J., Dutton, D.W. (2000)

Comparison of computerized polygraph scoring algorithms

Journal of Forensic Sciences All five algorithms demonstrated comparable accuracy (88-91% correct decisions excluding inconclusives) but exhibited false positive rates of 31-46% when inconclusives were treated as errors, with… Scoring & Test Data Analysis [165] Krapohl, D. J., Norris, W. F. (2000)

An exploratory study of traditional and objective scoring systems with MGQT field cases

Polygraph Human scorers demonstrated better sensitivity to deception while the OSS model outperformed human scorers in specificity to truthfulness, revealing that applying cumulative scoring models to… Scoring & Test Data Analysis [166] Donnie W. Dutton (1999)

A Comparison of Computer Programs Designed to Evaluate Psychophysiological Detection of Deception Examinations: Bakeoff 1

Department of Defense Polygraph Institute Report All five computer scoring programs achieved statistically equivalent accuracy rates of 88–91% on definitive decisions, with no single program significantly outperforming the others; four of… Scoring & Test Data Analysis [167] Bartlett, M.S., Hager, J.C., Ekman, P., Sejnowski, T.J. (1999)

Measuring facial expressions by computer image analysis

Psychophysiology The automated hybrid system achieved 91% accuracy in recognizing six upper facial Action Units, outperformed non-expert humans, matched expert-level performance, and reduced coding time from… Neuroimaging & New Technologies [168] Blackwell, N.J. (1999)

PolyScore 3.3 and psychophysiological detection of deception examiner rates of accuracy when scoring examinations from actual criminal investigations

Polygraph PolyScore 3.3 achieved 90.9% accuracy on ZCT examinations but lower accuracy on MGQT examinations, while human PDD examiners achieved 82.3% accuracy on MGQT using the… Scoring & Test Data Analysis [169] David C. Raskin; Charles Robert Honts (1996 • FIELD STUDY)

A Field Study of the Validity of the Utah CQT

University of Utah Department of Psychology (NIJ Grant) Large-scale NIJ-funded field study of actual criminal cases. Found overall accuracy exceeding 90% with experienced examiners using numerical scoring. Included 160+ confirmed criminal cases. Field Validity Studies [170] Dennis C. Brown (1995)

Computerized lie detection: Advancing the state of the art

Journal of Police and Criminal Psychology The conversion from analog to digital recording eliminated subjective errors in manual chart measurements, while real-time data acquisition enabled artifact correction and rapid analysis, representing… Foundational & Historical Research [171] Kohei Adachi (1995)

Statistical Classification Procedures for Polygraph Tests of Guilty Knowledge

Behaviormetrika Both within-subject and training-data statistical approaches achieved approximately 80% correct classification accuracy with adequate observations, outperforming human chart interpretation, though the within-subject method deteriorated with… Scoring & Test Data Analysis [172] Elaad, E. (1994)

The Accuracy of Human Decisions and Objective Measurements in Psychophysiological Detection of Knowledge

The Journal of Psychology All three measurements discriminated better than chance, but objectively measured SRR and RLL proved superior to subjective human respiration evaluation (RRE). Skin resistance showed the… Concealed Information Test (CIT) [173] Jan Stefan Widacki (1994)

The current status of research in forensic psychophysiology and its application in the psychophysiological detection of deception

Polygraph The computerization of polygraph represented the most significant technological advance, with research directed toward new sensors, digitized data collection, automated diagnostic algorithms, and countermeasure detection… Foundational & Historical Research [174] Benjamin Knapp, Mitra Dastmalchi, Eric Jacobs, Shahab Layeghi (1993)

The Use of Fuzzy Set Classification for Pattern Recognition of the Polygraph

The fuzzy k-nearest neighbor algorithm successfully classified polygraph data using optimized feature combinations from multiple physiological channels, demonstrating that machine learning approaches could extract meaningful… AI & Machine Learning in Deception Detection [175] Mary K. Devitt (1993)

Multivariate classifiers perform as well as experts in the detection of deception

Statistical multivariate classifiers — including discriminant analysis and a bootstrap approach — achieved accuracy statistically equivalent to expert human evaluators on polygraph CQT data, with… Scoring & Test Data Analysis [176] Charles R. Honts, Mary K. Devitt (1992)

Bootstrap Decision Making for Polygraph Examinations,

Bootstrap resampling outperformed both human numerical evaluation and discriminant analysis in absolute terms. However, the expert human scorers likely overestimated typical field examiner accuracy, making… Scoring & Test Data Analysis [177] Mary K. Devitt (1992)

Neural network classifiers and the detection of deception revisited: Depth of learning and overfitting

Psychophysiology Neural network classifiers applied to polygraph data were found to be highly susceptible to overfitting, with deeper training producing inflated apparent accuracy that sharply deteriorated… AI & Machine Learning in Deception Detection [178] Raskin, D.C., Kircher, J.C. (1990)

Development of a Computerized Polygraph System and Physiological Measures for Detection of Deception and Countermeasures: A Pilot Study

Contract Report The study demonstrated the feasibility of fully computerized polygraph systems for both data acquisition and automated analysis, contributing to algorithms and measurement techniques that formed… Foundational & Historical Research [179] John C. Kircher; David C. Raskin (1988 • COMPUTERIZED SCORING)

Human Versus Computerized Evaluations of Polygraph Data in a Laboratory Setting

Journal of Applied Psychology Compared human examiner scoring with computerized analysis. Found computerized evaluations achieved accuracy of at least 90%, equaling or exceeding human scorers. Demonstrated feasibility of automated… Scoring & Test Data Analysis [180] David C. Raskin; John C. Kircher; Charles Robert Honts; Steven W. Horowitz (1988 • LANDMARK FIELD STUDY)

A Study of the Validity of Polygraph Examinations in Criminal Investigation

National Institute of Justice, Grant No. 85-IJ-CX-0040 Major NIJ-funded field study demonstrating that CQT accuracy exceeded 90% when properly employed by skilled examiners. Established benchmark for forensic polygraph validity in actual criminal… Field Validity Studies [181] Charles Robert Honts; John C. Kircher; David C. Raskin (1988 • RESEARCH)

Patterns of Activation and Deception

Psychophysiology Examined physiological activation patterns during deceptive vs. truthful responding. Found distinct activation patterns across respiratory, cardiovascular, and electrodermal channels that differentiate truth from deception. Psychophysiology & Autonomic Responses [182] David C. Raskin; John C. Kircher; Charles Robert Honts; Steven W. Horowitz (1988 • CROSS-VALIDATION)

Replication and Cross-Validation of Utah Mock Crime Study

University of Utah (Grant Report) Cross-validation study confirming earlier findings. Demonstrated replicability of CQT accuracy across multiple independent experiments with different examiners and participant pools. Field Validity Studies [183] Lawrence N. Driscoll; Charles Robert Honts; D. Jones (1987 • FIELD STUDY)

Polygraph Field Test Accuracy of CQT in Criminal Cases

Law and Human Behavior Field validation using confirmed criminal case outcomes. Achieved accuracy rates above 90% for both truthful and deceptive classifications, consistent with laboratory findings. Field Validity Studies [184] Kircher, J.C., Raskin, D.C. (1982)

Cross-validation of a computerized diagnostic procedure for detection of deception

Psychophysiology Computerized discriminant analysis achieved accuracy rates equivalent to experienced human evaluators in classifying guilty and innocent subjects, with successful cross-validation demonstrating generalizability across independent samples. Scoring & Test Data Analysis [185] Szucko, J.J., Kleinmuntz, B. (1981)

Statistical versus clinical lie detection

American Psychologist Clinical interpretation achieved 71% detection of guilty subjects but misclassified 50% of innocent participants as deceptive, while statistical analysis achieved 80% overall accuracy, suggesting examiners… Scoring & Test Data Analysis [186] Kircher, J. C. (1981)

Computerized chart evaluation in the detection of deception

The computerized algorithm achieved classification accuracy comparable to expert human examiners, with skin conductance amplitude emerging as the most diagnostic measure and multivariate discriminant analysis… Scoring & Test Data Analysis [187] Kubis, J. F. (1964)

Analysis of Polygraphic Data

Contrary to expectations, Dependent Judgment situations (comparing multiple suspects' charts) did not increase decision accuracy over Independent Judgment (evaluating charts individually), possibly due to greater… Scoring & Test Data Analysis [188] Joseph F. Kubis (1962)

Studies in Lie Detection: Computer Feasibility Considerations

RADC-TR 62-205, U.S. Air Force One of the earliest studies exploring computer-assisted analysis of polygraph data. Commissioned by the Air Force. Laid the groundwork for computerized scoring methods that would… Foundational & Historical Research [189] Jonathan Dowdall, Ioannis Pavlidis, Panagiotis Tsiamyrtzis (0)

Coalitional Tracker for Deception Detection in Thermal Imagery

Augmented Vision Perception in Infrared The coalitional tracking method achieved 82% deception classification accuracy, a 20% improvement over previous methods, while maintaining pixel-level tracking accuracy even during unrestricted subject movement.… Neuroimaging & New Technologies