Lie detection on pupil size by back propagation neural network

Nurçin, Fatih Veysel; Imanov, Elbrus; Işın, Ali; Ozsahin, Dilber Uzun

doi:10.1016/j.procs.2017.11.258

Cited by 9 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The goal of [19]'s research is to identify lies by examining and analyzing the pupil dilation of the human eye using a neural network and the backpropagation method. The 60 preprocessed data were fed into a neural network.…”

Section: Related Workmentioning

confidence: 99%

Explainable Enhanced Recurrent Neural Network for lie detection using voice stress analysis

Talaat

2023

Multimed Tools Appl

View full text Add to dashboard Cite

Lie detection is a crucial aspect of human interactions that affects everyone in their daily lives. Individuals often rely on various cues, such as verbal and nonverbal communication, particularly facial expressions, to determine if someone is truthful. While automated lie detection systems can assist in identifying these cues, current approaches are limited due to a lack of suitable datasets for testing their performance in real-world scenarios. Despite ongoing research efforts to develop effective and reliable lie detection methods, this remains a work in progress. The polygraph, voice stress analysis, and pupil dilation analysis are some of the methods currently used for this task. In this study, we propose a new detection algorithm based on an Enhanced Recurrent Neural Network (ERNN) with Explainable AI capabilities. The ERNN, based on long short-term memory (LSTM) architecture, was optimized using fuzzy logic to determine the hyperparameters. The LSTM model was then created and trained using a dataset of audio recordings from interviews with a randomly selected group. The proposed ERNN achieved an accuracy of 97.3%, which is statistically significant for the problem of voice stress analysis. These results suggest that it is possible to detect patterns in the voices of individuals experiencing stress in an explainable manner.

show abstract

Section: Related Workmentioning

confidence: 99%

Explainable Enhanced Recurrent Neural Network for lie detection using voice stress analysis

Talaat

2023

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…Deception atau ketidakjujuran dapat dideteksi dengan memperhatikan ukuran pupil dari orang yang sedang berbicara [8][9] [10], cara lain dalam mendeteksi kejujuran adalah memberikan pertanyaan yang tidak terduga atau unexpected question [11] [12]. Pada penelitian ini kami menggabungkan pertanyaan diagnose covid 19 dengan pertanyaan yang tidak terduga dengan memantau perubahan pupil dari pasien dalam menjawab pertanyaan.…”

Section: Pendahuluanunclassified

“…Pergerakan pupil dapat digunakan untuk mendeteksi kebohongan. Beberapa penelitian memantau pergerakan dan ukuran pupil untuk mendeteksi kebohongan, antara lain penelitian oleh [10] memantau lebar dari pupil dan kedipan mata menggunakan metode Hough Transform dan Frame Difference dengan Fuzzy Logic, penelitian lain oleh [9] memantau pergerakan mata dan ukuran pupil untuk mendeteksi kebohongan, penelitian lain oleh [8] memantau ukuran pupil menggunakan neural network. Selain itu juga ada penelitian yang dilakukan oleh [17] telah membuat sistem pendeteksian kebohongan melalui perubahan diameter pupil mata, dimana Sistem yang dibuat dapat mengetahui perubahan diameter pupil mata, untuk mengetahui kebohongan yang dilakukan oleh seseorang.…”

Section: Pendahuluanunclassified

Sistem Pakar Deteksi Covid-19 Dengan Lie Detection Menggunakan Metode Circle Hough Transform

Priambodo,

Jumaryadi

2022

JoSYC

View full text Add to dashboard Cite

The number of health workers infected with Covid-19 in Indonesia continues to grow amid the coronavirus pandemic. Not only doctors, nurses and other medical support staff have been exposed to Covid-19. To date, IDI has recorded more than 180 health workers who have died from Corona. Health workers are dying because of a lack of Personal Protective Equipment (PPE) and fatigue. Prevention of direct contact between asymptomatic patients and health workers is a way to prevent health workers from contracting COVID-19. An expert system for diagnosing COVID-19 with lie detection is proposed to be used for patients who wish to seek treatment at a health center before they meet face-to-face with health workers. Several previous studies have proven that the certainty method can be used to diagnose COVID-19 with an accuracy of up to 90%, provided that the patient answers questions honestly. In this study, control questions and pupil detection were added using the circle hard transform to find out whether patients who wanted treatment did not lie when answering questions about symptoms of exposure to Covid, travel history and family history of exposure to Covid. The combination of an expert system and lie detection is expected to be the first protective alternative for health workers from asymptomatic patients. Based on the results of the application testing carried out, it can be seen that the movement of the patient's pupils when answering questions.

show abstract

“…Pupil dilation presented a larger diameter when subjects lied in true/false questions (Webb et al, ), interviews (Nugroho, Nasrun, & Setianingsih, ), or multiple choices of questions (Nurçin, Imanov, Işın, & Ozsahin, ). Although pupil size metrics may be used to detect lying, eye sizes in subjects of different ethnicities may vary.…”

Section: Introductionmentioning

confidence: 99%

Assessing cognitive load using oculometrics to identify deceit during interviews

Mitre‐Hernandez

Sánchez-Rodríguez

Zataraín-Cabada

et al. 2018

Applied Cognitive Psychology

View full text Add to dashboard Cite

Lying requires a long-term memory search and is a cognitive load task. Telling a spontaneous lie is associated with a higher cognitive load compared with the truth, although when memories are planned before telling a lie, the cognitive load can be less compared with the truth; therefore, telling a spontaneous lie could be associated with a higher cognitive load compared with a planned lie. In this study, we examined cognitive load, as measured through oculometrics, to identify deceit in interviews. Twenty-four subjects were questioned, and their answers classified as spontaneous lies, planned lies, and truths. Results show that saccades and fixations were associated with a higher cognitive load when telling spontaneous lies compared with telling truths. Blinks and pupillometry show that subjects require greater cognitive load when telling truths compared with planned lies. Finally, telling spontaneous lies required higher cognitive load compared with planned lies, as assessed by blinks.

show abstract

Lie detection on pupil size by back propagation neural network

Cited by 9 publications

References 9 publications

Explainable Enhanced Recurrent Neural Network for lie detection using voice stress analysis

Explainable Enhanced Recurrent Neural Network for lie detection using voice stress analysis

Sistem Pakar Deteksi Covid-19 Dengan Lie Detection Menggunakan Metode Circle Hough Transform

Assessing cognitive load using oculometrics to identify deceit during interviews

Contact Info

Product

Resources

About