Validity of the Technique for the Concealed Information Revealing Based on the Registration of Heart Rate during Polygraph Testing

The construction of the integral model of polygraph testing implies the disclosure of a method that will be valid on the task of identifying the fact of information concealment. The aim of this study was to verify the criterion validity of polygraph testing method based on the registration of a person's heart rate with the use of a block test. The experiment was carried out in two series, where the examinees concealed autobiographical information, chosen according to the instruction (lie according to the instruction, 1st series), or at their own request (lie for the purpose of deception, 2nd series). The participants in the experiment (40 people in each part) were people undergoing the real polygraph testing, which increased the environmental validity of the experiment. We used indicators that reflect different systems of heart rate regulation and are observed for different types of mathematical calculation, which made it possible to take into account their interindividual variability. Based on the results of the study, the model based on the interpretation of heart rate indicators in the framework of the system-evolutionary approach was developed with a lie detection efficiency of 74.5%.

1. Alexandrov Yu.I. V.B. Shvyrkov: formirovanie novoj paradigmy v psihologii i smezhnyh naukah // Vydayushchiesya uchenye Instituta psihologii RAN / Pod red. A.L. ZHuravleva. M.: Izd-vo «Institut psihologii RAN», 2020. Pp. 218—255.
2. Alexandrov Yu.I. Differenciaciya i razvitie // Teoriya razvitiya: Differencionno-integracionnaya paradigma / sost. N.I. CHuprikova. M.: Yazyki slavyanskih kul'tur, 2009. Pp. 17—28.
3. Anastazi A., Urbina S. Psihologicheskoe testirovanie. 7-e izd. SPb.: Piter, 2007. 688 p.
4. Apanovich V.V., Tishchenko A.G., Znakov V.V., Alexandrov Yu.I. Konstruirovanie blokov analiticheskih i holisticheskih zadach i ih empiricheskaya proverka // Voprosy Psihologii, 2020. No. 4, pp. 142—154.
5. Baevskij R.M., Ivanov G.G. Variabel'nost' serdechnogo ritma: teoreticheskie aspekty i vozmozhnosti klinicheskogo primeneniya // Ul'trazvukovaya i funkcional'naya diagnostika, 2001. No. 3, pp. 108—127.
6. Bahchina A.V., Alexandrov Yu.I. Slozhnost' serdechnogo ritma pri vremennoj sistemnoj dedifferenciacii // Eksperimental'naya psihologiya, 2017. Vol. 10, no. 2, pp. 114—130.
7. Vinokurov E.A. K voprosu ob ispol'zovanii poligrafa v ugolovnom sudoproizvodstve // Problemy pravoohranitel'noj deyatel'nosti, 2018. No. 2, pp. 20.
8. Zhirnov S.I. Skrining / Zhirnov S.I., PritulyakYu.V.; pod red. Alekseeva L.G.M.: Izdatel'stvo «Pero», 2016. 221 p.
9. Isajchev E.S., Isajchev S.A. Metodologicheskie aspekty instrumental'noj «detekcii lzhi» // Mir Psihologii, 2016. Vol. 4, no. 88, pp. 202—214.
10. Kireev M.V. Sistemnaya organizaciya raboty mozga pri obespechenii celenapravlennogo povedeniya: dis. … dok. biol. nauk.: 03.03.01. Sankt-Peterburgskij gosudarstvennyj universitet, Sankt-Peterburg, 2017. 304 p.
11. Klajn P. Spravochnoe rukovodstvo po konstruirovaniyu testov. Kiev, 1994.
12. Kornilova T.V., Kornilov S.A., Chumakova M.A. Longityudnoe issledovanie dinamiki uspeshnosti resheniya studentami analiticheskih, tvorcheskih i prakticheskih zadanij // Psihologicheskaya nauka i obrazovanie, 2010. Vol. 1, pp. 55—68.
13. Kulaichev A.P. Statisticheskoe issledovanie diagnosticheskoj informativnosti pokazatelej variabel'nosti serdechnogo ritma // Funkcional'naya diagnostika, 2012. Vol. 36, no. 1, pp. 56—64.
14. Mihalev V.I., Reuckaya E.A., Koryagina Yu.V. Vliyanie kislorodno-vozdushnoj smesi s soderzhaniem kisloroda 93% na variabel'nost' serdechnogo ritma i system vneshnego dyhaniya sportsmenov // Teoriya i praktika fizicheskoj kul'tury, 2012. No. 11, pp. 12—15.
15. Ogloblin S.I., Molchanov A.Yu. Instrumental'naya «detekciya lzhi»: akademicheskij kurs // YAroslavl': Nyuans, 2004.
16. Polevaya S.A., et al. Telemetricheskie i informacionnye tekhnologii v diagnostike funkcional'nogo sostoyaniya sportsmenov // Sovremennye tekhnologii v medicine, 2012. No. 4, pp. 94—98.
17. Uchaev A.V. Sovremennye metody vyyavleniya skryvaemoj informacii // Psihologicheskij Zhurnal, 2022. Vol. 43, no. 1, pp. 42—50.
18. Uchaev A.V., Alexandrov Yu.I. Sistemno-evolyucionnyj podhod (SEP) kak metodologicheskij bazis proverok na poligrafe // Anan'evskie chteniya—2020. Psihologiya sluzhebnoj deyatel'nosti: dostizheniya i perspektivy razvitiya (v chest' 75-letiya Pobedy v Velikoj Otechestvennoj vojne 1941-1945 gg.). 2020. Pp. 545—546.
19. Uchaev A.V., Alexandrov Yu.I. Obuslovlennye stressom osobennosti aktualizacii sub"ektivnogo opyta v processe sokrytiya informacii // Rossijskij psihologicheskij zhurnal, 2022. Vol. 19, no. 1, pp. 158—172.
20. Fer R., Bakarak V.R. Psihometrika: Vvedenie. Chelyabinsk: Publishing Center of SUSU, 2010.
21. Shvyrkov V.B. Vvedenie v ob"ektivnuyu psihologiyu: Nejronal'nye osnovy psihiki: Izbrannye trudy. M.: Izd-vo «Institut psihologii RAN», 2006. 592 p.
22. Alexandrov Y.I., et al. Neuronal Bases of Systemic Organization of Behavior // Cheung-Hoi Yu. A., Li L. (Eds.).Systems Neuroscience. Advances in Neurobiology, 2018. Vol. 21, pp. 1—33.
23. Bakhchina A.V., et al. Sample entropy of the heart rate reflects properties of the system organization of behaviour // Entropy, 2018. Vol. 20, no. 6, pp. 449.
24. Ben-Shakhar G., Furedy J.J. Theories and applications in the detection of deception: A psychophysiological and international perspective. New York, Springer-Verlag Publ. 2012.
25. Bruni T. Cross-cultural variation and fMRI lie-detection // In Van den Berg B., Klaming L. (Eds.). Technologies on the stand: Legal and ethical questions in neuroscience and robotics, Nijmegen: Wolf Legal Publishers. 2013. Pp. 129—148.
26. Garner D.M., De Souza N.M., Vanderlei L.C.M. Heart rate variability analysis: Higuchi and Katz’s fractal dimensions in subjects with type 1 diabetes mellitus // Romanian Journal of Diabetes Nutrition and Metabolic Diseases, 2018. Vol. 25, no. 3, pp. 289—295.
27. Henriques T., et al. Nonlinear methods most applied to heart-rate time series: A review // Entropy, 2020. Vol. 22, no. 3, pp. 309.
28. Hirota A., et al. Heart rate and heart rate variability in psychophysiological detection of deception // Japanese Journal of Science and Technology for Identification, 2000. Vol. 5, no. 1, pp. 33—54.
29. Kamal S.M., et al. Complexity-based decoding of the coupling among heart rate variability (HRV) and walking path // Frontiers in physiology, 2020. Vol. 11. DOI:10.3389/fphys.2020.602027
30. Kim H.G., et al. Stress and heart rate variability: a meta-analysis and review of the literature // Psychiatry Investigation, 2018.Vol. 15, no. 3, pp. 235.
31. Kircher J.C., et al. Human and computer decision-making in the psychophysiological detection of deception.USA, The University of Utah ProQuest Dissertations Publ., 2005.
32. Krapohl D.J., Dutton D.W. Believing Is Seeing: The Influence of Expectations on Blind Scoring of Polygraph Data // Polygraph, 2018. Vol. 47, no. 2.
33. Levine T.R. Ecological validity and deception detection research design // Communication Methods and Measures, 2018.Vol. 12, no. 1, pp. 45—54.
34. Matsuda I., Ogawa T., Tsuneoka M. Broadening the use of the concealed information test in the field // Frontiers in Psychiatry. 2019. Vol. 10, Article 24. DOI:10.3389/fpsyt.2019.00024
35. Meijer E.H., et al. Deception detection with behavioral, autonomic, and neural measures: Conceptual and methodological considerations that warrant modesty // Psychophysiology, 2016. Vol. 53, no. 5, pp. 593—604.
36. Meijer E.H., et al. Memory detection with the Concealed Information Test: A meta-analysis of skin conductance, respiration, heart rate, and P300 data // Psychophysiology, 2014. Vol. 51, no. 9, pp. 879—904.
37. Spilka J., et al. Using nonlinear features for fetal heart rate classification // Biomedical signal processing and control, 2012. Vol. 7, no. 4, pp. 350—357.
38. Sung M., Pentland A. PokerMetrics: Stress and lie detection through non-invasive physiological sensing // International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association. 2009. Vol. 14. № 2. P. 111—118.
39. Swee T.T., et al. Formulation of a novel HRV classification model as a surrogate fraudulence detection schema // Malaysian Journal of Fundamental and Applied Sciences, 2020. Vol. 16, no. 1, pp. 121—127.