Use of Biofeedback and Virtual Reality as Facilitators of Emotional Recognition in the Treatment of Aggressive Outbursts (BReTIA)

Use of Biofeedback and Virtual Reality as Facilitators of Emotional Recognition in the Treatment of Aggressive Outbursts

Use of Biofeedback and Virtual Reality as Facilitators of Emotional Recognition in the Treatment of Aggressive Outbursts

The methodology will be applied for the treatment of aggressive episodes. Many people show this kind of behavior associated with several psychological disorders like austistic spectrum disorder (ASD). It will be studied the effect of aggressive outbursts on several physiological signals (heart rate (HR), breathing rate (BR), electroencephalography (EEG), etc). The use of those signals in a biofeedback loop could help patients recognize their internal states and avoid imminent aggression. The study want to verify the efficacy of a cognitive therapy that includes biofeedback and virtual reality (VR) and find out the most significant physiological features that are affected by these episodes.

The first goal is to register the scene together with physiological values before, during and after at least up to four aggressive outbursts at home. Next an outburst is induced and physiological signals before, during and after the aggressive episode are recorded. After it the participants go to a new relaxation phase for another 10-minute period using the VR. In following sessions, they are trained to identify their physiological response when they are relaxed and when an outburst is coming. To do that, the VR system receives and shows the physiological information on the virtual scenario. In following sessions, teenagers are then treated with cognitive, behavioral and emotional self-regulation therapies, which have proven their effectiveness for managing anger and learning positive coping skills. The underlying theory is that people can minimize their negative feelings and behaviors when they are aware of their irrational beliefs and work to change their minds, by focusing on them continuously. At the end of the experiment, the number of aggressive episodes in the last weeks of the intervention will be measured. The differences between the new scores, with respect to the initial ones, will be used to assess the efficacy of the intervention.

Participants are trained to identify their physiological response when they are relaxed and when an outburst is coming. They are treated with cognitive, behavioral and emotional self-regulation therapies for managing anger and learning positive coping skills. Biofeedback toghether with virtual reality help them to improve their recognition and control of emotions.

The HRV is especially interesting because it allows as-sessing the activity of the parasympathetic and sympathetic pathways of the autonomic nervous system. We used a wearable placed in the chest with Ag/AgCl electrodes for ECG, placed following the Einthoven's II lead positions. The position of R wave is determined using an appropriate algorithm and then time difference between two consecutive R waves is calculated, this time difference is used to calculed HR. We used 30s-length sliding windows with an overlap of 50%. The instantaneous HR is given by the average HR in such a window after removing the outliers.

EDA is a measure of conductivity of human skin cause by the sweating, and can provide an indication of changes in human sympathetic nervous system (SNS). To process EDA data, we use Ledalab tools, configured with Continuous Decomposition Analysis (CDA) to recover the characteristics of the underlying signal of the sudomotor nerve; with Standard trough-to-peak (TTP), which analyzes maximums and minimums of the data window; and with Global that offers general values of the data. Recorded data are adapted to Ledalab input format by adding events in the time points when the experimenter introduces a tag. We shall use a two-second window with an overlap of 50% and a sensitivity of 1 μS.

The EEG portrays the functioning of the brain. The recording of those signals will be done at a sampling rate of 125 Hz by OpenBCI. In this study it will be used the 16-channel configuration at a sampling rate of 125Hz and the following electrode placement: FP1, FP2, F1, F2, F5, F6, Cz, C3, C4, T7, T8, Pz, P3, P4, O1, O2 (Figure 5). Additional reference and ground electrodes will be placed on the right ear and Fpz positions respectively.

The temperature of the skin. A minimum window length of 1 min guarantees a spectral resolution of 0.017 Hz at a sampling frequency of 13 Hz.

Inclusion Criteria: Previous diagnosis of ADHD, Asperger syndrome or oppositional defiant disorder (ODD) combined with a lack of control of their aggressiveness. Positive impulsivity result obtained with any of the fol- lowing tests: score lower than 25 in CACIA [13], lower than 50 in CAPI-A [14], greater than 75 in Stroop [15] or greater than 115 in WCST [16]. Intermittent outburst episodes (verbal aggression includ- ing both arguments and temper tantrums, and physical aggression towards self or others) with a frequency of once a week in the two months prior to the beginning of the intervention. Exclusion Criteria: Participants will be excluded if they report (a) current (past month) psychopharmacotherapy, (b) a history of bipolar or psychotic disorder, or (c) a traumatic head injury with a loss of consciousness in excess of 60 minutes.

G. Alsina Masmitja, "Deficits de atencion y trastornos de conducta," Deficits de atencion y trastornos de conducta, pp. 1-259, 2014.

Schonenberg M, Schneidt A, Wiedemann E, Jusyte A. Processing of Dynamic Affective Information in Adults With ADHD. J Atten Disord. 2019 Jan;23(1):32-39. doi: 10.1177/1087054715577992. Epub 2015 Mar 30.

Fahlgren MK, Puhalla AA, Sorgi KM, McCloskey MS. Emotion processing in intermittent explosive disorder. Psychiatry Res. 2019 Mar;273:544-550. doi: 10.1016/j.psychres.2019.01.046. Epub 2019 Jan 14.

Persico AM, Ricciardello A, Lamberti M, Turriziani L, Cucinotta F, Brogna C, Vitiello B, Arango C. The pediatric psychopharmacology of autism spectrum disorder: A systematic review - Part I: The past and the present. Prog Neuropsychopharmacol Biol Psychiatry. 2021 Aug 30;110:110326. doi: 10.1016/j.pnpbp.2021.110326. Epub 2021 Apr 20.

B. M. Appelhans and L. J. Luecken, "Heart rate variability as an index of regulated emotional responding," Review of general psychology, vol. 10, no. 3, pp. 229-240, 2006.

Costescu C, Sogor M, Thill S, Rosan A. Emotional Dysregulation in Preschoolers with Autism Spectrum Disorder-A Sample of Romanian Children. Int J Environ Res Public Health. 2021 Oct 12;18(20):10683. doi: 10.3390/ijerph182010683.

Liddell BJ, Kemp AH, Steel Z, Nickerson A, Bryant RA, Tam N, Tay AK, Silove D. Heart rate variability and the relationship between trauma exposure age, and psychopathology in a post-conflict setting. BMC Psychiatry. 2016 May 10;16:133. doi: 10.1186/s12888-016-0850-5.

Liao YC, Guo NW, Su BY, Chen SJ, Tsai HF, Lee KY. Frontal Beta Activity in the Meta-Intention of Children With Attention Deficit Hyperactivity Disorder. Clin EEG Neurosci. 2021 Mar;52(2):136-143. doi: 10.1177/1550059420933142. Epub 2020 Jun 22.

Shereena EA, Gupta RK, Bennett CN, Sagar KJV, Rajeswaran J. EEG Neurofeedback Training in Children With Attention Deficit/Hyperactivity Disorder: A Cognitive and Behavioral Outcome Study. Clin EEG Neurosci. 2019 Jul;50(4):242-255. doi: 10.1177/1550059418813034. Epub 2018 Nov 20.

V. Delvigne, L. Ris, T. Dutoit, H. Wannous, and J.-P. Vandeborre, "Vera: Virtual environments recording attention," in 2020 IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH). IEEE, 2020, pp. 1-7.

S. Adabla, L. Nabors, and K. Hamblin, "A scoping review of virtual real- ity interventions for youth with attention-deficit/hyperactivity disorder," Advances in Neurodevelopmental Disorders, vol. 5, no. 3, pp. 304-315, 2021.

Karami B, Koushki R, Arabgol F, Rahmani M, Vahabie AH. Effectiveness of Virtual/Augmented Reality-Based Therapeutic Interventions on Individuals With Autism Spectrum Disorder: A Comprehensive Meta-Analysis. Front Psychiatry. 2021 Jun 23;12:665326. doi: 10.3389/fpsyt.2021.665326. eCollection 2021.

A. Capafons and F. Silva, "Cuestionario de autocontrol infantil y adolescente (rev.)," Madrid: TEA, 2001

J. M. Andreu, "Cuestionario de agresividad premeditada e impulsiva en adolescentes," Madrid: Tea Ediciones, 2010

Scarpina F, Tagini S. The Stroop Color and Word Test. Front Psychol. 2017 Apr 12;8:557. doi: 10.3389/fpsyg.2017.00557. eCollection 2017.

R. K. Heaton, G. J. Chelune, J. L. Talley, G. G. Kay, and G. Curtiss, WCST: Test de clasificacion de tarjetas de Wisconsin. TEA Madrid, Spain:, 200

T. Greitemeyer, "The spreading impact of playing violent video games on aggression," Computers in human behavior, vol. 80, pp. 216-219, 2018

Anderson CA, Carnagey NL, Eubanks J. Exposure to violent media: the effects of songs with violent lyrics on aggressive thoughts and feelings. J Pers Soc Psychol. 2003 May;84(5):960-71. doi: 10.1037/0022-3514.84.5.960.

L. Canet-Juric, A. Garcıa-Coni, M. L. Andres, S. Vernucci, Y. Ayd- mune, F. Stelzer et al., "Intervenci ́on sobre autorregulaci ́on cognitiva, conductual y emocional en ninos: Una revision de enfoques basados en procesos y en el currıculo escolar, en argentina," Revista Argentina de Ciencias del Comportamiento, vol. 12, no. 1, pp. 1-25, 2020.

J. A. Castro-Garcıa, A. J. Molina-Cantero, I. M. Gomez-Gonzalez, S. Lafuente-Arroyo, and M. Merino-Monge, "Towards human stress and activity recognition: A review and a first approach based on low-cost wearables," Electronics, vol. 11, no. 1, p. 155, 2022

Boucsein W, Fowles DC, Grimnes S, Ben-Shakhar G, roth WT, Dawson ME, Filion DL; Society for Psychophysiological Research Ad Hoc Committee on Electrodermal Measures. Publication recommendations for electrodermal measurements. Psychophysiology. 2012 Aug;49(8):1017-34. doi: 10.1111/j.1469-8986.2012.01384.x. Epub 2012 Jun 8.

Werner J, Heising M, Rautenberg W, Leimann K. Dynamics and topography of human temperature regulation in response to thermal and work load. Eur J Appl Physiol Occup Physiol. 1985;53(4):353-8. doi: 10.1007/BF00422853.

J. Werner, "Measurement of temperatures of the human body," Comprehensive Biomedical Physics, pp. 107-126, 2014. [Online]. Available: https://doi.org/10.1016/b978-0-444-53632-7.00515-3