Use of Biofeedback and Virtual Reality as Facilitators of Emotional Recognition in the Treatment of Aggressive Outbursts
- Conditions
- Passive-Aggressive Personality Disorder
- Interventions
- Behavioral: Use of biofeedback and virtual reality in the treatment of aggressive outbursts
- Registration Number
- NCT05748808
- Lead Sponsor
- University of Seville
- Brief Summary
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.
- Detailed Description
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.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 60
- 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.
- 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.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description Tweens and teens Use of biofeedback and virtual reality in the treatment of aggressive outbursts Kids between 10 and 16. ADHD, Asperger or ODD, with lack of aggressiveness control.
- Primary Outcome Measures
Name Time Method Skin Temperature (ST) 1 hour 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.
electrodermal activity (EDA) 1 hour 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.
Heart Rate Variability (HRV) 1 hour 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.Electroencephalography (EEG) 1 hour 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.
Breathing Rate (BR) 1 hour Number of breaths a person takes per minute.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Universidad de Sevilla
🇪🇸Sevilla, Spain