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

Condition(s) studied

Investigational drug(s) / intervention(s)

Use of biofeedback and virtual reality in the treatment of aggressive outbursts: 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.

Study 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.

Eligibility

Primary outcome measure(s)

• 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.
• 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.
• 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.
• 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.

Trial sites (1)

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