Abstract

For children with profound disabilities affecting communication, it can be extremely challenging to identify salient emotions such as anxiety. If left unmanaged, anxiety can lead to hypertension, cardiovascular disease, and other psychological diagnoses. Physiological signals of the autonomic nervous system are indicative of anxiety, but can be difficult to interpret for non-specialist caregivers. This paper evaluates an auditory interface for intuitive detection of anxiety from physiological signals. The interface, called “Biomusic,” maps physiological signals to music (i.e., electrodermal activity to melody; skin temperature to musical key; heart rate to drum beat; respiration to a “whooshing” embellishment resembling the sound of an exhalation). The Biomusic interface was tested in two experiments. Biomusic samples were generated from physiological recordings of typically developing children (n = 10) and children with autism spectrum disorders (n = 5) during relaxing and anxiety-provoking conditions. Adult participants (n = 16) were then asked to identify “anxious” or “relaxed” states by listening to the samples. In a classification task with 30 Biomusic samples (1 relaxed state, 1 anxious state per child), classification accuracy, sensitivity, and specificity were 80.8% [standard error (SE) = 2.3], 84.9% (SE = 3.0), and 76.8% (SE = 3.9), respectively. Participants were able to form an early and accurate impression of the anxiety state within 12.1 (SE = 0.7) seconds of hearing the Biomusic with very little training (i.e., < 10 min) and no contextual information. Biomusic holds promise for monitoring, communication, and biofeedback systems for anxiety management.

Highlights

  • Medical advancements have led to a growing number of people surviving previously fatal medical complications, and subsequently living with profound disabilities

  • Performance measures for the subset of songs recorded from typically-developing children (n = 20) and the subset associated with children with autism spectrum disorders (ASD) (n = 10) are noted

  • Participants listened to the Biomusic for 11.3 s (SE = 0.5 s) before completing the classification task

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Summary

Introduction

Medical advancements have led to a growing number of people surviving previously fatal medical complications, and subsequently living with profound disabilities For these individuals, survival depends on life-supporting technologies and teams of caregivers who can anticipate and respond to their complex continuing care needs. In the absence of a reliable communication pathway, the needs, thoughts, and feelings of those with profound disabilities are at risk of being overlooked, which presents concerning challenges to health and well-being (Blain-Moraes et al, 2013). This motivates the urgent need to establish communication channels with individuals with profound disabilities and methods for discerning their emotional states

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