Optomyography-based sensing of facial expression derived arousal and valence in adults with depression - Broulidakis, M. John; Kiprijanovska, Ivana; Severs, Liberty; Stankoski, Simon; Gjoreski, Martin; Mavridou, Ifigeneia; Gjoreski, Hristijan; Cox, Sophia; Bradwell, Daisy; Stone, James M.; Nduka, Charles (Frontiers in Psychiatry, 2023)
Background: Continuous assessment of affective behaviors could improve the diagnosis, assessment and monitoring of chronic mental health and neurological conditions such as depression. However, there are no technologies well suited to this, limiting potential clinical applications.To test if we could replicate previous evidence of hypo reactivity to emotional salient material using an entirely new sensing technique called optomyography which is well suited to remote monitoring.Methods: Thirty-eight depressed and 37 controls (≥18, ≤40 years) who met a research diagnosis of depression and an age-matched non-depressed control group. Changes in facial muscle activity over the brow (corrugator supercilli) and cheek (zygomaticus major) were measured whilst volunteers watched videos varying in emotional salience.Results: Across all participants, videos rated as subjectively positive were associated with activation of muscles in the cheek relative to videos rated as neutral or negative. Videos rated as subjectively negative were associated with brow activation relative to videos judged as neutral or positive. Self-reported arousal was associated with a step increase in facial muscle activation across the brow and cheek. Group differences were significantly reduced activation in facial muscles during videos considered subjectively negative or rated as high arousal in depressed volunteers compared with controls.We demonstrate for the first time that it is possible to detect facial expression hypo-reactivity in adults with depression in response to emotional content using glasses-based optomyography sensing. It is hoped these results may encourage the use of Optomyography-based sensing to track facial expressions in the real-world, outside of a specialized testing environment.