Accepted for/Published in: JMIR Formative Research
Date Submitted: Oct 2, 2020
Date Accepted: Jan 18, 2021
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Correlations between facial expressivity and apathy in elderly people with Neurocognitive Disorders
ABSTRACT
Background:
Neurocognitive disorders are often accompanied by behavioral symptoms such as anxiety, depression, and/or apathy. These symptoms can occur very early in the disease progression, and are often difficult to detect and quantify in non-specialized clinical settings. We focus in this study on apathy, one of the most common and debilitating neuropsychiatric symptoms in neurocognitive disorders. Specifically, we investigated whether facial expressivity extracted trough computer vision software correlates with the severity of apathy symptoms in elderly subjects with neurocognitive disorders.
Objective:
Specifically, we investigated whether facial expressivity extracted trough computer vision software correlates with the severity of apathy symptoms in elderly subjects with neurocognitive disorders.
Methods:
63 subjects (38 females and 25 males) with neurocognitive disorder participated in the study. Apathy was assessed using the Apathy Inventory (AI), a scale which comprises three domains of apathy: loss of interest, loss of initiation and emotional blunting. The higher the scales score, the more severe the apathy symptoms. Participants were asked to recall a positive and a negative event of their life, while their voice and face were recorded through a tablet device. Action Units (AU), which are basic facial movements, were extracted using OpenFace 2.0. 17 AUs (intensity and presence) for each frame of the video were extracted in both positive and negative storytelling. Average intensity and frequency of AU activation were calculated for each participant in each video. Partial correlations (controlling for the level of depression and cognitive impairment) were performed between these indexes and AI subscales.
Results:
Results showed that AU intensity and frequency were negatively correlated with apathy scales scores, in particular with the emotional blunting component. The more severe the apathy symptoms, the less expressivity was displayed from participants while recalling an emotional event in specific emotional and non-emotional AUs. Different AUs showed significant correlations depending on gender of the participant and the task (positive vs negative story), suggesting the importance to assess independently male and female participants.
Conclusions:
Our study suggest the interest of employing computer vision based facial analysis to quantify facial expressivity and assess the severity of apathy symptoms in subjects with Neurocognitive Disorders. This may thus represent a useful tool for a preliminary apathy assessment in non-specialized settings, and could be used to complement classical clinical scales. Future studies including larger samples should confirm the clinical relevance of this kind on instrument. Clinical Trial: N/A
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