What is it about?
This paper presents an innovative technology called UbiCAT to support taking cognitive tests outside clinics. UbiCAT can be used to identify mental disorders particularly bipolar disorder and depression through cognitive tests. Mobile sensor data is also collected for this study, which lasted 7 days pr. participant. Our findings show that more sleeping hours participants led to better working memory of the individuals the following day. Digital phenotypes of mental health are also extracted from our dataset. Sleep hours,, step counts, attention, and executive functions of the healthy individuals and bipolar patients were significantly different from each other. In addition, we applied supervised learning methods on the cognitive and mobile sensor data. K-nearest neighbourhood outperformed the classification methods with an accuracy of 74%.
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Why is it important?
Neuropsychological tests as a crucial tool for determining mental disorders are limited to clinical administration while UbiCAT is shown to be an accurate tool in assessing individuals' cognitive functioning in their free-living conditions. Therefore, psychologists can ask their patients to take the cognitive tests using UbiCAT without coming to the clinic. It should be noted that eHealth technologies are essential during the pandemic.
Perspectives
Future cognition-aware systems can utilise the findings of our paper to sense individuals' cognition passively everyday and frequently in order to support mental health of people.
Pegah Hafiz
Read the Original
This page is a summary of: Wearable Computing Technology for Assessment of Cognitive Functioning of Bipolar Patients and Healthy Controls, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, December 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3432219.
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