Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
Research output: Contribution to journal › Article
BACKGROUND: Measuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion.
OBJECTIVE: The purpose of this pilot study was to investigate the association between specific sleep measures and the change of emotional status based on voice patterns measured before and after nighttime sleep.
METHODS: A total of 20 volunteers were recruited. Their objective sleep measures were obtained using a portable single-channel electroencephalogram system, and their emotional status was assessed using MIMOSYS, a smartphone app analyzing voice patterns. The study analyzed 73 sleep episodes from 18 participants for the association between the change of emotional status following nighttime sleep (Δvitality) and specific sleep measures.
RESULTS: A significant association was identified between total sleep time and Δvitality (regression coefficient: 0.036, P=.008). A significant inverse association was also found between sleep onset latency and Δvitality (regression coefficient: -0.026, P=.001). There was no significant association between Δvitality and sleep efficiency or number of awakenings.
CONCLUSIONS: Total sleep time and sleep onset latency are significantly associated with Δvitality, which indicates a change of emotional status following nighttime sleep. This is the first study to report the association between the emotional status assessed using voice pattern and specific sleep measures.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Journal||JMIR formative research|
|Publication status||Published - 2020 Jun 9|