Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study

BackgroundMeasuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion. ObjectiveThe purpose of this pilot study was to investigate the association between specific sleep measures and the...

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Main Authors: Miyashita, Hirotaka, Nakamura, Mitsuteru, Svensson, Akiko Kishi, Nakamura, Masahiro, Tokuno, Shinichi, Chung, Ung-Il, Svensson, Thomas
Format: Article
Language:English
Published: JMIR Publications 2020-06-01
Series:JMIR Formative Research
Online Access:https://formative.jmir.org/2020/6/e16880
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spelling doaj-56123fcefab341d88a12e1d15fa457832021-04-02T19:20:35ZengJMIR PublicationsJMIR Formative Research2561-326X2020-06-0146e1688010.2196/16880Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot StudyMiyashita, HirotakaNakamura, MitsuteruSvensson, Akiko KishiNakamura, MasahiroTokuno, ShinichiChung, Ung-IlSvensson, Thomas BackgroundMeasuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion. ObjectiveThe 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. MethodsA 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. ResultsA 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. ConclusionsTotal 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.https://formative.jmir.org/2020/6/e16880
collection DOAJ
language English
format Article
sources DOAJ
author Miyashita, Hirotaka
Nakamura, Mitsuteru
Svensson, Akiko Kishi
Nakamura, Masahiro
Tokuno, Shinichi
Chung, Ung-Il
Svensson, Thomas
spellingShingle Miyashita, Hirotaka
Nakamura, Mitsuteru
Svensson, Akiko Kishi
Nakamura, Masahiro
Tokuno, Shinichi
Chung, Ung-Il
Svensson, Thomas
Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
JMIR Formative Research
author_facet Miyashita, Hirotaka
Nakamura, Mitsuteru
Svensson, Akiko Kishi
Nakamura, Masahiro
Tokuno, Shinichi
Chung, Ung-Il
Svensson, Thomas
author_sort Miyashita, Hirotaka
title Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
title_short Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
title_full Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
title_fullStr Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
title_full_unstemmed Association Between Electroencephalogram-Derived Sleep Measures and the Change of Emotional Status Analyzed Using Voice Patterns: Observational Pilot Study
title_sort association between electroencephalogram-derived sleep measures and the change of emotional status analyzed using voice patterns: observational pilot study
publisher JMIR Publications
series JMIR Formative Research
issn 2561-326X
publishDate 2020-06-01
description BackgroundMeasuring emotional status objectively is challenging, but voice pattern analysis has been reported to be useful in the study of emotion. ObjectiveThe 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. MethodsA 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. ResultsA 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. ConclusionsTotal 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.
url https://formative.jmir.org/2020/6/e16880
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