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Toward Sensor-Based Sleep Monitoring with Electrodermal Activity Measures
- Source :
- Sensors (Basel, Switzerland), Sensors, Vol 19, Iss 6, p 1417 (2019), Sensors, Volume 19, Issue 6
- Publication Year :
- 2019
-
Abstract
- We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep of six participants to test the efficacy of EDA data for sleep monitoring. We used factor analysis to find latent factors in the EDA data, and used causal model search to find the most probable graphical model accounting for self-reported sleep efficiency (SE), sleep quality (SQ), and the latent factors in the EDA data. Structural equation modeling was used to confirm fit of the extracted graph to the data. Based on the generated graph, logistic regression and na&iuml<br />ve Bayes models were used to test the efficacy of the EDA data in predicting SE and SQ. Six EDA features extracted from the total signal over a night&rsquo<br />s sleep could be explained by two latent factors, EDA Magnitude and EDA Storms. EDA Magnitude performed as a strong predictor for SE to aid detection of substantial changes in time asleep. The performance of EDA Magnitude and SE in classifying SQ demonstrates promise for using a wearable sensor for sleep monitoring. However, our data suggest that obtaining a more accurate sensor-based measure of SE will be necessary before smaller changes in SQ can be detected from EDA sensor data alone.
- Subjects :
- FOS: Computer and information sciences
Adult
Male
Computer Science - Machine Learning
Computer science
Polysomnography
Machine Learning (stat.ML)
Hardware_PERFORMANCEANDRELIABILITY
wearable sensor
lcsh:Chemical technology
Biochemistry
050105 experimental psychology
Article
Analytical Chemistry
Machine Learning (cs.LG)
03 medical and health sciences
Wearable Electronic Devices
0302 clinical medicine
Statistics - Machine Learning
Hardware_GENERAL
Heart Rate
Humans
model search
0501 psychology and cognitive sciences
lcsh:TP1-1185
Electrical and Electronic Engineering
sleep
Instrumentation
Sleep quality
Sleep monitoring
business.industry
05 social sciences
Pattern recognition
Atomic and Molecular Physics, and Optics
electrodermal activity
ROC Curve
Area Under Curve
Artificial intelligence
business
Skin Temperature
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 14248220
- Volume :
- 19
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Sensors (Basel, Switzerland)
- Accession number :
- edsair.doi.dedup.....b2c5d13f0c45f2251fae695c881eebbd