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Performance comparison between wrist and chest actigraphy in combination with heart rate variability for sleep
Md Aktaruzzaman1, Massimo Walter Rivolta2, Ruby Karmacharya2
1Dipartimento di Informatica, Università degli Studi di Milano, Crema, Italy; Department of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh.
Computers in Biology and Medicine
|August 26, 2017
Summary
Chest and wrist actigraphy combined with heart rate variability (HRV) show promise for sleep monitoring. Wrist actigraphy alone achieved 77% accuracy, with chest actigraphy slightly higher at 78%.
Area of Science:
- Biomedical Engineering
- Sleep Science
- Wearable Technology
Background:
- Concurrent use of actigraphy and heart rate variability (HRV) for sleep efficiency is under investigation.
- Objective sleep vs. wake classification accuracy needs improvement for home monitoring.
Purpose of the Study:
- Compare chest (CACT) and wrist (WACT) actigraphy with HRV for automatic sleep/wake classification.
- Determine optimal signal length and feature sets for accurate sleep monitoring.
- Evaluate the added value of HRV when combined with actigraphy.
Main Methods:
- Collected accelerometer and ECG signals during polysomnographic studies (PSGs) in 18 healthy adults.
- Extracted 11 features from HRV and accelerometry, using a support vector machine (SVM) for classification.
- Identified 7-minute signal length as optimal for maximizing specificity.
Main Results:
- CACT (78%) and WACT (77%) showed similar accuracies, outperforming HRV alone (66%).
- Adding HRV to CACT improved specificity (33% to 51%) but slightly reduced accuracy.
- HRV with WACT did not yield statistically significant improvements over WACT alone.
Conclusions:
- Actigraphy, particularly chest-mounted, offers effective automatic sleep/wake classification.
- Combining HRV with actigraphy provides marginal benefits, with potential for improved specificity.
- Reduced feature sets maintain classification performance, supporting efficient wearable device design for home sleep monitoring.
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