November 13, 2017Journal of Low Power Electronics and ApplicationsOpen Access

Sleep Stage Classification by a Combination of Actigraphic and Heart Rate Signals

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Why the study?

Does a combined model of heart rate variability and actigraphic data accurately classify sleep stages in human subjects?

Structured PICO

Does a combined model of heart rate variability and actigraphic data accurately classify sleep stages in human subjects?

Population

289 subjects providing 40,643 epochs (length 3 min) of polysomnographic data

Intervention

Combined model consisting of autonomic functional indices from heart rate variability and body movement indices derived from actigraphic data

Outcome

Discrimination of non-rapid-eye-movement (REM) sleep from waking/REM sleep, and REM sleep from wakingsurrogate

Combining heart rate variability and actigraphic signals provides moderate accuracy for classifying sleep stages, which may be useful for wearable sensors.

Discussion

No takes yet. Share an insight, caveat, or question.

Implication

May support wearable sleep staging development; leaves open prospective validation before clinical use.

Cite This Study

Yuda et al. (2017) studied this question.

synapsesocial.com/papers/6a833778f9f199a528d4f3c7 https://doi.org/10.3390/jlpea7040028

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Sleep Stage Classification by a Combination of Actigraphic and Heart Rate Signals

Structured PICO

Discussion

Implication

Cite This Study

Sleep Stage Classification by a Combination of Actigraphic and Heart Rate Signals

Structured PICO

Discussion

Implication

Cite This Study

Also Consider

Also Consider