Philippe Renevey, Patrick Celka, Simon Arberet, Enric Muntané Calvo, Josep Solà i Carós, Claudio Sartori, Mattia Bertschi, Mathieu Lemay
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Photoplethysmography; sleep stages; REM; NREM;hypnogram, heart rate variability.
In this ongoing study we present the preliminary results of
a fully automatic sleep stages classification based on
acceleration and photoplethysmography signals recorded
at wrist. The device consists in a bracelet integrating
sensors, processing unit, communication capabilities, and
power management. The bracelet has been worn by two
healthy volunteers during a night period at hospital in
combination to a complete polysomnograph. Spectral
analysis of heartbeat intervals in standard HRV frequency
bands, as well as movement activity level have been
performed and used to differentiate 3 sleep states: WAKE,
REM and NREM. The automatic classification has been
compared to the hypnogram provided by a professional
clinician using standard polysomnography procedure.
Classification rates up to 90% have been achieved for
NREM state and between 44% and 72% for REM state.
High confusion coefficients for WAKE state is reported
and results from hypnographic misalignment with the