Signal processing and feature extraction for sleep evaluation in wearable devices
Conference Paper
-
- Overview
-
- Research
-
- Identity
-
- Additional Document Info
-
- View All
-
Overview
abstract
-
In this paper we discuss the possibility of performing a sleep evaluation form the heart rate variability (HRV) and respiratory signals. This is particularly useful for wearable devices. The HRV and the respiration were analyzed in the frequency domain and the statistics on the spectral and cross-spectral parameters put into evidence the possibility of a sleep evaluation on their basis. Additional information can be achieved from the number of microarousals recognized in correspondence of typical modifications in the HRV signal. © 2006 IEEE.
publication date
published in
Research
keywords
-
Heart rate variability (HRV); Respiratory signals; Feature extraction; Frequency domain analysis; Medical computing; Respiratory system; Signal processing; Wearable computers; analysis of variance; arousal; article; autonomic nervous system; biomedical engineering; breathing; case control study; equipment; heart rate; human; methodology; pathophysiology; polysomnography; positive end expiratory pressure; signal processing; sleep disordered breathing; statistics; Analysis of Variance; Arousal; Autonomic Nervous System; Biomedical Engineering; Case-Control Studies; Continuous Positive Airway Pressure; Heart Rate; Humans; Polysomnography; Respiration; Signal Processing, Computer-Assisted; Sleep Apnea, Obstructive
Identity
Digital Object Identifier (DOI)
PubMed ID
Additional Document Info