TY  - CHAP
U1  - Buchbeitrag
A1  - Gaiduk, Maksym
A1  - Boiko, Andrei
A1  - Conti, Massimo
A1  - Orcioni, Simone
A1  - Martínez Madrid, Natividad
A1  - Seepold, Ralf
ED  - Conti, Massimo
ED  - Orcioni, Simone
T1  - Heart rate estimation based on in-bed accelerometer sensor measurement
T2  - Models and applications for embedded systems
N2  - Accurate monitoring of a patient's heart rate is a key element in the medical observation and health monitoring. In particular, its importance extends to the identification of sleep-related disorders. Various methods have been established that involve sensor-based recording of physiological signals followed by automated examination and analysis. This study attempts to evaluate the efficacy of a non-invasive HR monitoring framework based on an accelerometer sensor specifically during sleep. To achieve this goal, the motion induced by thoracic movements during cardiac contractions is captured by a device installed under the mattress. Signal filtering techniques and heart rate estimation using the symlets6 wavelet are part of the implemented computational framework described in this article. Subsequent analysis indicates the potential applicability of this system in the prognostic domain, with an average error margin of approximately 3 beats per minute. The results obtained represent a promising advancement in non-invasive heart rate monitoring during sleep, with potential implications for improved diagnosis and management of cardiovascular and sleep-related disorders.
Y1  - 2024
UR  - http://www.dii.univpm.it/MAES-2023
SN  - 978-88-87548-00-6
SB  - 978-88-87548-00-6
SP  - 11
EP  - 14
S1  - 4
PB  - Università Politecnica delle Marche
CY  - Ancona
ER  -