We present a tool-kit for the time domain Heart Rate Variability (HRV) analysis, namely SPINE-HRV (Signal Processing In Node Environment-HRV). The HRV is based on the analysis (time and frequency domain) of the R-peak to R-peak intervals (RR-interval). The tool-kit is composed of a wearable Heart Activity Monitoring System (HAMS) to collect the RR-interval (RRi), and a processing application developed using the SPINE framework. The HAMS used to acquire the RRi signal is self-developed; the hardware system consists of a chest belt communicating wireless with a receiver node. The RRi signal is processed using the SPINE framework through a time domain analysis of HRV. That analysis provides seven common parameters known in medicine literature to help cardiologists in the diagnosis related to several heart diseases. The results have been validated with a commonly used high accuracy HRV software tool.
Time-Domain Heart Rate Variability Analysis with the SPINE-HRV Toolkit / Andreoli, A.; Gravina, R.; Giannantonio, R.; Pierleoni, P.; Fortino, G.. - (2010). (Intervento presentato al convegno PETRA 2010, 3rd International Conference on PErvasive Technologies Related to Assistive Environments tenutosi a Samos, Grecia nel June 23-25, 2010) [10.1145/1839294.1839362].
Time-Domain Heart Rate Variability Analysis with the SPINE-HRV Toolkit
Andreoli A.;Pierleoni P.
;
2010-01-01
Abstract
We present a tool-kit for the time domain Heart Rate Variability (HRV) analysis, namely SPINE-HRV (Signal Processing In Node Environment-HRV). The HRV is based on the analysis (time and frequency domain) of the R-peak to R-peak intervals (RR-interval). The tool-kit is composed of a wearable Heart Activity Monitoring System (HAMS) to collect the RR-interval (RRi), and a processing application developed using the SPINE framework. The HAMS used to acquire the RRi signal is self-developed; the hardware system consists of a chest belt communicating wireless with a receiver node. The RRi signal is processed using the SPINE framework through a time domain analysis of HRV. That analysis provides seven common parameters known in medicine literature to help cardiologists in the diagnosis related to several heart diseases. The results have been validated with a commonly used high accuracy HRV software tool.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.