Authors:
Sara Casaccia
;
Filippo Pietroni
;
Andrea Calvaresi
;
Gian Marco Revel
and
Lorenzo Scalise
Affiliation:
Università Politecnica delle Marche, Italy
Keyword(s):
Physiological Parameters, Heart Rate, Breathing Rate, Wearable Sensor, Signal Processing.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Physiological Computing Systems
;
Wearable Sensors and Systems
Abstract:
Nowadays, the monitoring of users’ health status is possible by means of smart sensing devices at low-cost and with high measuring capabilities. Wearable devices are able to acquire multiple physiological and physical waveforms and are equipped with on-board algorithms to process these signals and extract the required quantities. However, the performance of such processing techniques should be evaluated and compared to different approaches, e.g. processing of the raw waveforms acquired. In this paper, the authors have performed a metrological characterization of a commercial wearable monitoring device for the continuous acquisition of physiological quantities (e.g. Heart Rate - HR and Breathing Rate - BR) and raw waveforms (e.g. Electrocardiogram - ECG). The aim of this work is to compare the performance of the on-board processing algorithms for the calculation of HR and BR with a novel approach applied to the raw signals. Results show that the HR values provided by the device are ac
curate enough (±2.1 and ±2.8 bpm in static and dynamic tests), without the need of additional processing. On the contrary, the implementation of the dedicated processing technique for breathing waveform allows to compute accurate BR values (±2.1 bpm with respect to standard equipment).
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