Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body [1]. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.
Pattern recognition techniques and classification sets supporting behavioural tagging when using a limited number of body sensors / Scherz, Wilhelm Daniel; Ortega, Juan Antonio; Seepold, Ralf; Conti, Massimo. - ELETTRONICO. - 65:(2017), pp. 924-927. [10.1007/978-981-10-5122-7_231]
Pattern recognition techniques and classification sets supporting behavioural tagging when using a limited number of body sensors
CONTI, MASSIMO
2017-01-01
Abstract
Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body [1]. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
