Pregled bibliografske jedinice broj: 633791
WBAN for Physical Activity Monitoring in Health Care and Wellness
WBAN for Physical Activity Monitoring in Health Care and Wellness // IFMBE Proceedings Volume 39, 2013 / Mian Long (ur.).
Heidelberg: Springer, 2013. str. 2228-2231 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 633791 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
WBAN for Physical Activity Monitoring in Health Care and Wellness
Autori
Celić, Luka ; Varga, Matija ; Pozaić, Tomislav ; Žulj, Sara ; Džaja, Dominik ; Magjarević, Ratko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IFMBE Proceedings Volume 39, 2013
/ Mian Long - Heidelberg : Springer, 2013, 2228-2231
ISBN
978-3-642-29305-4
Skup
World Congress on Medical Physics and Biomedical Engineering
Mjesto i datum
Peking, Kina, 26.05.2012. - 31.05.2012
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
WBAN
Sažetak
Physical activity is an important factor of an individual’s health, and often a part of rehabilitation for patients suffering from post-trauma or some chronic diseases. The objective of this paper is to present the use of Wireless Body Area Network (WBAN) for measuring mobility and physical activity during assisted exercising as well as the algorithms for quantification of measurement results. Wireless sensor network is composed of sensor nods located on examinees’ body. With the help of networked sensors, it is possible to detect other physiological parameters of examinees at the same time, such as heart rate, breathing rate, temperature and body posture. Monitoring of physical activity has been realized with a three-axis accelerometer, while the data acquired from sensor node is sent to the central wearable node. Algorithms for the classification of mobility (different type of physical activity) during standard daily activities and for differentiation of exercises during workout has been developed and validated on a number of volunteers. In this paper we report on the second, used for assisted exercising. The algorithm is based on the first-neighbour method in n-dimensional space of signal features. Algorithm shows good features for physically different exercises. Our experience also indicates that the monitoring of physical activity and vital parameters at the same time is adequate for application in the rehabilitation of diabetic patients.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Dominik Džaja
(autor)
Matija Varga
(autor)
Ratko Magjarević
(autor)
Luka Celić
(autor)
Sara Žulj
(autor)