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001-es BibID:BIBFORM087640
035-os BibID:(cikkazonosító)1082 (Scopus)85079313653 (WOS)000517783300407
Első szerző:Rahman, Saifur
Cím:Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living / Saifur Rahman, Muhammad Irfan, Mohsin Raza, Khawaja Moyeezullah Ghori, Shumayla Yaqoob, Muhammad Awais
ISSN:1661-7827 1660-4601
Megjegyzések:Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this regard can provide a reliable and economical means of tracking such activities, and such sensors are readily available in smartphones and watches. This study is the first of its kind to develop a wearable sensor-based physical activity classification system using a special class of supervised machine learning approaches called boosting algorithms. The study presents the performance analysis of several boosting algorithms (extreme gradient boosting-XGB, light gradient boosting machine-LGBM, gradient boosting-GB, cat boosting-CB and AdaBoost) in a fair and unbiased performance way using uniform dataset, feature set, feature selection method, performance metric and cross-validation techniques. The study utilizes the Smartphone-based dataset of thirty individuals. The results showed that the proposed method could accurately classify the activities of daily living with very high performance (above 90%). These findings suggest the strength of the proposed system in classifying activity of daily living using only the smartphone sensor's data and can assist in reducing the physical inactivity patterns to promote a healthier lifestyle and wellbeing.
Tárgyszavak:Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:International Journal of Environmental Research and Public Health. - 17 : 3 (2020), p. 1-15. -
További szerzők:Irfan, Muhammad Raza, Mohsin Ghori, Khawaja Moyeezullah (1982-) (informatikus) Yaqoob, Shumayla Awais, Muhammad
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