Human Activity Recognition (HAR) deals with the automatic recognition of physical activities and plays a major role in the health and sports sector.
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Three HAR algorithms classify daily activities using a hierarchical architecture or decision level fusion. The proposed approaches achieved accuracy values.
This survey focuses on critical role of machine learning in developing HAR applications based on inertial sensors in conjunction with physiological and ...
Nov 12, 2020 · This survey focuses on critical role of machine learning in developing HAR applications based on inertial sensors in conjunction with ...
Nov 5, 2024 · This study aims to evaluate the accuracy of sport exercise recognition while minimizing the number of sensors required.
The primary objective of this study is to use innovative technology, specifically wearable inertial sensors combined with artificial intelligence techniques,
May 23, 2018 · This paper presents a wearable inertial sensor network and its associated activity recognition algorithm for accurately recognizing human daily and sport ...
Daily and sports activities are classified using five sensor units worn by eight subjects on the chest, the arms, and the legs. Each sensor unit comprises a ...
The approach could achieve recognition rates for the 10 common domestic activities of 98.23% and 11 sport activities of 99.55% by the 10-fold cross-validation ...
Feb 4, 2021 · HAR's goal is to recognize human activities of daily life (for example, walking, standing, sleeping, running, repose, watching TV, cooking, etc.) ...
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