We conclude that smartphones are well-suited for HAR research in the health sciences. Consequently, we identified 108 articles and described the various approaches used for data acquisition, data preprocessing, feature extraction, and activity classification, identifying the most common practices, and their alternatives. We extracted information on smartphone body location, sensors, and physical activity types studied and the data transformation techniques and classification schemes used for activity recognition. For this purpose, we systematically searched Scopus, PubMed, and Web of Science for peer-reviewed articles published up to December 2020 on the use of smartphones for HAR. In this review, we summarized the existing approaches to smartphone-based HAR. Researchers have proposed various human activity recognition (HAR) systems aimed at translating measurements from smartphones into various types of physical activity. Smartphones are now nearly ubiquitous their numerous built-in sensors enable continuous measurement of activities of daily living, making them especially well-suited for health research.
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