The Performance of an Algorithm for Classifying Gym-Based Tasks across Individuals with Different Body Mass Index

Autor/inn/en	Gerrard-Longworth, Simon; Preece, Stephen J.; Clarke-Cornwell, Alexandra M.; Goulermas, Yannis
Titel	The Performance of an Algorithm for Classifying Gym-Based Tasks across Individuals with Different Body Mass Index
Quelle	In: Measurement in Physical Education and Exercise Science, 24 (2020) 4, S.282-290 (9 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1091-367X
DOI	10.1080/1091367X.2020.1815749
Schlagwörter	Classification; Body Weight; Body Height; Body Composition; Human Body; Program Effectiveness; Foreign Countries; Exercise; Individual Differences; Obesity; Adults; Physiology; United Kingdom (England) + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Körpergewicht; Körpergröße; Menschlicher Körper; Ausland; Übung; Individueller Unterschied; Adipositas; Physiologie
Abstract	Previous activity classification studies have typically been performed on normal weight individuals. Therefore, it is unclear whether a generic classification algorithm could be developed that would perform consistently across individuals who fall within different BMI categories. Acceleration data were collected from the hip and ankle joints of 50 individuals: 17 normal weight, 14 overweight, and 19 obese. Each participant performed a set of 10 dynamic tasks, which included activities of daily living and gym-based exercises. The performance of a generic classification algorithm, developed using linear discriminant analysis, was compared across the three separate BMI groups for each sensor. Higher classification accuracies (92-95%) were observed for the ankle sensor; however, both sensors demonstrated consistent performance across the three groups. This is the first study to demonstrate the effectiveness of a generic classification algorithm across individuals with different BMI and may be a first step toward automated activity profiling in weight-loss programs. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01