Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/33508
Title: Can sensors be used to measure the Arm Curl Test results? a systematic review
Authors: Matos, Tomás
Vornicoglo, Daniel
Coelho, Paulo Jorge
Zdravevski, Eftim 
Albuquerque, Carlos
Pires, Ivan Miguel
Issue Date: 31-Jan-2024
Publisher: Springer Science and Business Media LLC
Journal: Discover Applied Sciences
Abstract: <jats:title>Abstract</jats:title><jats:p>There is growing interest in the automated measurement of physical fitness tests, such as the Arm Curl Test, to enable more objective and accurate assessments. This review aimed to systematically analyze the types of sensors and technological methods used for automated Arm Curl Test measurement and their benefits for different populations. The search consisted of the search related to the possibilities to measure the Arm Curl Test results with sensors in scientific databases, including PubMed Central, IEEE Explore, Elsevier, Springer, MDPI, ACM, and PMC, published from January 2010 to October 2022. The analysis included 30 studies from 15 nations with diverse populations analyzed. According to data extraction, the most prevalent sensors were chronometers, accelerometers, stadiometers, and dynamometers. In the investigations, statistical analysis predominated. The study shows how automated sensor technologies can objectively measure the Arm Curl Test. The detected sensors combined with statistical analysis techniques can enhance assessments. Applications for the Arm Curl Test may be improved even more with more research on cutting-edge sensors and algorithms. This evaluation offers insightful information about utilizing sensor-based automation to enhance Arm Curl Testing.</jats:p>
URI: http://hdl.handle.net/20.500.12188/33508
DOI: 10.1007/s42452-024-05643-5
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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