Contribution to Characterizing Time-Dependent Handgrip Strength Profiles

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Cardoso, A (Author) Other; Diana Urbano (Author) FEUP; Maria Teresa Restivo (Author) FEUP

Conference proceedings International

Title: SMART TECHNOLOGIES FOR A SUSTAINABLE FUTURE, VOL 2, STE 2024

Pages: 109-117

21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

Helsinki, FINLAND, MAR 06-08, 2024

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Other information

Authenticus ID: P-010-ZV0

DOI: 10.1007/978-3-031-61905-2_12

Abstract (EN): Themaximum value of HandGrip Strength (usually named by HGS) is an important biomarker that indicates several physical conditions such as diabetes, malnutrition, sarcopenia, frailty and general functional physical capacity. It is also relevant for evaluation purposes in the context of rehabilitation, in patients suffering from hand musculoskeletal or other pathologies. The HGS dynamometry is non-invasive, portable, easy to perform, fast and reliable, making it suitable for routine assessment in different health and sportsrelated areas. Besides the HGS value (maximum value), other parameters such as rate of force development and sustainability of force, obtained bymeasuring time-dependent HGS (HGS(t)), have also been used in different assessment contexts utilizing modern dynamometers such as the BodyGrip (nowon its commercialized version, Gripwise). A universal definition of the parameters characterizing HGS(t) curves has been proposed, and a study based on an artificial neural network model used those parameters to predict the frailty of elderlywomen. In thiswork, a newmethodology was used to investigate the characteristics of HGS(t). The main idea is to identify and explore a first or second-order continuous-time transfer function, which can be used to estimate the force profile, using the Mean Squared Error and the overall percentual fit as measures of the approximation quality. The authors consider the results to be promising for future exploitation of the model to investigate and extract the characteristics of the time-dependent HGS (HGS(t)).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9