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Wearable Fabric System for Sarcopenia Detection

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Specialty Biotechnology
Date 2024 Dec 27
PMID 39727887
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Abstract

Sarcopenia has been a serious concern in the context of an increasingly aging global population. Existing detection methods for sarcopenia are severely constrained by cumbersome devices, the necessity for specialized personnel, and controlled experimental environments. In this study, we developed an innovative wearable fabric system based on conductive fabric and flexible sensor array. This fabric system demonstrates remarkable pressure-sensing capabilities, with a high sensitivity of 18.8 kPa and extraordinary stability. It also exhibits excellent flexibility for wearable applications. By interacting with different parts of the human body, it facilitates the monitoring of various physiological activities, such as pulse dynamics, finger movements, speaking, and ambulation. Moreover, this fabric system can be seamlessly integrated into sole to track critical indicators of sarcopenia patients, such as walking speed and gait. Clinical evaluations have shown that this fabric system can effectively detect variations in indicators relevant to sarcopenia patients, proving that it offers a straightforward and promising approach for the diagnosis and assessment of sarcopenia.

References
1.
Turimov Mustapoevich D, Kim W . Machine Learning Applications in Sarcopenia Detection and Management: A Comprehensive Survey. Healthcare (Basel). 2023; 11(18). PMC: 10531485. DOI: 10.3390/healthcare11182483. View

2.
Tagliafico A, Bignotti B, Torri L, Rossi F . Sarcopenia: how to measure, when and why. Radiol Med. 2022; 127(3):228-237. PMC: 8960583. DOI: 10.1007/s11547-022-01450-3. View

3.
Han S, Xiao Q, Liang Y, Chen Y, Yan F, Chen H . Using Flexible-Printed Piezoelectric Sensor Arrays to Measure Plantar Pressure during Walking for Sarcopenia Screening. Sensors (Basel). 2024; 24(16). PMC: 11360066. DOI: 10.3390/s24165189. View

4.
Kim J, Bae M, Lee K, Kim J, Hong S . Explainable Artificial Intelligence and Wearable Sensor-Based Gait Analysis to Identify Patients with Osteopenia and Sarcopenia in Daily Life. Biosensors (Basel). 2022; 12(3). PMC: 8946270. DOI: 10.3390/bios12030167. View

5.
Cruz-Jentoft A, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T . Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2018; 48(1):16-31. PMC: 6322506. DOI: 10.1093/ageing/afy169. View