Abstract
Musculoskeletal disorders (MSD) are prevalent in society and currently lack effective treatments. The incidence of MSD appears to be increasing as the worldwide population ages and sedentary lifestyles. Real-time monitoring of the body posture and movement state may be an effective strategy for the prevention and treatment of MSD. We proposed a real-time monitoring system based on a wearable high-sensitive double-clad fiber Bragg grating (FBG) sensors and an integrated demodulation device to recognize the body posture and movement state. The results demonstrate that the double-clad FBG sensors exhibit a high measurement sensitivity of approximately 36 pm/° in elbow joint static tests and 7.5 pm/° in knee joint static tests, which is almost 1.4 times higher than that of a single-mode FBG. Furthermore, a dataset of six gestures was created based on time and wavelength information obtained from six double-clad FBG sensors monitoring subtle deformations of muscles of the arm. The accuracy of recognizing simple and complex gestures was close to 100% and about 88%, respectively. The static and dynamic measurements demonstrate that the double-clad sensors have high accuracy, improved sensitivity, excellent flexibility and good repeatability, and this work is expected to a reliable assessment tool for clinical trials of MSD.
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