Journal
IEEE SENSORS JOURNAL
Volume 23, Issue 16, Pages 18579-18586Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2023.3285397
Keywords
Double-clad fiber Bragg grating (FBG) sensor; gesture recognition; movement state monitoring
Ask authors/readers for more resources
Musculoskeletal disorders (MSDs) are common and lack effective treatments. Real-time monitoring of body posture and movement state using wearable high-sensitive double-clad fiber Bragg grating (FBG) sensors may be an effective strategy for the prevention and treatment of MSD. The results demonstrate the high accuracy and improved sensitivity of the double-clad FBG sensors, making them a reliable assessment tool for clinical trials of MSD.
Musculoskeletal disorders (MSDs) 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/& DEG; in elbow joint static tests and 7.5 pm/& DEG; 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available