TY - JOUR
T1 - Assessment of Shoulder Range of Motion Using a Wearable Inertial Sensor Network
AU - Lin, Yu Ching
AU - Tsai, Yi Ju
AU - Hsu, Yu Liang
AU - Yen, Ming Hsin
AU - Wang, Jeen Shing
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - Diagnosis and progress monitoring of frozen shoulder rely on correct measurement of active and passive range of motion (ROM) of shoulder. This paper studied the feasibility of a wearable inertial sensor network (WISN) and its associated shoulder ROM estimation algorithm for shoulder ROM assessment. The WISN composed of three inertial modules were placed on the trunk, upper arm, and forearm of human for assessment of shoulder ROM in real time. Each inertial module consists of an ARM-based 32-bit microcontroller, a triaxial accelerometer, a triaxial gyroscope, a triaxial magnetometer, and a controller area network (CAN) transceiver. The measured accelerations, angular velocities, and magnetic signals generated by the human shoulder movements are transmitted to a personal computer via a Bluetooth wireless transmission module. The proposed shoulder ROM estimation algorithm includes the procedures of data collection, signal preprocessing, quaternion-based orientation estimation, and shoulder joint compensation. In order to evaluate shoulder ROM accurately, accelerations, angular velocities, and magnetic signals are integrated into a quaternion-based complementary nonlinear filter for minimizing the cumulative errors caused by the drift of the inertial sensors. Experimental results demonstrate that the WISN with the designed shoulder ROM estimation algorithm, compared to an optical motion analysis system (Vicon), have the average root mean square (RMS) angle errors ranging from 2.53° to 3.56°. In addition, the intra-tester reliability for each shoulder ROM measurement is excellent. The proposed WISN is a valid and reliable tool and can be used anywhere without any external reference device for convenient evaluation of shoulder ROM.
AB - Diagnosis and progress monitoring of frozen shoulder rely on correct measurement of active and passive range of motion (ROM) of shoulder. This paper studied the feasibility of a wearable inertial sensor network (WISN) and its associated shoulder ROM estimation algorithm for shoulder ROM assessment. The WISN composed of three inertial modules were placed on the trunk, upper arm, and forearm of human for assessment of shoulder ROM in real time. Each inertial module consists of an ARM-based 32-bit microcontroller, a triaxial accelerometer, a triaxial gyroscope, a triaxial magnetometer, and a controller area network (CAN) transceiver. The measured accelerations, angular velocities, and magnetic signals generated by the human shoulder movements are transmitted to a personal computer via a Bluetooth wireless transmission module. The proposed shoulder ROM estimation algorithm includes the procedures of data collection, signal preprocessing, quaternion-based orientation estimation, and shoulder joint compensation. In order to evaluate shoulder ROM accurately, accelerations, angular velocities, and magnetic signals are integrated into a quaternion-based complementary nonlinear filter for minimizing the cumulative errors caused by the drift of the inertial sensors. Experimental results demonstrate that the WISN with the designed shoulder ROM estimation algorithm, compared to an optical motion analysis system (Vicon), have the average root mean square (RMS) angle errors ranging from 2.53° to 3.56°. In addition, the intra-tester reliability for each shoulder ROM measurement is excellent. The proposed WISN is a valid and reliable tool and can be used anywhere without any external reference device for convenient evaluation of shoulder ROM.
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U2 - 10.1109/JSEN.2021.3073569
DO - 10.1109/JSEN.2021.3073569
M3 - Article
AN - SCOPUS:85104600419
SN - 1530-437X
VL - 21
SP - 15330
EP - 15341
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 13
M1 - 9405640
ER -