Assessment of Shoulder Range of Motion Using a Wearable Inertial Sensor Network

Yu Ching Lin, Yi Ju Tsai, Yu Liang Hsu, Ming Hsin Yen, Jeen Shing Wang

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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.

Original languageEnglish
Article number9405640
Pages (from-to)15330-15341
Number of pages12
JournalIEEE Sensors Journal
Issue number13
Publication statusPublished - 2021 Jul 1

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering


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