Comparison of Motion Analysis Systems in Tracking Upper Body Movement of Myoelectric Bypass Prosthesis Users

Abstract

Current literature lacks a comparative analysis of different motion capture systems for tracking upper limb (UL) movement as individuals perform standard tasks. To better understand the performance of various motion capture systems in quantifying UL movement in the prosthesis user population, this study compares joint angles derived from three systems that vary in cost and motion capture mechanisms: a marker-based system (Vicon), an inertial measurement unit system (Xsens), and a markerless system (Kinect). Ten healthy participants (5F/5M; 29.6 ± 7.1 years) were trained with a TouchBionic i-Limb Ultra myoelectric terminal device mounted on a bypass prosthetic device. Participants were simultaneously recorded with all systems as they performed standardized tasks. Root mean square error and bias values for degrees of freedom in the right elbow, shoulder, neck, and torso were calculated. The IMU system yielded more accurate kinematics for shoulder, neck, and torso angles while the markerless system performed better for the elbow angles. By evaluating the ability of each system to capture kinematic changes of simulated upper limb prosthesis users during a variety of standardized tasks, this study provides insight into the advantages and limitations of using different motion capture technologies for upper limb functional assessment.

Where to mount the IMU? Validation of joint angle kinematics and sensor selection for activities of daily living

“…Compared to previous work (Uhlenberg et al, 2022), and similar to the lower limbs analysis, a minor increase in median RMSE by 1.5 • was observed for upper limbs. In comparison, Wang et al (2022) reported median RMSE for their 5-IMU system ranging between 23.8−62.6 • , with overall median RMSE below 30 • across activities including grasping, lifting small/heavy objects, and reaching overhead. IMUs were mounted at one side of the upper body only and tended to overestimate shoulder rotation.…”

“…For upper limbs Goodwin et al (2021) investigated humeral elevation in individuals with spinal cord injury and showed that shoulder motion was highly consistent with MoCap. In a study by Wang et al (2022), joint angles obtained from five IMUs positioned on one side of the upper body were compared with a markerless MoCap system and a standard marker-based method. The findings indicated that the RMSE for joint angles was smaller at the shoulders compared to the elbows.…”

A multifaceted suite of metrics for comparative myoelectric prosthesis controller research

“…As such, our suite of control metrics is not solely reliant on motion capture data for metrics calculations. Alternative sources that capture grip aperture and wrist rotation data (such as from device motor positions), along with shoulder flexion/extension data (such as from markerless motion capture technology or IMUs [ 91 ]) can be used for these calculations. Furthermore, other methods of segmenting functional tasks into Reach, Grasp, Transport, and Release phases (such as segmenting markerless motion capture data or IMU-captured data) can be implemented in preparation for metrics calculations.…”

A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System

“…Three-dimensional motion capture systems or optoelectronic systems, such as Vicon (Oxford, UK), MotionAnalysis (Santa Rosa, CA, USA), OptiTrack (Corvallis, OR, USA), or Qualisys (Göteborg, Sweden) [9], offer precision and reliability, among other advantages. As a result, optoelectronic systems have become a gold standard and have been used as benchmark systems in the validation of other proposals, especially in fields related to human healthcare [10][11][12][13][14][15].…”