Quantitative Assessment of Upper Limb Movement in Post-Stroke Adults for Identification of Sensitive Measures in Reaching and Lifting Activities

Real-time, accurate, and open source upper-limb musculoskeletal analysis using a single RGBD camera - An exploratory hand-cycling study

Biomechanical biofeedback may enhance rehabilitation and provide clinicians with more objective task evaluation. These feedbacks often rely on expensive motion capture systems (∼$100000), which restricts their widespread use, leading to the development of computer vision-based methods. These methods are subject to large joint angle errors, considering the upper limb, and exclude the scapula and clavicle motion in the analysis. Our open-source approach offers a user-friendly solution for high-fidelity upper-limb kinematics using a single consumer-grade depth-sensing camera (∼$500) and includes semi-automatic skin marker labeling. Real-time biomechanical analysis, ranging from kinematics to muscle force estimation, was conducted on eight participants performing a hand-cycling motion to demonstrate the applicability of our approach on the upper limb. Markers were recorded by the depth-sensing camera and an optoelectronic camera system, considered as a reference. Muscle activity and external load were recorded using eight electromyography sensors and instrumented hand pedals, respectively. Bland-Altman analysis revealed significant agreements in the 3D markers' positions between the two motion capture methods, with errors averaging 3.3 ± 3.9 mm. The error propagation was low for the biomechanical analysis, with joint angle differences, for example, below 5° when comparing both systems. Biofeedback from the depth-sensing camera was provided at 68 Hz. Our study introduces a novel method for using a depth-sensing camera as a low-cost motion capture solution. Results from healthy participants suggest its potential for accurate kinematic reconstruction and comprehensive upper-limb biomechanical studies. Further investigation is needed to explore its clinical applications in pathological populations.

Kinematic analysis in post-stroke patients with moderate to severe upper limb paresis and non-disabled controls

BACKGROUND

Kinematic analysis has been recommended to quantify the upper limb motor function after stroke. However, previous studies have rarely reported the kinematic data of the post-stroke patients with moderate to severe upper limb paresis due to the poor accomplishment of the complex tasks.

METHODS

27 post-stroke individuals and 20 non-disabled people participated in the study. The trunk and upper limb movements during the Hand-to-mouth task were captured by the motion capture system and upper extremity kinematic analysis software automatically. The subgroup analysis within stroke group were conducted layering by the Fugl-Meyer Assessment for Upper Extremity scores (severe: 16-31; moderate: 32-50).

FINDINGS

The paretic upper limbs in the stroke group tended to use more trunk and shoulder compensatory strategies to offset the impact of spasticity and weakness compared with non-disabled controls. The less-affected limbs in the stroke group also showed abnormal kinematic data. There were significant differences between the kinematic metrics of severe and moderate subgroups.

INTERPRETATION

The Hand-to-mouth task is a good and feasible option for kinematic analysis of these patients. It is essential to layer the severity of the paresis and put more emphasis on trunk movements in the future kinematic studies.