Quantitative Upper Limb Impairment Assessment for Stroke Rehabilitation: A Review

With the number of people surviving a stroke soaring, automated upper limb impairment assessment has been extensively investigated in the past decades since it lays the foundation for personalized precision rehabilitation. The recent advancement of sensor systems, such as high-precision and real-time data transmission, have made it possible to quantify the kinematic and physiological parameters of stroke patients. In this article, we review the development of sensor-based upper limb quantitative impairment assessment, concentrating on the capable of comprehensively and accurately detecting motion parameters and measuring physiological indicators to achieve the objective and rapid quantification of the stroke severity. The article discusses various features used by different sensors, detectable actions, their utilization techniques, and effects of sensor placement on system accuracy and stability. In addition, both the advantages and disadvantages of the model-based and model-free methods are also reviewed. Furthermore, challenges encompassing comprehensive assessment of medical scales, neurological deficits assessment, random movement detection, effects of the sensor placement, and effects of the number of sensors are also discussed.