[Research progress on intelligent assessment system for upper limb function of stroke patients]

Area of Science:

• Rehabilitation Engineering
• Medical Technology
• Biomedical Signal Processing

Background:

• Clinical assessment of stroke patients' upper limb function relies on scale methods.
• Traditional methods are time-consuming, inconsistent, and require significant physician involvement.

Purpose of the Study:

• To review intelligent upper limb function assessment systems for stroke patients.
• To analyze sensor and machine learning technologies in these systems.

Main Methods:

• Summarized traditional clinical upper limb functional assessment methods.
• Reviewed recent research on intelligent assessment systems.
• Focused on data acquisition and processing technologies.

Main Results:

• Identified limitations of scale-based assessments.
• Detailed the technologies used in intelligent assessment systems.
• Discussed advantages and disadvantages of current approaches.

Conclusions:

• Intelligent systems present a promising solution to the limitations of traditional assessment methods.
• Highlighted current challenges and future research directions in intelligent upper limb function assessment.