This invention relates to the field of
stroke hand function rehabilitation technology, and more particularly to a smart training
health data assessment
system for
stroke hand function rehabilitation. The
system includes: a
data acquisition and mapping module, a spatial filtering module, a spatiotemporal separation module, a template alignment module, a training adjustment module, and a
safety monitoring module. The
data acquisition and mapping module acquires multi-channel electromyographic signals of the hand and
forearm target
muscle groups of
stroke patients and establishes a mapping between the acquisition area and the target
muscle groups. The spatial filtering module performs spatial filtering on the acquired signals. The spatiotemporal separation module extracts spatiotemporal coordination patterns of the hand and adaptively adjusts the number of coordination patterns. The template alignment module spatially aligns the coordination patterns and calculates scores. The training adjustment module adjusts training parameters, and the
safety monitoring module monitors
safety indicators. In this invention, the
system achieves a complete
closed loop of
health data assessment and training adjustment, improving the problems of disconnect between assessment and
training needs and insufficient adaptability caused by traditional single
signal acquisition or offline assessment.