Automatic assessment method and system for motion function of upper limbs of stroke patient

Abstract

The invention provides an automatic assessment method and system for the motion function of the upper limbs of a stroke patient. According to the automatic assessment method and system for the motion function of the upper limbs of the stroke patient, a motion data set is constructed based on motion data; the motion data set is preprocessed to obtain a preprocessed data set; kinematics features are dynamically extracted from the preprocessed data set, and a feature set is constructed; the feature set is input into a trained assessment model so as to obtain all the exercise evaluation scores; and the total exercise evaluation score of the upper limbs of the to-be-evaluated stroke patient is obtained based on all the exercise evaluation scores. Thus, the obtained data are more objective, and a score result obtained based on the objective data is more accurate and objective; and therefore, the problem of limitation of a traditional upper limb motion function evaluation method in actual evaluation work can be solved.

Description

technical field [0001] The invention relates to the technical field of motion assessment, in particular to an automatic assessment method and system for upper limb motor function of stroke patients. Background technique [0002] Stroke (also known as stroke) is one of the leading causes of disability worldwide, and the prevalence of stroke is expected to continue to increase as the population ages worldwide. According to relevant statistics, up to 80% of stroke patients have varying degrees of upper limb disability in the acute to subacute stages after onset, which has a negative impact on the quality of life of them and their families. The recovery from stroke is a long process, and rehabilitation treatment will run through the whole process of the disease, which is mainly divided into three stages. Ultra-early (within 24 hours) / early rehabilitation (after 48 hours) for patients with acute stroke, they are usually treated in neurology departments or stroke centers, mainly ...

AI Technical Summary

Problems solved by technology

However, these clinical scales have two main limitations: 1) motor function assessment is time-consuming; 2) the scores of clinical scale tests are based on human subjective judgments and lack of objectivity

Therefore, sensor technology is applied to the assessment of motor function, but the traditional motion capture technology also has related limitations, mainly in: 1) It is necessary to strategically place physical markers (such as reflective balls) on the bony landmarks of the body In fact, this may interfere with the collection of patient motion and motion data; 2) It requires a special working environment to collect data, which cannot be met in many clinical rehabilitation and community rehabilitation environments; 3) The cost of the capture system and its settings is too high

Therefore, in the context of clinical rehabilitation and community rehabilitation, traditional upper limb motor function assessment methods and motion capture technology show many limitations

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