Abstract:  The restoration of finger motor functions is considered difficult during rehabilitation due to the complexity of the underlying muscles. The Fugl-Meyer Assessment (FMA) method is used by doctors to manually assess the level of finger movement impairment. However, there is a risk of evaluation errors due to inherent subjectivity. Therefore, a new, more accurate method must be developed to predict the level of impairment. This study aimed to evaluate the impairment level of finger movement based on the FMA. EMG signals were recorded from four patients while performing seven movements, and feature extraction was performed. SVM and Random Forest were used to classify the level of impairment for each movement. The SVM model obtained good results in the fourth movement, with an accuracy of 91.7% and an F1 score of 0.78.

Keywords: impairment level; finger movement; post-stroke patients; recognition.