HSMM-based Rehabilitation Assessment Method Of Upper Limb Motor Function

How to evaluate the rehabilitation level of the patient’s motor function is very important for the therapist to formulate a rehabilitation plan.Most of the existing clinical methods are based on different types of scales,which are obviously restricted by the therapist’s subjective clinical experience,and can only receive rehabilitation assessment before and after training each time.It is difficult to reflect the patient’s rehabilitation progress in real time,which has certain limitations.In recent years,with the development of MEMS,wearable and artificial intelligence technologies,sports rehabilitation assessment methods based on the integration of the above technologies have received extensive attention.Aiming at the above research background,this paper develops the HSMM-based upper limb motor function rehabilitation evaluation system by fusing the patient’s motion posture and surface EMG signal during the rehabilitation training process.The specific work is as follows:I.Firstly,the application of wearable sensors and machine learning algorithms in the field of rehabilitation evaluation is explained and analyzed.Mainly introduces the research status of upper extremity rehabilitation evaluation systems at home and abroad,analyzes the shortcomings of the current upper extremity evaluation systems,and proposes the idea of an upper extremity rehabilitation evaluation model based on the fusion of artificial intelligence algorithms and wearable technology,for the follow-up study of upper extremity rehabilitation of stroke patients The evaluation provides a theoretical basis.II.Secondly,design the upper limb motor function rehabilitation evaluation plan and collect and process the upper limb motor function evaluation data.Based on the analysis of the traditional rehabilitation evaluation theory,the system design scheme is given,and the motion posture and surface EMG data for the rehabilitation evaluation of upper limb motor function are collected and processed,and the motion posture and muscles used for the establishment of the evaluation model are obtained.Electric characteristic data set.III.Thirdly,based on HSMM,the upper limb exercise rehabilitation evaluation model is designed.Taking the healthy side of stroke patients as the standard,a HSMM-based upper extremity motor rehabilitation evaluation model was designed to evaluate the motor function of the affected side of the patient’s upper extremity;in addition,a rehabilitation evaluation software platform was built to provide therapists with a more efficient real-time grasp of the recovery status of stroke patients The accurate way.IV.Finally,select subjects,analyze and verify the effectiveness of the HSMM-based upper limb exercise rehabilitation evaluation model.Take the "good","fair" and "poor" patient’s motion posture and EMG data features as input respectively,and analyze and compare the upper limb motion rehabilitation evaluation models based on HSMM,SVM and DTW from the aspect of stability;here Based on the further analysis of the reliability and validity of the HSMM rehabilitation evaluation model based on motion posture,electromyography and the fusion of the two,the validity of the upper limb rehabilitation evaluation model based on HSMM is verified.