Design And Development Of Cycling Rehabolitation Training System Based On Physiological Signal Extraction

With the aggravation of China's aging population and the increasing number of dysfunctions caused by stroke and brain injury caused by traffic accidents,people's demand for rehabilitation is increasing.Medical researches show that the nerve injury caused by stroke can effectively help patients recover limb dysfunction through scientific exercise-auxiliary training.Rehabilitation machine is one of the main treatment methods at present.However,the current rehabilitation machines commonly used in the market are weak in monitoring physiological capabilities,low patient participation,and poor self-regulating functions,which cannot meet the needs of patients for rehabilitation machines.Therefore,the development of a rehabilitation machine with physiological signal monitoring function and improved rehabilitation effect is of great social significance and market value.By focusing on the rehabilitation of lower limbs and in view of recent progress of lower limb rehabilitation machines and their applications,this dissertation designs and develops a cycling rehabilitation training system based on physiological signal extraction.The main contents of this dissertation are listed as follows:1.To overcome the shortcoming that conventional rehabilitation machines cannot monitor physiological status and exercise intensity during the rehabilitation process,this dissertation designs and implements the physiological signal and motion data collecting function.The heart rate is extracted by remote photoplethysmography.The electromyograms(EMG)are collected,processed and analysed.Some of the obtained eigenvalues are viewed as indicators for the evaluation of rehabilitation effects.Finally,the acquisition and display of data including the heart rate,surface EMGs,speed,power and training time are realized.2.To strengthen the interest during rehabilitation and improve the patient's participation and initiative,the real-scene riding rehabilitation training scheme is designed.The active and passive training modes are designed according to the degree of lower limb damage and rehabilitation stages,which employ ANT+ protocol for upper and lower machines communication and real-scene videos to mimic the actual riding environment to improve the patient's initiative and enthusiasm.The server and database are designed to store physiological signals and exercise data,providing the basis for doctors and rehabilitation workers to make subsequent rehabilitation plans.3.To address the problem that traditional rehabilitation machines are lack of self-regulating function and unable to provide indicators for rehabilitation evaluation,this dissertation designes the heart rate-based negative feedback control and extracts some indicators that contribute to the rehabilitation evaluation.The speed and inclination of the lower limb rehabilitation machine can be adjusted in time according to the fluctuation of the subject's heart rate.The average electromyography(AEMG),average power frequency(MPF),and median frequency(MF)obtained from the myoelectric signals can serve as the basis of phasic rehabilitation treatment and rehabilitation effect evaluation.The overall test of the system demonstrates that the cycling rehabilitation training system based on physiological signal acquisition can collect heart rate and EMG signals and improve the patient's enthusiasm and initiative by real-scene video riding training.The extracted features based on EMG signals are of reference significance for the evaluation of rehabilitation effect.The system has great theoretical and practical application value.