An open low-cost EMG acquisition system for analysis and robot control

INTRODUCTION AND AIM Surface electromyography SEMG is increasingly used in combination with assistive and rehabilitation devices for control, biofeedback, customizing the intervention and monitoring the results in neurological patients [1,2]. Accurate SEMG signal acquisition requires amplifiers, electrodes, filters and graphic software, often leading to relatively expensive solutions. Because of the costs, using SEMG for analysis and control of rehabilitation devices is still limited in the academic and laboratory ambient. In this study, a low-cost easily interfaceable EMG signal acquisition system, based on an open software and hardware architecture, is proposed for data acquisition and control of rehabilitation devices. MATERIALS AND METHODS The proposed SEMG signal acquisition system is compared with the professional BTS FREEEMG system. Two surface electrodes were placed on the biceps of a healthy subject at the distance of about 1cm; the reference electrode was placed on the wrist. Data were acquired without modifying the position of the electrodes for both systems. The subject performed 5 maximal voluntary elbow flexion contractions and SEMG was acquired in sequence with the two systems. RESULTS AND DISCUSSION In Fig. 1 signals acquired by both systems are depicted. As it can be observed the result of the low-cost system is comparable with the BTS system and it is acceptable to use in the control process of rehabilitation robots. While the cost of producing the designed system is 1% of the price of the BTS FEEEMG system. CONCLUSION In this study, a 6 channels low-cost EMG acquisition system was realized. The acquired results by the designed system represented a good signal quality and reliability of the system, to use in clinical applications especially in the control process of rehabilitation robots. Moreover, the totall cost to produce the system is much less than the price of the other commercial systems. REFERENCES [1] Donovan L et al. Lower-extremity electromyography measures during walking with ankle destabilization devices. J Sport Rehabil. 23(2); 134-44, 2014. [2] The effects of post-stroke upper-limb training with and electromyography (EMG)-driven hand robot. Hu et al J Electrpmyogr Kinesiol. 23(5): 1065-1074, 2013