This study investigated the use of surface electromyography (EMG) combined with pattern recognition (PR) to identify user locomotion modes. Due to the nonstationary characteristics of leg EMG signals during locomotion, a new phase-dependent EMG PR strategy was proposed for classifying the user's locomotion modes. The variables of the system were studied for accurate classification and timely system response. The developed PR system was tested on EMG data collected from eight able-bodied subjects and two subjects with long transfemoral (TF) amputations while they were walking on different terrains or paths. The results showed reliable classification for the seven tested modes. For eight able-bodied subjects, the average classification errors in the four defined phases using ten electrodes located over the muscles above the knee (simulating EMG from the residual limb of a TF amputee) were 12.4% ± 5.0%, 6.0% ± 4.7%, 7.5% ± 5.1%, and 5.2% ± 3.7%, respectively. Comparable results were also observed in our pilot study on the subjects with TF amputations. The outcome of this investigation could promote the future design of neural-controlled artificial legs.
A novel method for the control of a myoelectric upper limb prosthesis was achieved in a patient with bilateral amputations at the shoulder disarticulation level. Four independently controlled nerve-muscle units were created by surgically anastomosing residual brachial plexus nerves to dissected and divided aspects of the pectoralis major and minor muscles. The musculocutaneous nerve was anastomosed to the upper pectoralis major; the median nerve was transferred to the middle pectoralis major region; the radial nerve was anastomosed to the lower pectoralis major region; and the ulnar nerve was transferred to the pectoralis minor muscle which was moved out to the lateral chest wall. After five months, three nerve-muscle units were successful (the musculocutaneous, median and radial nerves) in that a contraction could be seen, felt and a surface electromyogram (EMG) could be recorded. Sensory reinnervation also occurred on the chest in an area where the subcutaneous fat was removed. The patient was fitted with a new myoelectric prosthesis using the targeted muscle reinnervation. The patient could simultaneously control two degrees-of-freedom with the experimental prosthesis, the elbow and either the terminal device or wrist. Objective testing showed a doubling of blocks moved with a box and blocks test and a 26% increase in speed with a clothes pin moving test. Subjectively the patient clearly preferred the new prosthesis. He reported that it was easier and faster to use, and felt more natural.
The clinical application of robotic technology to powered prosthetic knees and ankles is limited by the lack of a robust control strategy. We found that the use of electromyographic (EMG) signals from natively innervated and surgically reinnervated residual thigh muscles in a patient who had undergone knee amputation improved control of a robotic leg prosthesis. EMG signals were decoded with a pattern-recognition algorithm and combined with data from sensors on the prosthesis to interpret the patient's intended movements. This provided robust and intuitive control of ambulation--with seamless transitions between walking on level ground, stairs, and ramps--and of the ability to reposition the leg while the patient was seated.
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