Automatic vs hand-controlled walking of paraplegics.
A rule-based control and its application in functional electrical stimulation (FES) assisted walking of subjects with paraplegia are described in this paper. The design of rules for control comprises the following two steps: (1) determination of muscle activation patterns by using a fully customized spatial (3D) model of paraplegic walking, and (2) learning of rules, that is, correlation between the muscle activation patterns and kinematics of walking by means of an artificial neural network. The adopted FES system activated eight muscle groups with surface electrodes. The only joints allowing movement in the coronal plane were the hips, and externally controlled joints in sagittal plane were ankles, knees and hips. The simulation minimized the tracking error of the joint angles and the total activation of all eight muscles being stimulated. A radial-basis function artificial neural network was applied for learning of rules. Three automatically controlled modes (slow, near-normal, and near-ballistic) and hand-controlled walking were evaluated in six subjects with a complete spinal cord lesion (T8-T10). The performance of walking was assessed by the following: (1) energy consumption based on oxygen uptake, (2) physiological cost index, (3) maximum speed of walking, and (4) a questionnaire. The results showed that all modes of walking are achievable and that automatic control leads to more efficient and faster walking. The speed of walking achieved by automatic control was almost three times bigger compared with the speed of hand-controlled walking. The energy cost and rate decreased significantly when automatic control was applied; yet, they were still much bigger than the values measured in able-bodied subjects. The objective outcome measures suggest that the near-ballistic walking was the most effective, yet a questionnaire shows that most subjects preferred slow walking. The most likely reason for the preference of lower efficiency walking over the faster end energy efficient near-ballistic walking was that paraplegic patients had difficulties in synchronizing the voluntary movement of the trunk and arms to the artificially controlled movements of legs.
Popović
Dejan
D
Center for Sensory-Motor Interaction, Aalborg University, Fredrik Bajers Vej 7, D-3, 9220 Aalborg, Denmark. dbp@smi.auc.dk
Radulović
Milovan
M
Schwirtlich
Laszlo
L
Jauković
Novak
N
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D004599:Electric Stimulation Therapy / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005684:Gait; D006225:Hand / Q000503:physiopathology; D006801:Humans; D035002:Lower Extremity / Q000503:physiopathology; D008297:Male; D018482:Muscle, Skeletal / Q000503:physiopathology*; D016571:Neural Networks, Computer; D010264:Paraplegia / Q000503:physiopathology / Q000534:rehabilitation*; D014836:Volition; D016138:Walking