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Two machine learning techniques were evaluated for automatic design of a rule-based control of functional electrical stimulation (FES) for locomotion of spinal cord injured humans. The task was to learn the invariant characteristics of the relationship between sensory information and the FES-control signal by using off-line supervised training. Sensory(More)
Localized electrical nerve blocking was investigated in computer simulation and in vivo trials for sinusoidal frequencies between 5 and 20 kHz. Computer simulations indicated that a localized transmission block of the axons could occur in each of the axon models. An approximation of nerve stimulation was derived from individual axon simulations conducted(More)
One symbolic (rule-based inductive learning) and one connectionist (neural network) machine learning technique were used to reconstruct muscle activation patterns from kinematic data measured during normal human walking at several speeds. The activation patterns (or desired outputs) consisted of surface electromyographic (EMG) signals from the(More)
Tilt sensors, or inclinometers have been investigated for the control of Functional Electrical Stimulation (FES) to improve the gait of persons who had a stroke or incomplete spinal cord injury (SCI). Different types of tilt sensors were studied for their characteristics and their performance in measuring the angular displacement of leg segments during(More)
Rule based detectors were used with a single cluster of accelerometers attached to the shank for the real time detection of the main phases of normal gait during walking. The gait phase detectors were synthesized from two rule induction algorithms, Rough Sets (RS) and Adaptive Logic Networks (ALNs), and compared with to a previously reported stance/swing(More)
OBJECTIVES To assess changes in peak functional aerobic power after a 36-session, progressive functional electric stimulation (FES) rowing hybrid training program for persons with spinal cord injury (SCI) and to examine the safety and acceptability of the ROWSTIM II device as well as the integrity of technical modifications to it. DESIGN Repeated-measures(More)
Using computer simulation, the theoretical feasibility of functional electrical stimulation (FES) assisted standing up is demonstrated using a closed-loop self-adaptive fuzzy logic controller based on reinforcement machine learning (FLC-RL). The control goal was to minimize upper limb forces and the terminal velocity of the knee joint. The reinforcement(More)
Objectives.  To explore the potential of functional electrical stimulation (FES)-assisted indoor rowing to enable spinal cord individuals to participate in indoor rowing competitions and to achieve high exercise intensities and volumes. Materials and Methods.  Six spinal cord injured subjects used a newly developed four-channel, manually controlled,(More)
Musculoskeletal simulation software and model repositories have broadened the user base able to perform musculoskeletal analysis and have facilitated in the sharing of models. As the recognition of musculoskeletal modeling continues to grow as an engineering discipline, the consistency in results derived from different models and software is becoming more(More)
A group of patients who are good candidates for the application of Functional Electrical Stimulation (FES) to restore reciprocal walking is described. They have incomplete lesions of the spinal cord. Because of the degree of preserved voluntary control, proprioception and sensation some of these patients can achieve crutch assisted walking by means of(More)