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Knee joint angle and angular velocity were calculated in real time during standing up and sitting down. Two small modules comprising rate gyroscopes and accelerometers were attached to the thigh and shank of two able-bodied volunteers and one T5 ASIA(A) paraplegic assisted by functional electrical stimulation (FES). The offset and drift of the rate(More)
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)
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)
A practical system for Functional Electrical Stimulation (FES) assisted standing up in paraplegia should involve only a minimum of manual set up and tuning. An improved tuning method, using a genetic algorithm (GA) is proposed and demonstrated using computer simulation. Specifically, the GA adjusts the parameters of fuzzy logic (FL) and gain-scheduling(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)
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)
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)
We modified a commercial indoor rowing machine (Concept 2 Inc., Morrisville, NJ, USA) for a functional electrical stimulation (FES) assisted indoor rowing exercise in which the rowers must repeatedly press the two switches on the handle that stimulate their paralyzed leg muscles. The objective of this study was to automate the delivery of electrical(More)