Human walking is a complicated interaction among the musculoskeletal system, nervoussystem and the environment. An injury affecting the neurological system, such as a spinalcord injury (SCI) can cause sensor and motor deficits, and can result in a partial or completeloss of their ambulatory functions. Functional electrical stimulation (FES), a technique togenerate artificial muscle contractions with the application of electrical current, has beenshown to improve the ambulatory ability of patients with an SCI. FES walking systems havebeen used as a neural prosthesis to assist patients walking, but further work is needed toestablish a system with reduced engineering complexity which more closely resembles thepattern of natural walking.The aim of this thesis was to develop a new FES gait assistance system with a simple andefficient FES control based on insights from robotic walking models, which can be used inpatients with neuromuscular dysfunction, for example in SCI.The understanding of human walking is fundamental to develop suitable control strategies.Limit cycle walkers are capable of walking with reduced mechanical complexity and simplecontrol. Walking robots based on this principle allow bio-inspired mechanisms to be analysedand validated in a real environment. The Runbot is a bipedal walker which has beendeveloped based on models of reflexes in the human central nervous system, without theneed for a precise trajectory algorithm. Instead, the timing of the control pattern is basedon ground contact information. Taking the inspiration of bio-inspired robotic control, twoprimary objectives were addressed. Firstly, the development of a new reflexive controllerwith the addition of ankle control. Secondly, the development of a new FES walking systemwith an FES control model derived from the principles of the robotic control system.The control model of the original Runbot utilized a model of neuronal firing processes basedon the complexity of the central neural system. As a causal relationship between foot contactinformation and muscle activity during human walking has been established, the controlmodel was simplified using filter functions that transfer the sensory inputs into motor outputs,based on experimental observations in humans. The transfer functions were appliedto the RunBot II to generate a stable walking pattern. A control system for walking wascreated, based on linear transfer functions and ground reaction information. The new controlsystem also includes ankle control, which has not been considered before. The controllerwas validated in experiments with the new RunBot III.The successful generation of stable walking with the implementation of the novel reflexiverobotic controller indicates that the control system has the potential to be used in controllingthe strategies in neural prosthesis for the retraining of an efficient and effective gait. To aidof the development of the FES walking system, a reliable and practical gait phase detectionsystem was firstly developed to provide correct ground contact information and trigger timingfor the control. The reliability of the system was investigated in experiments with tenable-bodied subjects. Secondly, an automatic FES walking system was implemented, whichcan apply stimulation to eight muscles (four in each leg) in synchrony with the user’s walkingactivity. The feasibility and effectiveness of this system for gait assistance was demonstratedwith an experiment in seven able-bodied participants.This thesis addresses the feasibility and effectiveness of applying biomimetic robotic controlprinciples to FES control. The interaction among robotic control, biology and FES controlin assistive neural prosthesis provides a novel framework to developing an efficient andeffective control system that can be applied in various control applications.
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The Runbot: engineering control applied to rehabilitation in spinal cord injury patients
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