Abstract
Control of human walking is not thoroughly understood, which has implications in developing suitable strategies for the retraining of a functional gait following neurological injuries such as spinal cord injury (SCI). Bipedal robots allow us to investigate simple elements of the complex nervous system to quantify their contribution to motor control. RunBot is a bipedal robot which operates through reflexes without using central pattern generators or trajectory planning algorithms. Ground contact information from the feet is used to activate motors in the legs, generating a gait cycle visually similar to that of humans. Rather than developing a more complicated biologically realistic neural system to control the robot's stepping, we have instead further simplified our model by measuring the correlation between heel contact and leg muscle activity (EMG) in human subjects during walking and from this data created filter functions transferring the sensory data into motor actions. Adaptive filtering was used to identify the unknown transfer functions which translate the contact information into muscle activation signals. Our results show a causal relationship between ground contact information from the heel and EMG, which allows us to create a minimal, linear, analogue control system for controlling walking. The derived transfer functions were applied to RunBot II as a proof of concept. The gait cycle produced was stable and controlled, which is a positive indication that the transfer functions have potential for use in the control of assistive devices for the retraining of an efficient and effective gait with potential applications in SCI rehabilitation.
Highlights
Human walking can be viewed as a complex programme of reflexes which through the use of feedback and feed-forward processes allows stepping to adapt to a constantly changing terrain or walking environment
We have shown that there is a direct causal relationship between foot contact information and muscle activity during biped walking
This causal relationship allowed us to calculate filter functions using established filtering techniques, which reproduce the activations of the relevant muscles after foot contact
Summary
Human walking can be viewed as a complex programme of reflexes which through the use of feedback and feed-forward processes allows stepping to adapt to a constantly changing terrain or walking environment. Many different control strategies have been used within robotics, to produce bipeds with a stable and efficient gait pattern, and for studying biological models and gaining insight into walking control systems that may be present in humans. This allows us to simplify and analyse individual components of a complex system to study their role in generating functional locomotion. From this information, development can be made in the area of rehabilitation engineering with the aim of improving functional gait in individuals with spinal cord injuries (SCI) and other neurological injuries. It is of fundamental importance to find a successful mechanism to control FES, one which is realtime, simple and does not override or counteract voluntary control originating from the user
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