Toward Balance Recovery With Leg Prostheses Using Neuromuscular Model Control

Abstract

Objective: Lower limb amputees are at high risk of falling as current prosthetic legs provide only limited functionality for recovering balance after unexpected disturbances. For instance, the most established control method used on powered leg prostheses tracks local joint impedance functions without taking the global function of the leg in balance recovery into account. Here, we explore an alternative control policy for powered transfemoral prostheses that considers the global leg function and is based on a neuromuscular model of human locomotion.

Methods: We adapt this model to describe and simulate an amputee walking with a powered prosthesis using the proposed control, and evaluate the gait robustness when confronted with rough ground and swing leg disturbances. We then implement and partially evaluate the resulting controller on a leg prosthesis prototype worn by a nonamputee user.

Results: In simulation, the proposed prosthesis control leads to gaits that are more robust than those obtained by the impedance control method. The initial hardware experiments with the prosthesis prototype show that the proposed control reproduces normal walking patterns qualitatively and effectively responds to disturbances in early and late swing. However, the response to midswing disturbances neither replicates human responses nor averts falls.

Conclusions: The neuromuscular model control is a promising alternative to existing prosthesis controls, although further research will need to improve on the initial implementation and determine how well these results transfer to amputee gait.

Significance: This paper provides a potential avenue for future development of control policies that help to improve amputee balance recovery.

Fig. 1

Snapshots following a simulated tripping event. Response of the proposed prosthetic control (A) and impedance control (B) to a 15 N ·s impulse applied shortly after toe-off (red arrow). The proposed neuromuscular model control successfully responds to the trip and continues walking. In contrast, impedance control cannot effectively react to the same disturbance and subsequently falls.

Fig. 2

Unimpaired human walking model with labeled muscles and definitions of hip and knee angles, leg length, and current and target swing leg angles.

Fig. 3

Prosthesis prototype. (A) CAD render of proposed design of powered knee and ankle prosthesis used in simulated experiments. (B) Current stage of prototype with active knee and passive ankle used for hardware evaluation experiments.

Fig. 4

Control overview of the amputee walking model. The amputee and the prosthesis are driven by nearly identical neuromuscular controls. During stance, reflex stimulations of Hill-type muscles generate torques about the joints. During swing, the control specifies torques that drive the legs to desired landing angles α_tgt (compare Fig. 2). To control the prosthesis, the torques produced by the muscles and the swing control are converted to motor voltages by series elastic actuator controllers.

Fig. 5

Control performance of simulated prosthesis on rough terrain. The distances walked over terrains with different ground roughness are compared between the amputee model using a powered knee-ankle prosthesis with impedance control (green) and hybrid neuromuscular control (blue) as well as with the unimpaired human model (red). Shown are the median and range (25^th and 75^th percentiles) of the covered distances for 50 terrains sampled at each roughness level.

Fig. 6

Tripping response of the amputee model with neuromuscular (A) and impedance control (B) of the prosthesis. Shown are the prosthetic toe trajectories during undisturbed gait (dashed line) and when disturbed by a 15 N ·s impulse (solid line). The neuromuscular controller effectively responds to the disturbance and maintains a qualitatively similar toe trajectory. The impedance controller leads to foot scuffing and an eventual fall (compare Fig. 1).

Fig. 7

A non-amputee experimenter tests the prosthesis using an iWalk Crutch as a knee adaptor. The experimenter wears a lift shoe on the contralateral leg to compensate for the added thigh length of the prosthesis and knee adaptor.

Fig. 8

Prosthesis behavior at walking speed of 0.5 m/s. Shown are the hip and knee trajectories, the knee controller torque, and the activations of the vastus, hamstring, and gastrocnemius muscles generated by the prosthesis control in the testbed. Solid black lines show averaged data of ten trials with the individual trials depicted in gray. Dashed lines show corresponding data from human walking at preferred speed (joint angles and knee torque: [30], muscle surface electromyograms: [31]). Solid and dashed vertical lines indicate median toe off times for the prosthesis and human data respectively.

Fig. 9

Response to simulated tripping disturbance. (A) Undisturbed ankle trajectory calculated from hip and knee angles assuming constant hip height. (B-D) Ankle trajectories with disturbance applied in early, mid and late swing (arrows). The vertical dashed line shows the target landing position of the foot, which corresponds to a 75 degree landing angle.