Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis

Abstract

A hybrid neuroprosthesis that combines human muscle power, elicited through functional electrical stimulation (FES), with a powered orthosis may be advantageous over a sole FES or a powered exoskeleton-based rehabilitation system. The hybrid system can conceivably overcome torque reduction due to FES-induced muscle fatigue by complementarily using torque from the powered exoskeleton. The second advantage of the hybrid system is that the use of human muscle power can supplement the powered exoskeleton's power (motor torque) requirements; thus, potentially reducing the size and weight of a walking restoration system. To realize these advantages, however, it is unknown how to concurrently optimize desired control performance and allocation of control inputs between FES and electric motor. In this paper, a model predictive control-based dynamic control allocation (DCA) is used to allocate control between FES and the electric motor that simultaneously maintain a desired knee angle. The experimental results, depicting the performance of the DCA method while the muscle fatigues, are presented for an able-bodied participant and a participant with spinal cord injury. The experimental results showed that the motor torque recruited by the hybrid system was less than that recruited by the motor-only system, the algorithm can be easily used to allocate more control input to the electric motor as the muscle fatigues, and the muscle fatigue induced by the hybrid system was found to be less than the fatigue induced by sole FES. These results validate the aforementioned advantages of the hybrid system; thus implying the hybrid technology's potential use in walking rehabilitation.

Figures

Figure 1

The hybrid leg extension neuroprosthesis uses a motor at the knee joint, τm, and electrical stimulation of the quadriceps muscles, I, to move the shank. The position of the shank relative to equilibrium is θ, and ϕ is the anatomical knee angle.

Figure 2

The modified hybrid neuroprosthesis system that combines FES quadriceps muscle with an electric motor.

Figure 3

This figure shows the regulation performance of the two participants.

Figure 4

This figure shows the inputs applied to the right leg of S1 and left leg of S2. [Norm.] stands for normalized (no units). The dashed lines stand for desired control inputs, which were computed based on the musculoskeletal parameters as described in Section 4.2.

Figure 5

This figure shows the estimated muscle fatigue of the right leg of S1 and left leg of S2.

Figure 6

This figure shows the post-experiment fatigue test results after the 3 scenarios.