Abstract

Closed-loop controlled functional electrical stimulation (FES) applied to the lower limb muscles can be used as a neuroprosthesis for standing balance in neurologically impaired individuals. The objective of this study was to propose a methodology for designing a proportional-integral-derivative (PID) controller for FES applied to the ankle muscles toward maintaining standing balance for several minutes and in the presence of perturbations. First, a model of the physiological control strategy for standing balance was developed. Second, the parameters of a PID controller that mimicked the physiological balance control strategy were determined to stabilize the human body when modeled as an inverted pendulum. Third, this PID controller was implemented using a custom-made Inverted Pendulum Standing Apparatus that eliminated the effect of visual and vestibular sensory information on voluntary balance control. Using this setup, the individual-specific FES controllers were tested in able-bodied individuals and compared with disrupted voluntary control conditions in four experimental paradigms: (i) quiet-standing; (ii) sudden change of targeted pendulum angle (step response); (iii) balance perturbations that simulate arm movements; and (iv) sudden change of targeted angle of a pendulum with individual-specific body-weight (step response). In paradigms (i) to (iii), a standard 39.5-kg pendulum was used, and 12 subjects were involved. In paradigm (iv) 9 subjects were involved. Across the different experimental paradigms and subjects, the FES-controlled and disrupted voluntarily-controlled pendulum angle showed root mean square errors of <1.2 and 2.3 deg, respectively. The root mean square error (all paradigms), rise time, settle time, and overshoot [paradigms (ii) and (iv)] in FES-controlled balance were significantly smaller or tended to be smaller than those observed with voluntarily-controlled balance, implying improved steady-state and transient responses of FES-controlled balance. At the same time, the FES-controlled balance required similar torque levels (no significant difference) as voluntarily-controlled balance. The implemented PID parameters were to some extent consistent among subjects for standard weight conditions and did not require prolonged individual-specific tuning. The proposed methodology can be used to design FES controllers for closed-loop controlled neuroprostheses for standing balance. Further investigation of the clinical implementation of this approach for neurologically impaired individuals is needed.

Highlights

  • In various neurological conditions, including spinal cord injury, stroke, and traumatic brain injury, a diminished ability to maintain balance during stance is common

  • To investigate standing balance based on this model, a humansized inverted pendulum apparatus, hereafter referred to as Inverted Pendulum Standing Apparatus (IPSA), was created inhouse (Tan et al, 2014; Figure 1A)

  • Three subjects were not able to tolerate the discomfort due to functional electrical stimulation (FES) application in the Body-weight paradigm and, only nine subjects participated in test paradigm (iv)

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Summary

Introduction

In various neurological conditions, including spinal cord injury, stroke, and traumatic brain injury, a diminished ability to maintain balance during stance is common. By applying functional electrical stimulation (FES) to contract lower limb muscles (Popovic, 2014), multiple groups have attempted to facilitate or improve the standing ability of these clinical populations. A number of FES closedloop control strategies have been investigated, predominantly focusing on plantarflexion/dorsiflexion control of the ankle joints during stance These have included linear quadratic Gaussian (Hunt et al, 1997; Munih et al, 1997), pole placement design (Hunt et al, 2001; Gollee et al, 2004), H-infinity (Holderbaum et al, 2004), artificial neural network, and sliding mode (Kobravi and Erfanian, 2012) control techniques. These control techniques suffer from limitations, including the need for voluntary trunk control, the lack of a strong physiological basis and/or high computational complexity limiting the operating frequency of the controller

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