Research Article Experimental Implementation of Automatic Control of Posture-Dependent Stimulation in an Implanted Standing Neuroprosthesis Brooke M. Odle , 1,2 Lisa M. Lombardo , 2 Musa L. Audu , 1,2 and Ronald J. Triolo 1,2 1 Department of Biomedical Engineering, Case Western Reserve University, Cleveland 44106, USA 2 Motion Study Laboratory, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland 44106, USA Correspondence should be addressed to Brooke M. Odle; brooke.odle@case.edu Received 23 May 2018; Accepted 13 January 2019; Published 14 March 2019 Academic Editor: Le Ping Li Copyright © 2019 Brooke M. Odle et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Knowledge of the upper extremity (UE) effort exerted under real-world conditions is important for understanding how persons with motor or sensory disorders perform the postural shifts necessary to complete many activities of daily living while standing. To this end, a feedback controller, named the “Posture Follower Controller”, was developed to aid in task-dependent posture shifting by individuals with spinal cord injury standing with functional neuromuscular stimulation. In this experimental feasibility study, the controller modulated activation to the paralyzed lower extremity muscles as a function of the position of overall center of pressure (CoP), which was prescribed to move in a straight line in forward and diagonal directions. Posture-dependent control of stimulation enabled leaning movements that translated the CoP up to 48 mm away from the nominal position during quiet standing. The mean 95% prediction ellipse area, a measure of the CoP dispersion in the forward, forward-right, and forward-left directions, was 951 0 ± 341 1 mm 2 , 1095 9 ± 251 2 mm 2 , and 1364 5 ± 688 2 mm 2 , respectively. The average width of the prediction ellipses across the three directions was 15.1 mm, indicating that the CoP deviated from the prescribed path as task-dependent postures were assumed. The average maximal UE effort required to adjust posture across all leaning directions was 24.1% body weight, which is only slightly more than twice of what is required to maintain balance in an erect standing posture. These preliminary findings suggest that stimulation can be modulated to effectively assume user-specified, task-dependent leaning postures characterized by the CoP shifts that deviate away from the nominal position and which require moderate UE effort to execute. 1. Introduction Spinal cord injury (SCI) often results in partial or total paralysis of the trunk and lower extremity (LE) muscles. Implanted neuroprostheses (NPs) utilizing functional neuro- muscular stimulation (FNS) can restore basic standing func- tion in individuals with SCI, providing them with the independence to accomplish several activities of daily living [1, 2]. Standing NPs supply constant preprogrammed open- loop stimulation to the trunk, hip, and knee extensors to maintain a single, upright stance. Thus, to maintain balance in the presence of postural perturbations, NP users rely on voluntary upper extremity (UE) effort exerted on a support device, such as a walker or a countertop. To address this lim- itation, previous groups explored closed-loop feedback con- trol systems for standing with stimulation employed at individual joints [3–8] as well as a stimulation controller based on comprehensive or global joint feedback combined with center of mass (CoM) acceleration that rejected destabi- lizing perturbations and reduced the UE effort to maintain standing balance [9]. However, these advanced control sys- tems have been designed to maintain only a single upright setpoint in the nominal standing position. Users are only able to stand optimally and resist potentially destabilizing pertur- bations in one erect, neutral posture rather than at forward- or side-leaning postures best suited for specific functional Hindawi Applied Bionics and Biomechanics Volume 2019, Article ID 2639271, 11 pages https://doi.org/10.1155/2019/2639271