Predictive Simulation of Post-Stroke Gait and Effects of Functional Electrical Stimulation: A Case Report

Abstract

Post-stroke patients present various gait abnormalities such as drop foot, stiff-knee gait (SKG), and knee hyperextension. Functional electrical stimulation (FES) improves drop foot gait although the mechanistic basis for this effect is not well understood. To answer this question, we evaluated the gait of a post-stroke patient walking with and without FES by inverse dynamics analysis and compared the results to an optimal control framework. The effect of FES and cause-effect relationship of changes in knee and ankle muscle strength were investigated; personalized muscle-tendon parameters allowed the prediction of pathologic gait. We also predicted healthy gait patterns at different speeds to simulate the subject walking without impairment. The passive moment of the knee played an important role in the estimation of muscle force with knee hyperextension, which was decreased during FES and knee extensor strengthening. Weakening the knee extensors and strengthening the flexors improved SKG. During FES, weak ankle plantarflexors and strong ankle dorsiflexors resulted in increased ankle dorsiflexion, which reduced drop foot. FES also improved gait speed and reduced circumduction. These findings provide insight into compensatory strategies adopted by post-stroke patients that can guide the design of individualized rehabilitation and treatment programs.

Changes in walking function and neural control following pelvic cancer surgery with reconstruction

“…At a high-level, two different neural control assumptions representing two different philosophies have been used in published studies. The first neural control assumption, which is used in most published studies (Fox et al, 2009;Koelewijn and van den Bogert, 2016;Lin et al, 2018;Song and Geyer, 2018;Falisse et al, 2019;Pitto et al, 2019;Miller and Esposito, 2021;Santos et al, 2021;Cseke et al, 2022;Hu et al, 2022;Bianco et al, 2023), will be termed "absolute control." Absolute control involves minimizing one or more quantities in an absolute sense (i.e., relative to zero), such as minimizing the sum of squares of predicted muscle activations regardless of the walking situation or treatment.…”

“…Coupling comprehensive human movement data collection with personalized neuromusculoskeletal computer modeling provides an objective approach for quantifying changes in walking function as well as predicting how surgical decisions and custom prosthesis design will affect post-surgery walking function. Several previous studies have collected comprehensive human movement data sets from individuals who were implanted with an instrumented total knee replacement (Taylor et al, 2004;Fregly et al, 2012;Bergmann et al, 2014) or who suffered a stroke (Meyer et al, 2016;Sauder et al, 2019;Santos et al, 2021). These data sets include surface marker motion, ground reaction, and EMG data collected for walking and other functional tasks, and researchers have created associated personalized neuromusculoskeletal models using such data sets.…”

“…Personalized models have been used to analyze joint contact loads in knee osteoarthritis, muscle force generation in cerebral palsy, and neural control capabilities in stroke (Fregly et al, 2012;Meyer et al, 2016;Saxby et al, 2016;Pitto et al, 2019;Kainz and Jonkers, 2023;Jing et al, 2023). They have also been used to develop predictive simulations of walking that investigate how an individual post-stroke would walk at his fastest comfortable speed (Meyer et al, 2016), how an individual post-stroke would walk while receiving functional electrical stimulation of different leg muscles (Sauder et al, 2019;Santos et al, 2021), and how a neurologically healthy individual would walk following different pelvic cancer surgeries with different levels of post-surgery rehabilitation (Vega et al, 2022). However, no study to date has validated a predictive simulation of post-surgery walking using post-and pre-surgery experimental walking data collected from the same patient, where the post-surgery data are used to validate the walking prediction and the pre-surgery data are used to create the personalized neuromusculoskeletal model of the patient.…”

“…While nearly all published three-dimensional predictive simulations of walking have used individual muscle controls (Anderson and Pandy, 2001;Fox et al, 2009;Koelewijn and van den Bogert, 2016;Lin et al, 2018;Song and Geyer, 2018;Falisse et al, 2019;Miller and Esposito, 2021;Santos et al, 2021;Cseke et al, 2022;Hu et al, 2022;Bianco et al, 2023), several studies have explored using muscle synergy controls as an alternative (Meyer et al, 2016;Pitto et al, 2019;Sauder et al, 2019;Vega et al, 2022). Muscle synergies (also called "motor modules" (Clark et al, 2010;Oliveira et al, 2014)) are a low-dimensional representation of a higher-dimensional control space (D'Avella et al, 2003;Tresch et al, 2006;Chvatal and Ting, 2013) and have traditionally been used to study how the healthy and impaired human central nervous system reduces control complexity for functional tasks such as walking.…”