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1. Real-time feedback control of split-belt ratio to induce targeted step length asymmetry

   https://doi.org/10.1186/s12984-022-01044-0  

   Carr, Sean; Rasouli, Fatemeh; Kim, Seok Hun; Reed, Kyle B. (December 2022, Journal of NeuroEngineering and Rehabilitation)

   Abstract Introduction Split-belt treadmill training has been used to assist with gait rehabilitation following stroke. This method modifies a patient’s step length asymmetry by adjusting left and right tread speeds individually during training. However, current split-belt training approaches pay little attention to the individuality of patients by applying set tread speed ratios (e.g., 2:1 or 3:1). This generalization results in unpredictable step length adjustments between the legs. To customize the training, this study explores the capabilities of a live feedback system that modulates split-belt tread speeds based on real-time step length asymmetry. Materials and methods Fourteen healthy individuals participated in two 1.5-h gait training sessions scheduled 1 week apart. They were asked to walk on the Computer Assisted Rehabilitation Environment (CAREN) split-belt treadmill system with a boot on one foot to impose asymmetrical gait patterns. Each training session consisted of a 3-min baseline, 10-min baseline with boot, 10-min feedback with boot (6% asymmetry exaggeration in the first session and personalized in the second), 5-min post feedback with boot, and 3-min post feedback without boot. A proportional-integral (PI) controller was used to maintain a specified step-length asymmetry by changing the tread speed ratios during the 10-min feedback period. After the first session, a linear model between baseline asymmetry exaggeration and post-intervention asymmetry improvement was utilized to develop a relationship between target exaggeration and target post-intervention asymmetry. In the second session, this model predicted a necessary target asymmetry exaggeration to replace the original 6%. This prediction was intended to result in a highly symmetric post-intervention step length. Results and discussion Eleven out of 14 participants (78.6%) developed a successful relationship between asymmetry exaggeration and decreased asymmetry in the post-intervention period of the first session. Seven out of the 11 participants (63.6%) in this successful correlation group had second session post-intervention asymmetries of < 3.5%. Conclusions The use of a PI controller to modulate split-belt tread speeds demonstrated itself to be a viable method for individualizing split-belt treadmill training. 

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2. Human Gait Analysis Metric for Gait Retraining

   https://doi.org/10.1155/2019/1286864  

   Ramakrishnan, Tyagi; Kim, Seok Hun; Reed, Kyle B. (November 2019, Applied Bionics and Biomechanics)

   The combined gait asymmetry metric (CGAM) provides a method to synthesize human gait motion. The metric is weighted to balance each parameter’s effect by normalizing the data so all parameters are more equally weighted. It is designed to combine spatial, temporal, kinematic, and kinetic gait parameter asymmetries. It can also combine subsets of the different gait parameters to provide a more thorough analysis. The single number quantifying gait could assist robotic rehabilitation methods to optimize the resulting gait patterns. CGAM will help define quantitative thresholds for achievable balanced overall gait asymmetry. The study presented here compares the combined gait parameters with clinical measures such as timed up and go (TUG), six-minute walk test (6MWT), and gait velocity. The comparisons are made on gait data collected on individuals with stroke before and after twelve sessions of rehabilitation. Step length, step time, and swing time showed a strong correlation to CGAM, but the double limb support asymmetry has nearly no correlation with CGAM and ground reaction force asymmetry has a weak correlation. The CGAM scores were moderately correlated with TUG and strongly correlated to 6MWT and gait velocity. 

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3. Fascicle dynamics of the tibialis anterior muscle reflect whole-body walking economy

   https://doi.org/10.1038/S41598-023-31501-2  

   Kwak, Samuel T.; Chang, Young-Hui (December 2023, Scientific Reports)

   Humans can inherently adapt their gait pattern in a way that minimizes the metabolic cost of transport, or walking economy, within a few steps, which is faster than any known direct physiological sensor of metabolic energy. Instead, walking economy may be indirectly sensed through mechanoreceptors that correlate with the metabolic cost per step to make such gait adaptations. We tested whether velocity feedback from tibialis anterior (TA) muscle fascicles during the early stance phase of walking could potentially act to indirectly sense walking economy. As participants walked within a range of steady-state speeds and step frequencies, we observed that TA fascicles lengthen on almost every step. Moreover, the average peak fascicle velocity experienced during lengthening reflected the metabolic cost of transport of the given walking condition. We observed that the peak TA muscle activation occurred earlier than could be explained by a short latency reflex response. The activation of the TA muscle just prior to heel strike may serve as a prediction of the magnitude of the ground collision and the associated energy exchange. In this scenario, any unexpected length change experienced by the TA fascicle would serve as an error signal to the nervous system and provide additional information about energy lost per step. Our work helps provide a biomechanical framework to understand the possible neural mechanisms underlying the rapid optimization of walking economy. 

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4. A continuous statistical-geometric framework for normative and impaired gaits

   https://doi.org/10.1098/rsif.2022.0402  

   Swaminathan, Krithika; Tolkova, Irina; Baker, Lauren; Arumukhom Revi, Dheepak; Awad, Louis N.; Walsh, Conor J.; Mahadevan, L. (November 2022, Journal of The Royal Society Interface)

   A quantitative analysis of human gait patterns in space–time provides an opportunity to observe variability within and across individuals of varying motor capabilities. Impaired gait significantly affects independence and quality of life, and thus a large part of clinical research is dedicated to improving gait through rehabilitative therapies. Evaluation of these paradigms relies on understanding the characteristic differences in the kinematics and underlying biomechanics of impaired and unimpaired locomotion, which has motivated quantitative measurement and analysis of the gait cycle. Previous analysis has largely been limited to a statistical comparison of manually selected pointwise metrics identified through expert knowledge. Here, we use a recent statistical-geometric framework, elastic functional data analysis (FDA), to decompose kinematic data into continuous ‘amplitude’ (spatial) and ‘phase’ (temporal) components, which can then be integrated with established dimensionality reduction techniques. We demonstrate the utility of elastic FDA through two unsupervised applications to post-stroke gait datasets. First, we distinguish between unimpaired, paretic and non-paretic gait presentations. Then, we use FDA to reveal robust, interpretable groups of differential response to exosuit assistance. The proposed methods aim to benefit clinical practice for post-stroke gait rehabilitation, and more broadly, to automate the quantitative analysis of motion. 

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5. Facilitation of motor adaptation using multiple gait rehabilitation interventions

   https://doi.org/10.3389/fresc.2024.1238139  

   Hoque, Adila; Kim, Seok Hun; Reed, Kyle B (October 2024, Frontiers in Rehabilitation Sciences)

   Escorpizo, Reuben (Ed.)

   The rate of adjustment in a movement, driven by feedback error, is referred to as the adaptation rate, and the rate of recovery of a newly adapted movement to its unperturbed condition is called the de-adaptation rate. The rates of adaptation and de-adaptation are dependent on the training mechanism and intrinsic factors such as the participant's sensorimotor abilities. This study investigated the facilitation of the motor adaptation and de-adaptation processes for spatiotemporal features of an asymmetric gait pattern by sequentially applying split-belt treadmill (SBT) and asymmetric rhythmic auditory cueing (ARAC). Methods: Two sessions tested the individual gait characteristics of SBT and ARAC, and the remaining four sessions consisted of applying the two interventions sequentially during training. The adjustment process to the second intervention is referred to as “re-adaptation” and is driven by feedback error associated with the second intervention. Results: Ten healthy individuals participated in the randomized six-session trial. Spatiotemporal asymmetries during the adaptation and post-adaptation (when intervention is removed) stages were fitted into a two-component exponential model that reflects the explicit and implicit adaptation processes. A double component was shown to fit better than a single-component model. The decay constants of the model were indicative of the corresponding timescales and compared between trials. Results revealed that the explicit (fast) component of adaptation to ARAC was reduced for step length and step time when applied after SBT. Contrarily, the explicit component of adaptation to SBT was increased when it was applied after ARAC for step length. Additionally, the implicit (slow) component of adaptation to SBT was inhibited when applied incongruently after ARAC for step time. These outcomes show that the role of working motor memory as a translational tool between different gait interventions is dependent on (i) the adaptation mechanisms associated with the interventions, (ii) the targeted motor outcome of the interventions; the effects of factors (i) and (ii) are specific to the explicit and implicit components of the adaptation processes; these effects are unique to spatial and temporal gait characteristics. 

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