Lab member, Sasha Portnova, launched a new podcast on research in rehabilitation and assistive technologies. The first episode features Steele Lab Alumni, Elijah Kuska, with a conversation on computational biomechanics, synergies debates, and the importance of education accessibility.
Theme: Podcast about research and innovations in rehabilitation engineering and assistive technologies aimed to improve accessibility for people with disabilities. Every episode will feature engineers, medical professionals, end-users, and organizations who focus on improving the health and well-being of individuals with disabilities. We will be covering topics such as emerging tech, outcome measures, medical practice, public policy, accessibility education, and so much more!
In collaboration with Gillette Children’s Specialty Healthcare, we evaluated whether muscle synergies change when unimpaired individuals walk at different speeds and slopes.
Background: The aim of this study was to determine whether changes in synergies relate to changes in gait while walking on a treadmill at multiple speeds and slopes. The hypothesis was that significant changes in movement pattern would not be accompanied by significant changes in synergies, suggesting that synergies are not dependent on the mechanical constraints but are instead neurological in origin.
Methods: Sixteen typically developing children walked on a treadmill for nine combinations (stages) of different speeds and slopes while simultaneously collecting kinematics, kinetics, and surface electromyography (EMG) data. The kinematics for each stride were summarized using a modified version of the Gait Deviation Index that only includes the sagittal plane. The kinetics for each stride were summarized using a modified version of the Gait Deviation Index – Kinetic which includes sagittal plane moments and powers. Within each synergy group, the correlations of the synergies were calculated between the treadmill stages.
Results: While kinematics and kinetics were significantly altered at the highest slope compared to level ground when walking on a treadmill, synergies were similar across stages.
Conclusions: The high correlations between synergies across stages indicate that neuromuscular control strategies do not change as children walk at different speeds and slopes on a treadmill. However, the multiple significant differences in kinematics and kinetics between stages indicate real differences in movement pattern. This supports the theory that synergies are neurological in origin and not simply a response to the biomechanical task constraints.
Filtering parameters impact the results from muscle synergy analyses.
Abstract: Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important. The aim of this study was to evaluate how EMG signal processing impacts synergy outputs during gait. We evaluated the impacts of two common processing steps for synergy analyses: low pass (LP) filtering and unit variance scaling. We evaluated EMG data collected during barefoot walking from five muscles of 113 children with cerebral palsy (CP) and 73 typically-developing (TD) children. We applied LP filters to the EMG data with cutoff frequencies ranging from 4 to 40 Hz (reflecting the range reported in prior synergy research). We also evaluated the impact of normalizing EMG amplitude by unit variance. We found that the total variance accounted for (tVAF) by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency (e.g., 9.3 percentage points change for one synergy between 4 and 40 Hz). This change in tVAF can alter the number of synergies selected for further analyses. Normalizing tVAF to a z-score (e.g., dynamic motor control index during walking, walk-DMC) reduced sensitivity to LP cutoff. Unit variance scaling caused comparatively small changes in tVAF. Synergy weights and activations were impacted less than tVAF by LP filter choice and unit variance normalization. These results demonstrate that EMG signal processing methods impact outputs of synergy analysis and z-score based measures can assist in reporting and comparing results across studies and clinical centers.
How do muscle activations and synergies change when an individual wears an ankle exoskeleton during gait?
Abstract: Exoskeletons have the potential to assist and augment human performance. Understanding how users adapt their movement and neuromuscular control in response to external assistance is important to inform the design of these devices. The aim of this research was to evaluate changes in muscle recruitment and coordination for ten unimpaired individuals walking with an ankle exoskeleton. We evaluated changes in the activity of individual muscles, cocontraction levels, and synergistic patterns of muscle coordination with increasing exoskeleton work and torque. Participants were able to selectively reduce activity of the ankle plantarflexors with increasing exoskeleton assistance. Increasing exoskeleton net work resulted in greater reductions in muscle activity than increasing exoskeleton torque. Patterns of muscle coordination were not restricted or constrained to synergistic patterns observed during unassisted walking. While three synergies could describe nearly 95% of the variance in electromyography data during unassisted walking, these same synergies could describe only 85–90% of the variance in muscle activity while walking with the exoskeleton. Synergies calculated with the exoskeleton demonstrated greater changes in synergy weights with increasing exoskeleton work versus greater changes in synergy activations with increasing exoskeleton torque. These results support the theory that unimpaired individuals do not exclusively use central pattern generators or other low-level building blocks to coordinate muscle activity, especially when learning a new task or adapting to external assistance, and demonstrate the potential for using exoskeletons to modulate muscle recruitment and coordination patterns for rehabilitation or performance.
Filtering parameters impact the results from muscle synergy analyses.
Abstract: Muscle synergies are typically calculated from electromyographic (EMG) signals using nonnegative matrix factorization. Synergies identify weighted groups of muscles that are commonly activated together during a task, such as walking. Synergy analysis has become an emerging tool to evaluate neuromuscular control; however, the repeatability of synergies between trials and days has not been evaluated. The goal of this study was to evaluate the repeatability of synergy complexity and structure in unimpaired individuals and individuals with cerebral palsy (CP). EMG data were collected from eight lower-limb muscles during gait for six typically developing (TD) children and five children with CP on two separate days, over three walking speeds. To evaluate synergy complexity, we calculated the total variance accounted for by one synergy (tVAF1). On a given day, the average range in tVAF1 between gait cycles was 18.2% for TD and 19.1% for CP. The average standard deviation in tVAF1 between gait cycles was 4.9% for TD and 5.0% for CP. Average tVAF1 calculated across gait cycles was not significantly different between days for TD or CP participants. Comparing synergy structure, the average (standard deviation) within day correlation coefficients of synergy weights for two or more synergies were 0.89 (0.15) for TD and 0.88 (0.15) for CP. Between days, the average correlation coefficient of synergy weights for two or more synergies was greater than 0.89 for TD and 0.74 for CP. These results demonstrate that synergy complexity and structure averaged over multiple gait cycles are repeatable between days in both TD and CP groups.