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Evaluation of Spatiotemporal Patterns of the Spinal Muscle Coordination Output during Walking in the Exoskeleton. | LitMetric

AI Article Synopsis

  • Recent research has shown that while kinematic and kinetic measurements are useful for assessing walking performance in exoskeletons, they fall short in providing insight into neural control strategies and muscle coordination.
  • The PEPATO software has been developed as a benchmarking tool to evaluate changes in spinal cord activity during walking in exoskeletons, correlating this data with normal walking references.
  • An example demonstrated the software's capability to analyze EMG activity during walking in a specially designed exoskeleton, revealing significant insights into muscle activation patterns and spinal motor control, crucial for rehabilitation.

Article Abstract

Recent advances in the performance and evaluation of walking in exoskeletons use various assessments based on kinematic/kinetic measurements. While such variables provide general characteristics of gait performance, only limited conclusions can be made about the neural control strategies. Moreover, some kinematic or kinetic parameters are a consequence of the control implemented on the exoskeleton. Therefore, standard indicators based on kinematic variables have limitations and need to be complemented by performance measures of muscle coordination and control strategy. Knowledge about what happens at the spinal cord output level might also be critical for rehabilitation since an abnormal spatiotemporal integration of activity in specific spinal segments may result in a risk for abnormalities in gait recovery. Here we present the PEPATO software, which is a benchmarking solution to assess changes in the spinal locomotor output during walking in the exoskeleton with respect to reference data on normal walking. In particular, functional and structural changes at the spinal cord level can be mapped into muscle synergies and spinal maps of motoneuron activity. A user-friendly software interface guides the user through several data processing steps leading to a set of performance indicators as output. We present an example of the usage of this software for evaluating walking in an unloading exoskeleton that allows a person to step in simulated reduced (the Moon's) gravity. By analyzing the EMG activity from lower limb muscles, the algorithms detected several performance indicators demonstrating differential adaptation (shifts in the center of activity, prolonged activation) of specific muscle activation modules and spinal motor pools and increased coactivation of lumbar and sacral segments. The software is integrated at EUROBENCH facilities to benchmark the performance of walking in the exoskeleton from the point of view of changes in the spinal locomotor output.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370895PMC
http://dx.doi.org/10.3390/s22155708DOI Listing

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