Dataset Information

Identifying classifier input signals to predict a cross-slope during transtibial amputee walking.

ABSTRACT: Advanced prosthetic foot designs often incorporate mechanisms that adapt to terrain changes in real-time to improve mobility. Early identification of terrain (e.g., cross-slopes) is critical to appropriate adaptation. This study suggests that a simple classifier based on linear discriminant analysis can accurately predict a cross-slope encountered (0°, -15°, 15°) using measurements from the residual limb, primarily from the prosthesis itself. The classifier was trained and tested offline using motion capture and in-pylon sensor data collected during walking trials in mid-swing and early stance. Residual limb kinematics, especially measurements from the foot, shank and ankle, successfully predicted the cross-slope terrain with high accuracy (99%). Although accuracy decreased when predictions were made for test data instead of the training data, the accuracy was still relatively high for one input signal set (>89%) and moderate for three others (>71%). This suggests that classifiers can be designed and generalized to be effective for new conditions and/or subjects. While measurements of shank acceleration and angular velocity from only in-pylon sensors were insufficient to accurately predict the cross-slope terrain, the addition of foot and ankle kinematics from motion capture data allowed accurate terrain prediction. Inversion angular velocity and foot vertical velocity were particularly useful. As in-pylon sensor data and shank kinematics from motion capture appeared interchangeable, combining foot and ankle kinematics from prosthesis-mounted sensors with shank kinematics from in-pylon sensors may provide enough information to accurately predict the terrain.

SUBMITTER: Shell CE

PROVIDER: S-EPMC5815617 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Identifying classifier input signals to predict a cross-slope during transtibial amputee walking.

Shell Courtney E CE Klute Glenn K GK Neptune Richard R RR

PloS one 20180216 2

Advanced prosthetic foot designs often incorporate mechanisms that adapt to terrain changes in real-time to improve mobility. Early identification of terrain (e.g., cross-slopes) is critical to appropriate adaptation. This study suggests that a simple classifier based on linear discriminant analysis can accurately predict a cross-slope encountered (0°, -15°, 15°) using measurements from the residual limb, primarily from the prosthesis itself. The classifier was trained and tested offline using m ...[more]

PMID: 29451922

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Project description:This study investigated electrocortical dynamics of human walking across different unconstrained walking conditions (i.e., level ground (LW), ramp ascent (RA), and stair ascent (SA)). Non-invasive active-electrode scalp electroencephalography (EEG) signals were recorded and a systematic EEG processing method was implemented to reduce artifacts. Source localization combined with independent component analysis and k-means clustering revealed the involvement of four clusters in the brain during the walking tasks: Left and Right Occipital Lobe (LOL, ROL), Posterior Parietal Cortex (PPC), and Central Sensorimotor Cortex (SMC). Results showed that the changes of spectral power in the PPC and SMC clusters were associated with the level of motor task demands. Specifically, we observed α and β suppression at the beginning of the gait cycle in both SA and RA walking (relative to LW) in the SMC. Additionally, we observed significant β rebound (synchronization) at the initial swing phase of the gait cycle, which may be indicative of active cortical signaling involved in maintaining the current locomotor state. An increase of low γ band power in this cluster was also found in SA walking. In the PPC, the low γ band power increased with the level of task demands (from LW to RA and SA). Additionally, our results provide evidence that electrocortical amplitude modulations (relative to average gait cycle) are correlated with the level of difficulty in locomotion tasks. Specifically, the modulations in the PPC shifted to higher frequency bands when the subjects walked in RA and SA conditions. Moreover, low γ modulations in the central sensorimotor area were observed in the LW walking and shifted to lower frequency bands in RA and SA walking. These findings extend our understanding of cortical dynamics of human walking at different level of locomotion task demands and reinforces the growing body of literature supporting a shared-control paradigm between spinal and cortical networks during locomotion.

Project description:BackgroundPersons with lower limb amputation often experience decreased physical capacity, difficulty walking, and increased fall risk. To either prevent or recover from a loss of balance, one must effectively regulate their stepping movements. It is therefore critical to identify how well persons with amputation regulate stepping. Here, we used a multi-objective control framework based on Goal Equivalent Manifolds to identify how persons with transtibial amputation (TTA) regulate lateral stepping while walking without and with lateral perturbations.Research questionWhen walking in destabilizing environments, do otherwise healthy persons with TTA exhibit greater difficulty regulating lateral stepping due to impaired control? Or do they instead continue to use similar strategies to regulate lateral stepping despite their amputation?MethodsEight persons with unilateral TTA and thirteen able-bodied (AB) controls walked in a virtual environment under three conditions: no perturbations, laterally oscillating visual field, and laterally oscillating treadmill platform. We analyzed step-to-step time series of step widths and absolute lateral body positions. We computed means, standard deviations and Detrended Fluctuation Analysis scaling exponents for each time series and computed how much participants directly corrected step width and position deviations at each step. We compared our results to computational predictions to identify the underlying causes of our experimental findings.ResultsAll participants exhibited significantly increased variability, decreased scaling exponents, and tighter direct control when perturbed. Simulations from our stepping regulation models revealed that people responded to the increased variability produced by the imposed perturbations by tightening their control of both step width and lateral position. Participants with TTA exhibited only a few minor differences from AB in lateral stepping regulation, even when subjected to substantially destabilizing lateral perturbations.SignificanceSince control of stepping is intrinsically multi-objective, developing effective interventions to reduce fall risk in persons with amputation will likely require strategies that adopt multi-objective approaches.

Dataset Information

Identifying classifier input signals to predict a cross-slope during transtibial amputee walking.

Publications

Identifying classifier input signals to predict a cross-slope during transtibial amputee walking.

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