Predicting walking response to ankle exoskeletons using data-driven models
Summary (1 min read)
Introduction
- The authors expected the NPV model’s prediction accuracy to meet or exceed that of the 192 LPV model.
- The amount of data required to accurately predict response to exoskeletons will restrict the settings in which 252 phase-varying models are practical, such as in clinical gait analysis where datasets typically contain only a 253 few gait cycles [2, 8].
- To test each model’s generalizability across a range of exoskeleton torque conditions, the authors separately predicted 261 responses to torque in the K1, K2, and K3 datasets, termed held-out conditions, at a 12.5% stride prediction 262 horizon (1/8th of a stride).
VI. DISCUSSION 336
- The authors evaluated the ability of subject-specific phase-varying models to predict kinematic and myoelectric 337 responses to ankle exoskeleton torques during treadmill walking.
- 351 the LPV model’s predictions explained more of the variance in kinematic responses to exoskeletons than the 352 PV model, regardless of whether predictions interpolated (K1 and K2) or extrapolated (K3) relative to the 353 training set.
VII. CONCLUSION 459
- To their knowledge, this is the first study to predict subject-specific responses to ankle exoskeletons using 460 phase-varying models.
- Without making assumptions about individual physiology or motor control, an LPV 461 model predicted short-time kinematic responses to bilateral passive ankle exoskeletons, though predicting 462 myoelectric responses remains challenging.
- Results support the utility of LPV models for studying and 463 predicting response to exoskeleton torque.
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Citations
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References
26 citations
"Predicting walking response to ankl..." refers background in this paper
...exoskeleton (ankle-foot orthosis) designs in children with cerebral palsy [9]....
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...exoskeleton design principles to reduce the energetic demand of walking and improve the quality of gait [1, 33 5, 7, 9, 10]....
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...The amount of data required to accurately predict response to exoskeletons will restrict the settings in which phase-varying models may be practical, such as in clinical gait analysis where datasets typically contain only a small number of gait cycles [2, 9]....
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26 citations
"Predicting walking response to ankl..." refers background or methods in this paper
...spaced equally over the gait cycle, we fit discrete maps between initial and final phases using weighted leastsquares regression [25, 26, 29]....
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...extension of Floquet Theory to gait with exoskeletons and indicates that, for rhythmic locomotion at a constant speed over level ground, linear phase-varying models appear to have sufficiently complex structure to predict kinematic responses to exoskeletons [25-27, 29]....
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...and prior models of human locomotion, LPV models appear appropriate for predicting responses to exoskeleton torque over short prediction horizons, evidenced by its similar prediction accuracy to the more complex NPV model and improved prediction accuracy over the less complex PV model [25-27, 29]....
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...Moreover, phase-varying modeling principles have been applied to biological systems, identifying linear phase-varying dynamics to investigate gait stability and predict changes in kinematics in response to perturbations [25, 26, 29-31]....
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...Since passive exoskeletons typically elicit small changes in joint kinematics and muscle activity, we expected the validity of Floquet Theory for human gait without exoskeletons to extend to gait with exoskeletons, indicating that the LPV model should accurately predict responses to passive exoskeleton torque [1, 25-27, 29]....
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24 citations
"Predicting walking response to ankl..." refers background in this paper
...However, the myoelectric and kinematic input variables used as model inputs may also be insufficient to encode nonlinear musculotendon dynamics between the initial and final phases, which are impacted by ankle exoskeletons [17, 40, 45]....
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18 citations
"Predicting walking response to ankl..." refers background in this paper
...More physiologically-detailed musculoskeletal models have 45 been used to predict the impacts of exoskeleton design on muscle activity during walking in children with 46 cerebral palsy and running in unimpaired adults [15, 16]....
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3 citations
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Frequently Asked Questions (2)
Q2. What are the future works in "Predicting walking response to ankle exoskeletons using data-driven models" ?
Improving data-driven models and experimental protocols to study 464 and predict myoelectric responses to exoskeletons represents an important direction for future research. 465 Modeling responses to exoskeletons or other assistive devices using a phase-varying perspective has the 466 potential to inform exoskeleton design for a range of user groups.