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Selective control of gait subtasks in robotic gait training: foot clearance support in stroke survivors with a powered exoskeleton.

Koopman B, van Asseldonk EH, van der Kooij H - J Neuroeng Rehabil (2013)

Bottom Line: The provided support did not result in reliance on the support for both groups.This enables the therapist to focus the support on the subtasks that are impaired, and leave the other subtasks up to the patient, encouraging him to participate more actively in the training.Additionally, the speed-dependent reference patterns provide the therapist with the tools to easily adapt the treadmill speed to the capabilities and progress of the patient.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biomedical Technology and Technical Medicine MIRA, Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands. b.koopman@utwente.nl

ABSTRACT

Background: Robot-aided gait training is an emerging clinical tool for gait rehabilitation of neurological patients. This paper deals with a novel method of offering gait assistance, using an impedance controlled exoskeleton (LOPES). The provided assistance is based on a recent finding that, in the control of walking, different modules can be discerned that are associated with different subtasks. In this study, a Virtual Model Controller (VMC) for supporting one of these subtasks, namely the foot clearance, is presented and evaluated.

Methods: The developed VMC provides virtual support at the ankle, to increase foot clearance. Therefore, we first developed a new method to derive reference trajectories of the ankle position. These trajectories consist of splines between key events, which are dependent on walking speed and body height. Subsequently, the VMC was evaluated in twelve healthy subjects and six chronic stroke survivors. The impedance levels, of the support, were altered between trials to investigate whether the controller allowed gradual and selective support. Additionally, an adaptive algorithm was tested, that automatically shaped the amount of support to the subjects' needs. Catch trials were introduced to determine whether the subjects tended to rely on the support. We also assessed the additional value of providing visual feedback.

Results: With the VMC, the step height could be selectively and gradually influenced. The adaptive algorithm clearly shaped the support level to the specific needs of every stroke survivor. The provided support did not result in reliance on the support for both groups. All healthy subjects and most patients were able to utilize the visual feedback to increase their active participation.

Conclusion: The presented approach can provide selective control on one of the essential subtasks of walking. This module is the first in a set of modules to control all subtasks. This enables the therapist to focus the support on the subtasks that are impaired, and leave the other subtasks up to the patient, encouraging him to participate more actively in the training. Additionally, the speed-dependent reference patterns provide the therapist with the tools to easily adapt the treadmill speed to the capabilities and progress of the patient.

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Effect of non-adaptive support on reliance. A: Mean normalized step height during different steps of the trial in which the healthy subjects walked with the compliant (HC) and stiff (HS) step-height VMC. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, during the first step of the catch block and during continuous exposure. Continuous exposure is based on the last 10 steps of the last exposure block. B: Mean normalized step height during different steps of the trial in which the stroke survivors walked with the compliant (PCV) and stiff (PSV) step-height VMC, in combination with visual feedback. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, and the first step in the catch block. The last exposure block, with 50 steps of continuous exposure, was not included in the protocol of the stroke survivors. The error bars indicate the standard error of the mean. *p < 0.05.
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Figure 9: Effect of non-adaptive support on reliance. A: Mean normalized step height during different steps of the trial in which the healthy subjects walked with the compliant (HC) and stiff (HS) step-height VMC. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, during the first step of the catch block and during continuous exposure. Continuous exposure is based on the last 10 steps of the last exposure block. B: Mean normalized step height during different steps of the trial in which the stroke survivors walked with the compliant (PCV) and stiff (PSV) step-height VMC, in combination with visual feedback. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, and the first step in the catch block. The last exposure block, with 50 steps of continuous exposure, was not included in the protocol of the stroke survivors. The error bars indicate the standard error of the mean. *p < 0.05.

Mentions: We did not find any evidence for reliance of the subjects on the provided support, when they are exposed to continuous non-adaptive support. No significant difference between the initial exposure (first steps of the exposure blocks) and prolonged exposure (last steps of the exposure block) was found (see Figure 9). The step height during the first step of the catch block also revealed no signs of reliance. It shows that the subjects drop back to their baseline, without any significant undershoot, which was to be expected when reliance would occur (see Figure 9). This holds for the compliant as well as the stiff controller. Even when the subjects received continuous support for a longer period of time (50 steps of continuous exposure), the step height did not significantly differ from the initial exposure.


Selective control of gait subtasks in robotic gait training: foot clearance support in stroke survivors with a powered exoskeleton.

Koopman B, van Asseldonk EH, van der Kooij H - J Neuroeng Rehabil (2013)

Effect of non-adaptive support on reliance. A: Mean normalized step height during different steps of the trial in which the healthy subjects walked with the compliant (HC) and stiff (HS) step-height VMC. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, during the first step of the catch block and during continuous exposure. Continuous exposure is based on the last 10 steps of the last exposure block. B: Mean normalized step height during different steps of the trial in which the stroke survivors walked with the compliant (PCV) and stiff (PSV) step-height VMC, in combination with visual feedback. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, and the first step in the catch block. The last exposure block, with 50 steps of continuous exposure, was not included in the protocol of the stroke survivors. The error bars indicate the standard error of the mean. *p < 0.05.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3585791&req=5

Figure 9: Effect of non-adaptive support on reliance. A: Mean normalized step height during different steps of the trial in which the healthy subjects walked with the compliant (HC) and stiff (HS) step-height VMC. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, during the first step of the catch block and during continuous exposure. Continuous exposure is based on the last 10 steps of the last exposure block. B: Mean normalized step height during different steps of the trial in which the stroke survivors walked with the compliant (PCV) and stiff (PSV) step-height VMC, in combination with visual feedback. Mean parameters are calculated during the first step of the exposure block, during the last step of the exposure block, and the first step in the catch block. The last exposure block, with 50 steps of continuous exposure, was not included in the protocol of the stroke survivors. The error bars indicate the standard error of the mean. *p < 0.05.
Mentions: We did not find any evidence for reliance of the subjects on the provided support, when they are exposed to continuous non-adaptive support. No significant difference between the initial exposure (first steps of the exposure blocks) and prolonged exposure (last steps of the exposure block) was found (see Figure 9). The step height during the first step of the catch block also revealed no signs of reliance. It shows that the subjects drop back to their baseline, without any significant undershoot, which was to be expected when reliance would occur (see Figure 9). This holds for the compliant as well as the stiff controller. Even when the subjects received continuous support for a longer period of time (50 steps of continuous exposure), the step height did not significantly differ from the initial exposure.

Bottom Line: The provided support did not result in reliance on the support for both groups.This enables the therapist to focus the support on the subtasks that are impaired, and leave the other subtasks up to the patient, encouraging him to participate more actively in the training.Additionally, the speed-dependent reference patterns provide the therapist with the tools to easily adapt the treadmill speed to the capabilities and progress of the patient.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biomedical Technology and Technical Medicine MIRA, Department of Biomechanical Engineering, University of Twente, Enschede, The Netherlands. b.koopman@utwente.nl

ABSTRACT

Background: Robot-aided gait training is an emerging clinical tool for gait rehabilitation of neurological patients. This paper deals with a novel method of offering gait assistance, using an impedance controlled exoskeleton (LOPES). The provided assistance is based on a recent finding that, in the control of walking, different modules can be discerned that are associated with different subtasks. In this study, a Virtual Model Controller (VMC) for supporting one of these subtasks, namely the foot clearance, is presented and evaluated.

Methods: The developed VMC provides virtual support at the ankle, to increase foot clearance. Therefore, we first developed a new method to derive reference trajectories of the ankle position. These trajectories consist of splines between key events, which are dependent on walking speed and body height. Subsequently, the VMC was evaluated in twelve healthy subjects and six chronic stroke survivors. The impedance levels, of the support, were altered between trials to investigate whether the controller allowed gradual and selective support. Additionally, an adaptive algorithm was tested, that automatically shaped the amount of support to the subjects' needs. Catch trials were introduced to determine whether the subjects tended to rely on the support. We also assessed the additional value of providing visual feedback.

Results: With the VMC, the step height could be selectively and gradually influenced. The adaptive algorithm clearly shaped the support level to the specific needs of every stroke survivor. The provided support did not result in reliance on the support for both groups. All healthy subjects and most patients were able to utilize the visual feedback to increase their active participation.

Conclusion: The presented approach can provide selective control on one of the essential subtasks of walking. This module is the first in a set of modules to control all subtasks. This enables the therapist to focus the support on the subtasks that are impaired, and leave the other subtasks up to the patient, encouraging him to participate more actively in the training. Additionally, the speed-dependent reference patterns provide the therapist with the tools to easily adapt the treadmill speed to the capabilities and progress of the patient.

Show MeSH
Related in: MedlinePlus