A Therapist Helping Hand for Walker-Assisted Gait Rehabilitation: A Pre-Clinical Assessment

Sierra, David; Jimenez, Mario; Múnera, Marcela; Bastos, Teodiano; Frizera, Anselmo; Cifuentes, Carlos A.

doi:10.1109/ccac.2019.8920943

Cited by 5 publications

(4 citation statements)

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“…Comparing these results with literature, in [ 73 ] negative results were obtained when the user received feedback on a screen in a path-following task. Moreover, the study by [ 24 ] suggested that visual feedback on the joystick was better, even compared with haptic feedback. This evidence suggests that visual methods can be implemented to facilitate the therapists’ involvement and to provide a useful teleoperation tool.…”

Section: Results and Discussionmentioning

confidence: 99%

“…The KTE compares the achieved path by the participant against the ideal (the proposed path for the experiment), calculating the mean error and including the trial variance, as Equation ( 2 ) shows.

where the

value refers to the mean squared errors between the ideal and achieved paths, and the

value represents the data variance [ 24 , 63 ]. It is worth noting that this equation does not require the walker’s speed or acceleration, since it aims to provide insights into the spatial performance of the path-following error, rather than kinematic information.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…where the |ε| 2 value refers to the mean squared errors between the ideal and achieved paths, and the σ 2 value represents the data variance [24,63]. It is worth noting that this equation does not require the walker's speed or acceleration, since it aims to provide insights into the spatial performance of the path-following error, rather than kinematic information.…”

Section: Quantitative Assessmentmentioning

confidence: 99%

“…This has allowed the therapy manager to focus on more specific tasks such as functional rehabilitation and supervision of patients, optimizing their expertise and time [ 7 , 21 , 22 ]. In this sense, when using mobile robots such as walkers, it is crucial to provide the therapists with a communication channel that allows them to interact with the patient and the device without affecting independence or adding cognitive burden to the patient [ 17 , 23 , 24 ]. With such a communication channel, the therapists would command the robot remotely, perceive environment constraints, avoid hazardous situations, and monitor the patient state.…”

Section: Introductionmentioning

confidence: 99%

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Semi-Remote Gait Assistance Interface: A Joystick with Visual Feedback Capabilities for Therapists

Gomez-Vargas

et al. 2021

Sensors

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The constant growth of pathologies affecting human mobility has led to developing of different assistive devices to provide physical and cognitive assistance. Smart walkers are a particular type of these devices since they integrate navigation systems, path-following algorithms, and user interaction modules to ensure natural and intuitive interaction. Although these functionalities are often implemented in rehabilitation scenarios, there is a need to actively involve the healthcare professionals in the interaction loop while guaranteeing safety for them and patients. This work presents the validation of two visual feedback strategies for the teleoperation of a simulated robotic walker during an assisted navigation task. For this purpose, a group of 14 clinicians from the rehabilitation area formed the validation group. A simple path-following task was proposed, and the feedback strategies were assessed through the kinematic estimation error (KTE) and a usability survey. A KTE of 0.28 m was obtained for the feedback strategy on the joystick. Additionally, significant differences were found through a Mann–Whitney–Wilcoxon test for the perception of behavior and confidence towards the joystick according to the modes of interaction (p-values of 0.04 and 0.01, respectively). The use of visual feedback with this tool contributes to research areas such as remote management of therapies and monitoring rehabilitation of people’s mobility.

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Section: Results and Discussionmentioning

confidence: 99%

where the

value refers to the mean squared errors between the ideal and achieved paths, and the

Section: Materials and Methodsmentioning

confidence: 99%

Section: Quantitative Assessmentmentioning

confidence: 99%