Torso-Based Control Interface for Standing Mobility-Assistive Devices

Wheelchairs and mobility devices have transformed our bodies into cybernic systems, enhancing our well-being by enabling individuals with reduced mobility to regain freedom. Notwithstanding, current interfaces of control primarily rely on hand operation, therefore constraining the user from performing functional activities of daily living. In this work, we propose a design of a torso-based control interface with compliant coupling support for standing mobility assistive devices. We consider the coupling between the human and robot in the interface design. The design includes a compliant support mechanism and mapping between the body movement space and the velocity space. We present experiments including multiple conditions, with a joystick for comparison with the proposed torso control interface. The results of a path-following experiment demonstrated that users could control the device naturally using the hands-free interface, and the performance was comparable with the joystick, with 10% more consumed time, an average cross error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 0.116\text{ m}$</tex-math></inline-formula> and 4.9% less average acceleration. In an object-transferring experiment, the proposed interface demonstrated a clear advantage when users needed to manipulate objects during locomotion. Lastly, the torso control scored 15% less than the joystick on the system usability scale for the path-following task but 3.3% more for the object-transferring task.

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Institutions

Publication Details

Journal
IEEE/ASME Transactions on Mechatronics
Published
2024-11-15
DOI
https://doi.org/10.1109/tmech.2024.3487905
Citations
1
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.25

Funders

Controls
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article

Torso-Based Control Interface for Standing Mobility-Assistive Devices

Modar Hassan, Diego Páez-Granados, Yang Chen, Kenji Suzuki
1 citations
IEEE/ASME Transactions on Mechatronics
Context-Aware Activity Recognition Systems
0.25
article

Torso-Based Control Interface for Standing Mobility-Assistive Devices

Modar Hassan, Diego Páez-Granados, Yang Chen, Kenji Suzuki
article en
1 citations

Abstract

Wheelchairs and mobility devices have transformed our bodies into cybernic systems, enhancing our well-being by enabling individuals with reduced mobility to regain freedom. Notwithstanding, current interfaces of control primarily rely on hand operation, therefore constraining the user from performing functional activities of daily living. In this work, we propose a design of a torso-based control interface with compliant coupling support for standing mobility assistive devices. We consider the coupling between the human and robot in the interface design. The design includes a compliant support mechanism and mapping between the body movement space and the velocity space. We present experiments including multiple conditions, with a joystick for comparison with the proposed torso control interface. The results of a path-following experiment demonstrated that users could control the device naturally using the hands-free interface, and the performance was comparable with the joystick, with 10% more consumed time, an average cross error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 0.116\text{ m}$</tex-math></inline-formula> and 4.9% less average acceleration. In an object-transferring experiment, the proposed interface demonstrated a clear advantage when users needed to manipulate objects during locomotion. Lastly, the torso control scored 15% less than the joystick on the system usability scale for the path-following task but 3.3% more for the object-transferring task.

IEEE/ASME Transactions on MechatronicsVol. 30(5)
University of Tsukuba (JP), ETH Zurich (CH), Swiss Paraplegic Research (CH)
Ministry of Education, Culture, Sports, Science and Technology
Affordable and clean energy
Openalex Percentile: Top 45%
Context-Aware Activity Recognition Systems
0.25
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