A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance

Author:

Zhu Kefan1,Phan Phuoc Thien1,Sharma Bibhu1,Davies James1,Thai Mai Thanh12ORCID,Hoang Trung Thien1,Nguyen Chi Cong1ORCID,Ji Adrienne1,Nicotra Emanuele1,La Hung Manh3ORCID,Vo-Doan Tat Thang4ORCID,Phan Hoang-Phuong56ORCID,Lovell Nigel H.16ORCID,Do Thanh Nho16ORCID

Affiliation:

1. Graduate School of Biomedical Engineering, Faculty of Engineering, UNSW Sydney, Kensington Campus, Sydney, NSW 2052, Australia

2. College of Engineering and Computer Science, VinUniversity, Hanoi 100000, Vietnam

3. Advanced Robotics and Automation Lab, Computer Science and Engineering, University of Nevada, Reno, NV 89512, USA

4. School of Mechanical & Mining Engineering, The University of Queensland, St. Lucia, QLD 4072, Australia

5. School of Mechanical and Manufacturing Engineering, Faculty of Engineering, UNSW Sydney, Kensington Campus, Sydney, NSW 2052, Australia

6. Tyree Foundation Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW 2052, Australia

Abstract

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user’s comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user’s movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.

Funder

UNSW Scientia Fellowship

UNSW Start-up Grant

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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