4.7 Article

sEMG-Triggered Fast Assistance Strategy for a Pneumatic Back Support Exoskeleton

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2022.3196361

Keywords

Muscles; Torque; Exoskeletons; Hip; Back; Actuators; Timing; Electromyography; human-robot interaction; pneumatic actuators; wearable robots

Funding

  1. Korea Medical Device Development Fund Grant through the Korea Government (Ministry of Science and ICT) [9991006863/KMDF_PR_20200901_0193]
  2. Korea Medical Device Development Fund Grant through the Korea Government (Ministry of Trade, Industry and Energy) [9991006863/KMDF_PR_20200901_0193]
  3. Korea Medical Device Development Fund Grant through the Korea Government (Ministry of Health Welfare) [9991006863/KMDF_PR_20200901_0193]
  4. Korea Medical Device Development Fund Grant through the Korea Government (Ministry of Food and Drug Safety) [9991006863/KMDF_PR_20200901_0193]

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To prevent lower back pain in the industrial workplace, various powered back support exoskeletons have been developed. However, conventional kinematics-triggered assistance strategies induce latency, degrading assistance efficiency. Therefore, a surface electromyography-triggered assistance strategy was proposed and experimentally evaluated, showing improved assistance efficiency and particular benefits in heavy external load situations.
To prevent lower back pain (LBP) in the industrial workplace, various powered back support exoskeletons (BSEs) have been developed. However, conventional kinematics-triggered assistance (KA) strategies induce latency, degrading assistance efficiency. Therefore, we proposed and experimentally evaluated a surface electromyography (sEMG)-triggered assistance (EA) strategy. Nine healthy subjects participated in the lifting experiments: 1) external loads test, 2) extra latency test, and 3) repetitive lifting test. In the external loads test, subject performed lifting with four different external loads (0 kg, 7.5 kg, 15 kg, and 22.5 kg). The assistance was triggered earlier by EA compared to KA from 114 ms to 202 ms, 163 ms to 269 ms for squat and stoop lifting respectively, as external loads increased from 0 kg to 22.5 kg. In the extra latency test, the effects of extra latency (manual switch, 0 ms, 100 ms and 200 ms) in EA on muscle activities were investigated. Muscle activities were minimized in the fast assistance (0 ms and 100 ms) condition and increased with extra latency. In the repetitive lifting test, the EA strategy significantly reduced L1 muscle fatigue by 70.4% in stoop lifting, compared to KA strategy. Based on the experimental results, we concluded that fast assistance triggered by sEMG improved assistance efficiency in BSE and was particularly beneficial in heavy external loads situations. The proposed assistive strategy can be used to prevent LBP by reducing back muscle fatigue and is easily applicable to various industrial exoskeleton applications.

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