Simulation of Stand-to-Sit Biomechanics for Robotic Exoskeletons and Prostheses with Energy Regeneration

Brokoslaw Laschowski, Reza Sharif Razavian, John McPhee

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Previous studies of robotic exoskeletons and prostheses with regenerative actuators have focused on level-ground walking. Here we analyzed the lower-limb joint mechanical power during stand-to-sit movements using inverse dynamics to estimate the biomechanical energy available for electrical regeneration. Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were measured. Subject-specific body segment parameters were estimated using parameter identification. Joint mechanical power was calculated from joint torques and rotational velocities and numerically integrated over time to estimate the joint biomechanical energy. The hip absorbed the largest peak negative mechanical power (1.8 ± 0.5 W/kg), followed by the knee (0.8 ± 0.3 W/kg) and ankle (0.2 ± 0.1 W/kg). Negative mechanical work on the hip, knee, and ankle joints per stand-to-sit movement were 0.35 ± 0.06 J/kg, 0.15 ± 0.08 J/kg, and 0.02 ± 0.01 J/kg, respectively. Assuming known regenerative actuator efficiencies (i.e., maximum 63%), robotic exoskeletons and prostheses could regenerate 26 Joules of electrical energy while sitting down, compared to 19 Joules per walking stride. Given that these regeneration performance calculations are based on healthy young adults, future research should include seniors and/or rehabilitation patients to better estimate the biomechanical energy available for electrical regeneration.

Original languageEnglish (US)
Article number9351558
Pages (from-to)455-462
Number of pages8
JournalIEEE Transactions on Medical Robotics and Bionics
Volume3
Issue number2
DOIs
StatePublished - May 2021
Externally publishedYes

Keywords

  • Biomechanics
  • efficiency
  • exoskeletons
  • prosthetics
  • wearable robotics

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Optimization
  • Biomedical Engineering

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