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A Review on Human Motion Prediction in Sit to Stand and Lifting Tasks

[+] Author Affiliations
Erik A. Chumacero-Polanco, James Yang

Texas Tech University, Lubbock, TX

Paper No. DETC2016-59891, pp. V01AT02A066; 15 pages
doi:10.1115/DETC2016-59891
From:
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1A: 36th Computers and Information in Engineering Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5007-7
  • Copyright © 2016 by ASME

abstract

Human-like motion prediction and simulation is an important task with many applications in fields such as occupational-biomechanics, ergonomics in industrial engineering, study of biomechanical systems, prevention of musculoskeletal disorders, computer-graphics animation of articulated figures, prosthesis and exoskeletons design as well as design and control of humanoid robots, among others.

In an effort to get biomechanical insight in many human movements, extensive work has been conducted over the last decades on human-motion prediction of tasks as: walking, running, jumping, standing from a chair, reaching and lifting. This literature review is focused on the STS motion and the LLM. STS is defined as the process of rising from a chair to standing up position without losing stability balance, it is the most ubiquitous and torque-demanding daily labor and it is closely related to other capabilities of the human body. LLM is defined as the activity of raising a load, generally a box, from a low to a higher position while stability is maintained, this task produces a high number of incidences of low-back pain and injuries in many industrial and domestic activities.

In order to predict STS and LLM, two methods have been identified: these are the OBMG method and the CBMG method.

Copyright © 2016 by ASME

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