People lifting patterns—a reference dataset for practitioners

Konrad Kluwak, Ryszard Klempous, Zenon Chaczko, Jerzy W. Rozenblit, Marek Kulbacki

Research output: Contribution to journalArticlepeer-review

Abstract

Many health professionals do not use correct person transfer techniques in their daily practice. This results in damage to the paraspinal musculature over time, resulting in lower back pain and injuries. In this work, we propose an approach for the accurate multimodal measurement of people lifting and related motion patterns for ergonomic education regarding the application of correct patient transfer techniques. Several examples of person lifting were recorded and processed through accurate instrumentation and the well-defined measurements of kinematics, kinetics, surface electromyography of muscles as well as multicamera video. This resulted in a complete measurement protocol and unique reference datasets of correct and incorrect lifting schemes for caregivers and patients. This understanding of multimodal motion patterns provides insights for further independent investigations.

Original languageEnglish (US)
Article number3142
JournalSensors
Volume21
Issue number9
DOIs
StatePublished - May 1 2021

Keywords

  • Data processing tag detection
  • Decision support
  • Ergonomics in people lifting
  • Human motion dataset
  • Human motion lab
  • Motion analysis
  • Recommending systems
  • Tag detection

ASJC Scopus subject areas

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

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