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Effect of sensor number and location on accelerometry-based vertical ground reaction force estimation during walking.
Pimentel, Ricky; Armitano-Lago, Cortney; MacPherson, Ryan; Sathyan, Anoop; Twiddy, Jack; Peterson, Kaila; Daniele, Michael; Kiefer, Adam W; Lobaton, Edgar; Pietrosimone, Brian; Franz, Jason R.
Afiliação
  • Pimentel R; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill & North Carolina State University, Chapel Hill & Raleigh, North Carolina, United States of America.
  • Armitano-Lago C; Department of Exercise & Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • MacPherson R; Department of Exercise & Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Sathyan A; Department of Aerospace Engineering, University of Cincinnati, Cincinnati, OH, United States of America.
  • Twiddy J; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill & North Carolina State University, Chapel Hill & Raleigh, North Carolina, United States of America.
  • Peterson K; Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.
  • Daniele M; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill & North Carolina State University, Chapel Hill & Raleigh, North Carolina, United States of America.
  • Kiefer AW; Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.
  • Lobaton E; Department of Exercise & Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Pietrosimone B; Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.
  • Franz JR; Department of Exercise & Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
PLOS Digit Health ; 3(5): e0000343, 2024 May.
Article em En | MEDLINE | ID: mdl-38743651
ABSTRACT
Knee osteoarthritis is a major cause of global disability and is a major cost for the healthcare system. Lower extremity loading is a determinant of knee osteoarthritis onset and progression; however, technology that assists rehabilitative clinicians in optimizing key metrics of lower extremity loading is significantly limited. The peak vertical component of the ground reaction force (vGRF) in the first 50% of stance is highly associated with biological and patient-reported outcomes linked to knee osteoarthritis symptoms. Monitoring and maintaining typical vGRF profiles may support healthy gait biomechanics and joint tissue loading to prevent the onset and progression of knee osteoarthritis. Yet, the optimal number of sensors and sensor placements for predicting accurate vGRF from accelerometry remains unknown. Our goals were to 1) determine how many sensors and what sensor locations yielded the most accurate vGRF loading peak estimates during walking; and 2) characterize how prescribing different loading conditions affected vGRF loading peak estimates. We asked 20 young adult participants to wear 5 accelerometers on their waist, shanks, and feet and walk on a force-instrumented treadmill during control and targeted biofeedback conditions prompting 5% underloading and overloading vGRFs. We trained and tested machine learning models to estimate vGRF from the various sensor accelerometer inputs and identified which combinations were most accurate. We found that a neural network using one accelerometer at the waist yielded the most accurate loading peak vGRF estimates during walking, with average errors of 4.4% body weight. The waist-only configuration was able to distinguish between control and overloading conditions prescribed using biofeedback, matching measured vGRF outcomes. Including foot or shank acceleration signals in the model reduced accuracy, particularly for the overloading condition. Our results suggest that a system designed to monitor changes in walking vGRF or to deploy targeted biofeedback may only need a single accelerometer located at the waist for healthy participants.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLOS Digit Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLOS Digit Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos