Machine Learning Groups Patients by Early Functional Improvement Likelihood Based on Wearable Sensor Instrumented Preoperative Timed-Up-and-Go Tests.

Journal: The Journal of arthroplasty
PMID: 31255408

Abstract

BACKGROUND: Wearable sensors permit efficient data collection and unobtrusive systems can be used for instrumenting knee patients for objective assessment. Machine learning can be leveraged to parse the abundant information these systems provide and segment patients into relevant groups without specifying group membership criteria. The objective of this study is to examine functional parameters influencing favorable recovery outcomes by separating patients into functional groups and tracking them through clinical follow-ups.

Authors

  • Riley A Bloomfield
    Department of Electrical & Computer Engineering, Western University, London, Ontario, Canada; Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.
  • Harley A Williams
    Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
  • Jordan S Broberg
    Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
  • Brent A Lanting
    Division of Orthopaedic Surgery, Department of Surgery, Schulich School of Medicine & Dentistry, Western University and London Health Sciences Centre, London, Ontario, Canada.
  • Kenneth A McIsaac
    Department of Electrical & Computer Engineering, Western University, London, Ontario, Canada.
  • Matthew G Teeter
    Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; Division of Orthopaedic Surgery, Department of Surgery, Schulich School of Medicine & Dentistry, Western University and London Health Sciences Centre, London, Ontario, Canada; Surgical Innovation Program, Lawson Health Research Institute, London, Ontario, Canada.

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