Your browser doesn't support javascript.
loading
Unsupervised Gait Event Identification with a Single Wearable Accelerometer and/or Gyroscope: A Comparison of Methods across Running Speeds, Surfaces, and Foot Strike Patterns.
Kiernan, Dovin; Dunn Siino, Kristine; Hawkins, David A.
Affiliation
  • Kiernan D; Biomedical Engineering Graduate Group, University of California, Davis, Davis, CA 95616, USA.
  • Dunn Siino K; Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA 95616, USA.
  • Hawkins DA; Biomedical Engineering Graduate Group, University of California, Davis, Davis, CA 95616, USA.
Sensors (Basel) ; 23(11)2023 May 24.
Article in En | MEDLINE | ID: mdl-37299749
We evaluated 18 methods capable of identifying initial contact (IC) and terminal contact (TC) gait events during human running using data from a single wearable sensor on the shank or sacrum. We adapted or created code to automatically execute each method, then applied it to identify gait events from 74 runners across different foot strike angles, surfaces, and speeds. To quantify error, estimated gait events were compared to ground truth events from a time-synchronized force plate. Based on our findings, to identify gait events with a wearable on the shank, we recommend the Purcell or Fadillioglu method for IC (biases +17.4 and -24.3 ms; LOAs -96.8 to +131.6 and -137.0 to +88.4 ms) and the Purcell method for TC (bias +3.5 ms; LOAs -143.9 to +150.9 ms). To identify gait events with a wearable on the sacrum, we recommend the Auvinet or Reenalda method for IC (biases -30.4 and +29.0 ms; LOAs -149.2 to +88.5 and -83.3 to +141.3 ms) and the Auvinet method for TC (bias -2.8 ms; LOAs -152.7 to +147.2 ms). Finally, to identify the foot in contact with the ground when using a wearable on the sacrum, we recommend the Lee method (81.9% accuracy).
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Running / Wearable Electronic Devices Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Running / Wearable Electronic Devices Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Sensors (Basel) Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland