A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology-Reference-Cited by-同舟云学术

A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology

Published:2022-01-20 Issue: Volume: Page:1-18
ISSN:1476-3141
Container-title:Sports Biomechanics
language:en
Short-container-title:Sports Biomechanics

Author:

Carter Joshua Autton¹^ORCID,Rivadulla Adrian Rodriguez¹^ORCID,Preatoni Ezio¹^ORCID

Affiliation:

1. Department for Health, University of Bath, Bath, UK

Funder

there is no funding

Publisher

Informa UK Limited

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Orthopedics and Sports Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/14763141.2022.2027509

Reference34 articles.

1. The metabolic cost of human running: is swinging the arms worth it?

2. Classifying running speed conditions using a single wearable sensor: Optimal segmentation and feature extraction methods

3. Automated Accelerometer-Based Gait Event Detection During Multiple Running Conditions

4. The effect of three surface conditions, speed and running experience on vertical acceleration of the tibia during running

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