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Joshua Carter
Mr
Doctor of Philosophy
,
Department for Health
Postgraduate Research Student
,
Department for Health
Centre for Health and Injury and Illness Prevention in Sport
Email
jc2369
bath.ac
uk
Overview
Fingerprint
Network
Projects
(1)
Research output
(9)
Datasets
(1)
Prizes
(3)
Similar Profiles
(12)
Research output
4
Chapter in a published conference proceeding
3
Article
1
Commissioned report
1
Abstract
Research output per year
Research output per year
3 results
Publication Year, Title
(descending)
Publication Year, Title
(ascending)
Title
Type
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Article
Search results
2024
Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions
Carter, J.
,
Chen, X.
,
Cazzola, D.
, Trewartha, G. &
Preatoni, E.
,
29 Aug 2024
,
In:
PeerJ.
12
,
8
, e17896.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
File
Deep Learning Method
100%
Machine Learning
50%
Learning System
50%
11
Downloads (Pure)
2023
Understanding the Role of Physical Activity on the Pathway from Intra-Articular Knee Injury to Post-Traumatic Osteoarthritis Disease in Young People: A Scoping Review Protocol
Morgan, K.
, Cowburn, J., Farrow, M.,
Carter, J.
,
Cazzola, D.
,
Walhin, J.-P.
&
McKay, C.
,
3 Mar 2023
,
In:
BMJ Open.
13
,
3
, e067147.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
Disease
100%
Physical Activity
100%
Osteoarthritis
100%
Comprehension
100%
Young People
100%
2022
A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology
Carter, J.
,
Rivadulla, A.
&
Preatoni, E.
,
20 Jan 2022
, (E-pub ahead of print)
In:
Sports Biomechanics.
p. 1-18
RSPB 2027509.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
File
Models
100%
Algorithm
100%
Wearable Sensor
100%
Support Vector Machine
100%
Sensor Data
100%
4
Citations (SciVal)
174
Downloads (Pure)