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Page 1
Determining Stroke and Movement Profiles in Competitive Tennis Match-Play From Wearable Sensor Accelerometry.
J Strength Cond Res. 2023 Jun 1;37(6):1271-1276. doi: 10.1519/JSC.0000000000004283. Epub 2023 Apr 6.
J Strength Cond Res. 2023.
PMID: 35916877
Prototype Machine Learning Algorithms from Wearable Technology to Detect Tennis Stroke and Movement Actions.
Perri T, Reid M, Murphy A, Howle K, Duffield R.
Perri T, et al.
Sensors (Basel). 2022 Nov 16;22(22):8868. doi: 10.3390/s22228868.
Sensors (Basel). 2022.
PMID: 36433462
Free PMC article.
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Competition scheduling patterns of emerging elite players in professional men's tennis.
Perri T, Duffield R, Murphy A, Mabon T, Reid M.
Perri T, et al.
J Sports Sci. 2021 Sep;39(18):2087-2094. doi: 10.1080/02640414.2021.1918431. Epub 2021 Apr 23.
J Sports Sci. 2021.
PMID: 33890556
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Validating an algorithm from a trunk-mounted wearable sensor for detecting stroke events in tennis.
Perri T, Reid M, Murphy A, Howle K, Duffield R.
Perri T, et al.
J Sports Sci. 2022 May;40(10):1168-1174. doi: 10.1080/02640414.2022.2056365. Epub 2022 Mar 23.
J Sports Sci. 2022.
PMID: 35318889
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Differentiating Stroke and Movement Accelerometer Profiles to Improve Prescription of Tennis Training Drills.
Perri T, Reid M, Murphy A, Howle K, Duffield R.
Perri T, et al.
J Strength Cond Res. 2023 Mar 1;37(3):646-651. doi: 10.1519/JSC.0000000000004318. Epub 2022 Sep 8.
J Strength Cond Res. 2023.
PMID: 36165877
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