Conference Paper/Proceeding/Abstract 404 views 81 downloads
Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
Sara Sardari,
Bahareh Nakisa,
Sara Sharifzadeh
,
Alireza Daneshkhah,
Seng W. Loke,
Michael J. Duncan,
Matteo Crotti,
Vasile Palade
2024 IEEE Consumer Life Tech (ICLT), Pages: 1 - 6
Swansea University Author:
Sara Sharifzadeh
-
PDF | Accepted Manuscript
Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention).
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DOI (Published version): 10.1109/iclt63507.2024.11038644
Abstract
Online Deep Squat Evaluation: Leveraging Subject-Specific Adaptation and Information Retention
| Published in: | 2024 IEEE Consumer Life Tech (ICLT) |
|---|---|
| ISBN: | 979-8-3315-1934-6 979-8-3315-1933-9 |
| Published: |
IEEE
2025
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa68670 |
| Keywords: |
Metalearning, Continuing education, Adaptation models, Three-dimensional displays, Frequency modulation, Skeleton, Sensors, Quality assessment, Monitoring, Videos |
|---|---|
| College: |
Faculty of Science and Engineering |
| Funders: |
Co tutelle PhD funded between Coventry University and Deakin University, Australia |
| Start Page: |
1 |
| End Page: |
6 |

