Assessment of Rehabilitation Exercises from Depth Sensor Data-Reference-Cited by-同舟云学术

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Assessment of Rehabilitation Exercises from Depth Sensor Data

Published:2021-12-18 Issue: Volume: Page:
ISSN:
Container-title:2021 24th International Conference on Computer and Information Technology (ICCIT)
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Author:

Chowdhury Shehzan Haider,Amin Murshed Al,Rahman A K M Mahbubur,Amin M Ashraful,Ali Amin Ahsan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9689773/9689775/09689826.pdf?arnumber=9689826

Reference19 articles.

1. Spiking neural network classification for spike train analysis of physiotherapy movements

2. Gc-lstm: Graph convolution embedded lstm for dynamic link prediction;chen;arXiv preprint arXiv 1812 08942,2018

3. Short-Term Traffic Flow Prediction Based on Graph Convolutional Network Embedded LSTM

4. A Hybrid Deep Learning Approach with GCN and LSTM for Traffic Flow Prediction*

5. Exploring Visual Relationship for Image Captioning

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Technological advances in lower-limb tele-rehabilitation: A review of literature;Journal of Rehabilitation and Assistive Technologies Engineering;2024-01

2. Graph Transformer for Physical Rehabilitation Evaluation;2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG);2023-01-05

3. Assessing Human Motion During Exercise Using Machine Learning: A Literature Review;IEEE Access;2022

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