148 related articles for article (PubMed ID: 32854288)
1. Recognition and Repetition Counting for Local Muscular Endurance Exercises in Exercise-Based Rehabilitation: A Comparative Study Using Artificial Intelligence Models.
Prabhu G; O'Connor NE; Moran K
Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32854288
[TBL] [Abstract][Full Text] [Related]
2. Deep Learning for Sensor-Based Rehabilitation Exercise Recognition and Evaluation.
Zhu ZA; Lu YC; You CH; Chiang CK
Sensors (Basel); 2019 Feb; 19(4):. PubMed ID: 30791648
[TBL] [Abstract][Full Text] [Related]
3. Assessing Physical Rehabilitation Exercises using Graph Convolutional Network with Self-supervised regularization.
Du C; Graham S; Depp C; Nguyen T
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():281-285. PubMed ID: 34891291
[TBL] [Abstract][Full Text] [Related]
4. Recognition and Repetition Counting for ComplexPhysical Exercises with Deep Learning.
Soro A; Brunner G; Tanner S; Wattenhofer R
Sensors (Basel); 2019 Feb; 19(3):. PubMed ID: 30744158
[TBL] [Abstract][Full Text] [Related]
5. Enhancing automated lower limb rehabilitation exercise task recognition through multi-sensor data fusion in tele-rehabilitation.
Ettefagh A; Roshan Fekr A
Biomed Eng Online; 2024 Mar; 23(1):35. PubMed ID: 38504279
[TBL] [Abstract][Full Text] [Related]
6. Graph Convolutional Networks for Assessment of Physical Rehabilitation Exercises.
Deb S; Islam MF; Rahman S; Rahman S
IEEE Trans Neural Syst Rehabil Eng; 2022; 30():410-419. PubMed ID: 35139022
[TBL] [Abstract][Full Text] [Related]
7. Deep learning model for classifying shoulder pain rehabilitation exercises using IMU sensor.
Lee K; Kim JH; Hong H; Jeong Y; Ryu H; Kim H; Lee SU
J Neuroeng Rehabil; 2024 Mar; 21(1):42. PubMed ID: 38539223
[TBL] [Abstract][Full Text] [Related]
8. White blood cells detection and classification based on regional convolutional neural networks.
Kutlu H; Avci E; Özyurt F
Med Hypotheses; 2020 Feb; 135():109472. PubMed ID: 31760248
[TBL] [Abstract][Full Text] [Related]
9. AIoT-Enabled Rehabilitation Recognition System-Exemplified by Hybrid Lower-Limb Exercises.
Lai YC; Kan YC; Lin YC; Lin HC
Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300501
[TBL] [Abstract][Full Text] [Related]
10. Computer Vision Based on a Modular Neural Network for Automatic Assessment of Physical Therapy Rehabilitation Activities.
Francisco JA; Rodrigues PS
IEEE Trans Neural Syst Rehabil Eng; 2023; 31():2174-2183. PubMed ID: 36459598
[TBL] [Abstract][Full Text] [Related]
11. Analysis of the role and robustness of artificial intelligence in commodity image recognition under deep learning neural network.
Chen R; Wang M; Lai Y
PLoS One; 2020; 15(7):e0235783. PubMed ID: 32634167
[TBL] [Abstract][Full Text] [Related]
12. Automatic Assessment of Functional Movement Screening Exercises with Deep Learning Architectures.
Spilz A; Munz M
Sensors (Basel); 2022 Dec; 23(1):. PubMed ID: 36616604
[TBL] [Abstract][Full Text] [Related]
13. CNN Multi-Position Wearable Sensor Human Activity Recognition Used in Basketball Training.
Tang B; Guan W
Comput Intell Neurosci; 2022; 2022():9918143. PubMed ID: 36172312
[TBL] [Abstract][Full Text] [Related]
14. Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms.
Czekaj Ł; Kowalewski M; Domaszewicz J; Kitłowski R; Szwoch M; Duch W
Sensors (Basel); 2024 Jun; 24(12):. PubMed ID: 38931675
[TBL] [Abstract][Full Text] [Related]
15. Development and Clinical Evaluation of a Web-Based Upper Limb Home Rehabilitation System Using a Smartwatch and Machine Learning Model for Chronic Stroke Survivors: Prospective Comparative Study.
Chae SH; Kim Y; Lee KS; Park HS
JMIR Mhealth Uhealth; 2020 Jul; 8(7):e17216. PubMed ID: 32480361
[TBL] [Abstract][Full Text] [Related]
16. Sensor-Based Human Activity Recognition Using Adaptive Class Hierarchy.
Kondo K; Hasegawa T
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833819
[TBL] [Abstract][Full Text] [Related]
17. A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.
Espinosa R; Ponce H; Gutiérrez S; Martínez-Villaseñor L; Brieva J; Moya-Albor E
Comput Biol Med; 2019 Dec; 115():103520. PubMed ID: 31698242
[TBL] [Abstract][Full Text] [Related]
18. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.
Vu H; Kim HC; Jung M; Lee JH
Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633
[TBL] [Abstract][Full Text] [Related]
19. An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.
Nasri N; Orts-Escolano S; Cazorla M
Sensors (Basel); 2020 Nov; 20(22):. PubMed ID: 33198083
[TBL] [Abstract][Full Text] [Related]
20. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]