Name
Abstract | ||
|---|---|---|
The rehabilitation treatment is important because it helps a patient restore physical sensory and mental capabilities. The patient whose symptoms are moderately relieved, or outpatient, usually rehabilitate the individual alone. Improper exercise or posture can slow the recovery of the patient or even worsen the patient's health status when doing rehabilitation exercise alone. The best way is to receive home visiting treatment from professional therapist until cured. However, such way is a burden on the patient in terms of cost. This paper proposes the novel model that corrects the improper postures of the patient when having rehabilitating exercise alone. We use Microsoft Kinect to recognize the posture of the patient by extracting the human skeleton. We will adopt deep neural network to analyze the extracted human skeleton, in order to determine whether the posture is correct or not. The data for training our model will be correct postures and incorrect postures and detailed data collection plan is provided in this paper. The implementation and experiment will be performed in the future work. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/BIGCOMP.2017.7881743 | 2017 IEEE International Conference on Big Data and Smart Computing (BigComp) |
Keywords | Field | DocType |
posture recognition,rehabilitation,deep neural network | Rehabilitation,Data collection,Rehabilitation exercise,Simulation,Computer science,Posture correction,Human skeleton,Physical medicine and rehabilitation,Artificial neural network | Conference |
ISSN | ISBN | Citations |
2375-933X | 978-1-5090-3016-3 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seung Ho Han | 1 | 11 | 5.52 |
| Han-Gyu Kim | 2 | 9 | 6.43 |
| Ho-Jin Choi | 3 | 280 | 53.61 |