Name
Abstract | ||
|---|---|---|
This paper proposes a fall risk prediction system, which adopts two cameras and an AI server to obtain the images of the 3D human skeleton torso activities. We use the Hidden Markov model (HMM) for the movement changes of the joint points of the human skeleton torso in 3D space to evaluate the probability of falling of subjects. The experimental results show that the proposed system can efficientl... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCE50685.2021.9427640 | 2021 IEEE International Conference on Consumer Electronics (ICCE) |
Keywords | DocType | ISBN |
Artificial intelligence (AI),deep learning,fall risk prediction,rehabilitation,Hidden Markov model (HMM) | Conference | 978-1-7281-9766-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wan-Jung Chang | 1 | 0 | 1.69 |
| Liang-Bi Chen | 2 | 0 | 0.34 |
| Jian-Ping Su | 3 | 1 | 4.20 |
| Ming-Che Chen | 4 | 0 | 0.68 |
| Tzu-Chin Yang | 5 | 0 | 0.68 |