Name
Title | ||
|---|---|---|
Hidden Markov Model-Based Fall Detection With Motion Sensor Orientation Calibration: A Case for Real-Life Home Monitoring. |
Abstract | ||
|---|---|---|
Falls are a major threat for senior citizens' independent living. Motion sensor technologies and automatic fall detection systems have emerged as a reliable low-cost solution to this challenge. We develop a hidden Markov model (HMM) based fall detection system to detect falls automatically using a single motion sensor for real-life home monitoring scenarios. We propose a new representation for acc... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JBHI.2017.2782079 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Hidden Markov models,Signal detection,Feature extraction,Wearable sensors,Senior citizens,Injuries,Activity recognition | Computer vision,False alarm,Activity recognition,Pattern recognition,Detection theory,Computer science,Feature extraction,Feature engineering,Artificial intelligence,Acceleration,Hidden Markov model,Calibration | Journal |
Volume | Issue | ISSN |
22 | 6 | 2168-2194 |
Citations | PageRank | References |
6 | 0.51 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuo Yu | 1 | 68 | 13.95 |
| Hsinchun Chen | 2 | 9569 | 813.33 |
| Randall A Brown | 3 | 24 | 2.65 |