Name
Abstract | ||
|---|---|---|
In this preliminary work, we presented an effective and efficient algorithm on adaptive thresholds to automatically recognize falls from acceleration signals collected by a single tri-axial accelerometer in a mobile phone. Initial thresholds depend mainly on their carrying position of mobile phones, and then are adjusted automatically by a self-learning process and a classification module. Our researches are designed for carrying phones in casual ways which has not been done in previous researches. An android-based software is designed for experiments and the results show the efficiency of our method and improvements have been made on detection accuracy after having the learning process. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4304/jcp.9.7.1553-1559 | JOURNAL OF COMPUTERS |
Keywords | Field | DocType |
Accelerometer, fall detection, mobile phones, adaptive threshold | Android (operating system),Simulation,Computer science,Accelerometer,Real-time computing,Mobile device,Software,Acceleration,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
9 | 7 | 1796-203X |
Citations | PageRank | References |
2 | 0.42 | 4 |
Authors | ||
2 | ||