Name
Title | ||
|---|---|---|
Sensor Based Monitoring for People with Dementia: Searching for Movement Markers in Alzheimer's Disease for a Early Diagnostic. |
Abstract | ||
|---|---|---|
We report on first results of using motion pattern behaviour as a possible diagnostics marker for detection and prediction of alzheimer diseases. We observed elderly subjects with and without dementia and recorded their motion behaviour with mobile sensors for 3 days. Additionally, we analyzed the sensor data offline and used probabilistic models (Hierarchical Hidden Markov Models) to differentiate between healthy subjects and subjects suffering form the disease. Our first results with 32 subjects achieve an accuracy of 91 percent. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-31479-7_21 | Communications in Computer and Information Science |
Keywords | Field | DocType |
accelerometer,dementia,hidden markov model | Computer vision,Disease,Accelerometer,Computer science,Artificial intelligence,Probabilistic logic,Hidden Markov model,Machine learning,Dementia | Conference |
Volume | ISSN | Citations |
277 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| André Hoffmeyer | 1 | 8 | 1.32 |
| Kristina Yordanova | 2 | 70 | 15.22 |
| Stefan J Teipel | 3 | 141 | 10.13 |
| Thomas Kirste | 4 | 93 | 18.37 |