Abstract
The use of pervasive technologies to enable continuous patient monitoring and assessment in various setting outside of hospitals, lowering healthcare costs and allowing early detection of problems is discussed. A modified security system technology is a less obstructive alternative for home monitoring. Recent advances in wireless systems provide the basis for a realistic development and deployment of systems to support behavioral monitoring in multiperson homes. Statistical pattern-recognition and machine-learning algorithm integrate noisy and unreliable sensor data with the situation's context and dynamics. A hidden Markov Model can enhance the state estimation provided by modeling only the RSSI probabilities.
| Original language | English |
|---|---|
| Pages (from-to) | 36-43 |
| Number of pages | 8 |
| Journal | IEEE Pervasive Computing |
| Volume | 6 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2007 |
| Externally published | Yes |
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