Name
Title | ||
|---|---|---|
A real-time and self-calibrating algorithm based on triaxial accelerometer signals for the detection of human posture and activity. |
Abstract | ||
|---|---|---|
Assessment of human activity and posture with triaxial accelerometers provides insightful information about the functional ability: classification of human activities in rehabilitation and elderly surveillance contexts has been already proposed in the literature. In the meanwhile, recent technological advances allow developing miniaturized wearable devices, integrated within garments, which may extend this assessment to novel tasks, such as real-time remote surveillance of workers and emergency operators intervening in harsh environments. We present an algorithm for human posture and activity-level detection, based on the real-time processing of the signals produced by one wearable triaxial accelerometer. The algorithm is independent of the sensor orientation with respect to the body. Furthermore, it associates to its outputs a "reliability" value, representing the classification quality, in order to launch reliable alarms only when effective dangerous conditions are detected. The system was tested on a customized device to estimate the computational resources needed for real-time functioning. Results exhibit an overall 96.2% accuracy when classifying both static and dynamic activities. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TITB.2010.2050696 | IEEE Transactions on Information Technology in Biomedicine |
Keywords | Field | DocType |
self-calibrating algorithm,triaxial accelerometer signal,real-time functioning,classification quality,triaxial accelerometers,wearable triaxial accelerometer,human activity,real-time remote surveillance,elderly surveillance context,human posture,wearable device,real-time processing,biomechanics,accelerometers,real time processing,real time,system testing,signal processing,geriatrics,clothing,calibration,classification,real time systems,signal detection,algorithms | Signal processing,Computer vision,Detection theory,Wearable computer,Accelerometer,Computer science,System testing,Algorithm,Artificial intelligence,Classifier (linguistics),Wearable technology,Calibration | Journal |
Volume | Issue | ISSN |
14 | 4 | 1558-0032 |
Citations | PageRank | References |
29 | 2.67 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Davide Curone | 1 | 58 | 5.38 |
| Gian Mario Bertolotti | 2 | 35 | 6.59 |
| Andrea Cristiani | 3 | 36 | 6.13 |
| Emanuele Lindo Secco | 4 | 71 | 10.43 |
| Giovanni Magenes | 5 | 268 | 54.05 |