Name
Title | ||
|---|---|---|
Sensor-Classifier Co-Optimization for Wearable Human Activity Recognition Applications |
Abstract | ||
|---|---|---|
Advances in integrated sensors and low-power electronics have led to an increase in the use of wearable devices for health and activity monitoring applications. These devices have severe limitations on weight, form-factor, and battery size since they have to be comfortable to wear. Therefore, they must minimize the total platform energy consumption while satisfying functionality (e.g., accuracy) and performance requirements. Optimizing the platform-level energy efficiency requires considering both the sensor and processing subsystems. To this end, this paper presents a sensor-classifier co-optimization technique with human activity recognition as a driver application. The proposed technique dynamically powers down the accelerometer sensors and controls their sampling rate as a function of the user activity. It leads to a 49% reduction in total platform energy consumption with less than 1% decrease in activity recognition accuracy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICESS.2019.8782506 | 2019 IEEE International Conference on Embedded Software and Systems (ICESS) |
Keywords | Field | DocType |
Wearable computing,human activity recognition,IoT,flexible hybrid electronics (FHE),health monitoring | Activity recognition,Efficient energy use,Wearable computer,Accelerometer,Computer science,Real-time computing,Electronics,Wearable technology,Battery (electricity),Energy consumption | Conference |
ISSN | ISBN | Citations |
2576-3504 | 978-1-7281-2438-4 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anish Nk | 1 | 0 | 0.68 |
| Ganapati Bhat | 2 | 50 | 11.95 |
| Jaehyun Park | 3 | 11 | 5.10 |
| Hyung Gyu Lee | 4 | 572 | 42.41 |
| Ümit Y. Ogras | 5 | 203 | 15.03 |