Qualitative detection of motion by a moving observer
International Journal of Computer Vision
On Shortest Path Problems with "Non-Markovian" Link Contribution to Path Lengths
NETWORKING '00 Proceedings of the IFIP-TC6 / European Commission International Conference on Broadband Communications, High Performance Networking, and Performance of Communication Networks
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Robust Real-Time Face Detection
International Journal of Computer Vision
A wake-up detector for an acoustic surveillance sensor network: algorithm and VLSI implementation
Proceedings of the 3rd international symposium on Information processing in sensor networks
Analyzing features for activity recognition
Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
Invited Talk: Ultra Low Power Electronics for Medicine
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Lucid dreaming: reliable analog event detection for energy-constrained applications
Proceedings of the 6th international conference on Information processing in sensor networks
Algorithm to automatically detect abnormally long periods of inactivity in a home
Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments
Proceedings of the 5th international conference on Embedded networked sensor systems
A framework for the automated generation of power-efficient classifiers for embedded sensor nodes
Proceedings of the 5th international conference on Embedded networked sensor systems
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
IEEE Journal on Selected Areas in Communications - Special issue on body area networking: Technology and applications
A Low-Power, Battery-Free Tag for Body Sensor Networks
IEEE Pervasive Computing
Hibernets: energy-efficient sensor networks using analog signal processing
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Fast Template Matching Based on Normalized Cross Correlation with Centroid Bounding
ICMTMA '10 Proceedings of the 2010 International Conference on Measuring Technology and Mechatronics Automation - Volume 02
A practical approach to recognizing physical activities
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Cascade adaboost classifiers with stage optimization for face detection
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Hi-index | 0.00 |
Advances in technology have led to the development of wearable sensing, computing, and communication devices that can be woven into the physical environment of our daily lives, enabling a large variety of new applications in several domains, including wellness and health care. Despite their tremendous potential to impact our lives, wearable health monitoring systems face a number of hurdles to become a reality. The enabling processors and architectures demand a large amount of energy, requiring sizable batteries. In this article, we propose a granular decision-making architecture for physical movement monitoring applications. The module can be viewed as a tiered wake-up circuitry. This decision-making module, in combination with a low-power microcontroller, allows for significant power saving through an ultra low-power processing architecture. The significant power saving is achieved by performing a preliminary ultra low-power signal processing, and hence, keeping the microcontroller off when the incoming signal is not of interest. The preliminary signal processing is performed by a set of special-purpose functional units, also called screening blocks, that implement template matching functions. We formulate and solve an optimization problem for selecting screening blocks such that the accuracy requirements of the signal processing are accommodated while the total power is minimized. Our experimental results on real data from wearable motion sensors show that the proposed algorithm achieves 63.2% energy saving while maintaining a sensitivity of 94.3% in recognizing transitional actions.