Power and size optimized multi-sensor context recognition platform

This paper presents a miniaturized low-power platform for real-time activity recognition. The wearable sensor system comprises of accelerometers, a microphone, a light sensor and signal processing units. The recognition is performed with low-power features and a decision tree classifier. Power measurements show that our 4.15/spl times/2.75 cm/sup 2/, 9 gram platform consumes less than 3 mW and can perform continuous classification and result transmission for 129 hours on a small lithium-polymer battery.