Nagendra Bhargava Bharatula

Towards Wearable Autonomous Microsystems

This paper presents our work towards a wearable autonomous microsystem for context recognition. The design process needs to take into account the properties of a wearable environment in terms of sensor placement for data extraction, energy harvesting, comfort and easy integration into clothes and accessories. We suggest to encapsulate the system in an embroidery or a button. The study of a microsystem consisting of a light sensor, a microphone, an accelerometer, a microprocessor and a RF transceiver shows that it is feasible to integrate such a system in a button-like form of 12 mm diameter and 4 mm thickness. We discuss packaging and assembly aspects of such a system. Additionally, we argue that a solar cell on top of the button – together with a lithium polymer battery as energy storage – is capable to power the system even for a user who works predominantly indoors.

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.

Functionality-power-packaging considerations in context aware wearable systems

Wearable computing places tighter constraints on architecture design than traditional mobile computing. The architecture is described in terms of miniaturization, power-awareness, global low-power design and suitability for an application. In this article we present a new methodology based on three different system properties. Functionality, power and electronic Packaging metrics are proposed and evaluated to study different trade offs. We analyze the trade offs in different context recognition scenarios. The proof of concept case study is analyzed by studying (a) interaction with household appliances by a wrist worn device (acceleration, light sensors) (b) studying walking behavior with acceleration sensors, (c) computational task and (d) gesture recognition in a wood-workshop using the combination of accelerometer and microphone sensors. After analyzing the case study, we highlight the size aspect by electronic packaging for a given functionality and present the miniaturization trends for ‘autonomous sensor button’.

Hybrid micropower supply for wearable-pervasive sensor nodes

This article presents an architecture of hybrid micro power supply for wearable-pervasive sensor nodes. A lithium-ion button battery and a photo voltaic module with efficient power management circuitry are implemented as a miniaturised system. The performance was investigated in an office worker scenario with real-time power consumption measurements. It is shown that overall system efficiency in terms of battery life, low power dissipation and suitability for integration into a sensory system are highly improved. The measured power efficiencies in well-lit indoors and outdoors were reported to be in the range of 91-95%.

On-Body Context Recognition with Miniaturized Autonomous Sensor Button (Situationserkennung mit am Körper getragenen autonomen Minisensoren)

The vision of wearable computing is a personal mobile system that is always “on” and always useful and unobtrusive. In this article we present the on-body context recognition analysis considering the functionality or recognition performance, power, and packaging. Interaction with household appliances using a wrist worn “autonomous sensor button” is analyzed as a case study. An overall on-line recognition performance between 85 and 91% is reported. The measured power consumption of the sensor button at 10% duty cycle is around 500 μW. The power profiling in an office worker daily life scenario shows that its possible to achieve autonomous operation by a solar cell having an area of 40cm2 Die Vision eines tragbaren Computers besteht aus einem PDA, der ständig eingeschaltet, ständig nutzbringend und trotzdem nicht aufdringlich ist. In diesem Beitrag stellen wir ein System zur Situationserkennung vor und betrachten Funktionalität, Erkennungsqualität, Leistungsverbrauch und Gehäusung. Das Zusammenwirken mit Hausgeräten, unter Verwendung eines am Handgelenk getragenen autonomen Sensorknopfes, wird als Fallstudie behandelt. Eine Gesamt-Online-Erkennungsrate zwischen 85 und 91% wird erreicht. Der gemessene Leistungsverbrauch eines Sensorknopfes beträgt bei einem Tastverhältnis von 10% etwa 500 μW. Das Leistungsprofil in einem für Büroangestellte üblichen Szenario zeigt, dass es möglich ist, einen autonomen Betrieb mit einer Solarzellenfläche von 40 cm2 sicherzustellen.

Maximum Power Point Tracking (MPPT) for on-body Context Systems

In this article we present the use of MPPT (maximum- power-point-tracking) for miniaturized on-body activity recognition systems. We evaluate different solar cells and apply MPPT to study the suitability for on-line activity systems. With a wrist worn solar cell, MPPT allows us to track power levels of 1.35 mW for indoors/wood-workshop lighting and 7.21 mW during dull outdoor lighting conditions. The overall efficiency of the proposed technique is 96% in the best-case scenario and 80% in the worst-case.