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

Functionality-power-packaging considerations in context aware wearable systems

ISSN:1617-4909ISSN:1617-4917ISSN:0949-205

On-body Activity Recognition in a Dynamic Sensor Network

Recognizing user activities using body-worn, miniaturized sensor nodes enables wearable computers to act contextaware. This paper describes how online activity recognition algorithms can be run on the SensorButton, our miniaturized wireless sensor platform. We present how the activity recognition algorithms have been optimized to be run online on our sensor platform, and how the execution can be distributed to the wireless sensor network. The resulting algorithm has been implemented as a custom, platform-specific executable as well as integrated into TinyOS. A comparison shows that the TinyOS executable is using about 7kB more code memory, while both implementations classify the activity in up to 18 classifications per second

Towards wearable autonomous microsystems, Pervasive Computing

Abstract. This paper presents our work towards a wearable autonomous microsystem for context recognition. The design process needs to take into account the properties ofa wearable environment in terms ofsensor 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 ofa microsystem consisting ofa 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 ofsuch a system. Additionally, we argue that a solar cell on top ofthe button – together with a lithium polymer battery as energy storage – is capable to power the system even for a user who works predominantly indoors.

From Sensors to Miniature Networked SensorButtons

Wearable computing aims to empower people by providing intelligence embedded within garments. It relies on sensors placed at different locations of the body. To foster useracceptance sensors should be small, light, and unobtrusive. In this paper we present a wearable platform that addresses those challenges: a miniature networked SensorButton with the form factor of a button, so that it can be integrated in garments in an unobtrusive way. It has several sensors used in wearable computing, on-board processing power, a wireless link for sensor networking or communication with a base station, and it focuses on low power consumption. We describe its use to recognize user activity and highlight the need for further research in poweraware algorithms for wearable computing