Power and Size Optimized Multi-Sensor Context Recognition Platform

Bharatula, Nagendra Bhargava; Stäger, Mathias; Lukowicz, Paul; Tröster, Gerhard

doi:10.1109/iswc.2005.42

Cited by 14 publications

(9 citation statements)

References 4 publications

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“…It evaluates multiple feature sets and makes the tradeoff between power consumption and recognition accuracy. A system that classifies household activities in realtime with a focus on low power consumption is presented in [3].…”

Section: Figure 1 Ewatch Sensing Platformmentioning

confidence: 99%

Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions

Maurer¹,

Smailagic²,

Siewiorek³

et al. 2006

279

174

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Section: Figure 1 Ewatch Sensing Platformmentioning

confidence: 99%

Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions

Maurer¹,

Smailagic²,

Siewiorek³

et al. 2006

279

174

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show abstract

“…'Electronic Textiles' [11] uses a conductive thread with insulator coating for horizontal and vertical directions as well as an insulator thread. The devices are attached at the cross point of the horizontal and vertical conductive threads in order to form the electronic circuit.…”

Section: Related Work On Wearable Network Systemmentioning

confidence: 99%

Wearable electromyography measurement system using cable-free network system on conductive fabric

Akita

Shinmura

Shimamoto

et al. 2008

Artificial Intelligence in Medicine

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SummaryObjective: To solve the complicated wires and battery maintainance problems in the application of werarable computing for biomedical monitoring, the electromyography (EMG) measurement system using conductive fabric for power supply and electric shield for noise reduction is proposed.Material and Methods: The basic cable-free network system using conductive fabric, named as "TextileNet" is developed. The conductive fabric has the function of electic shield for noise reduction in EMG measurement, and it enables the precise EMG measurement with wearable system.Results: The specifications of the developed prototype TextileNet system using wear with conductive fabric were communication speed of 9600 bit per second and power supply of 3W for each device. The electric shield effect was evaluated for precise EMG measurement, and the shield efficacy of conductive fabric was estimated as high as that of shield room.Conclusions: TextileNet system solves both the problems of complicated wires and battery maintainance in wearable computing systems. Conductive fabric * Phone: +81-76-234-4864, FAX:+81-76-264-6404, E-mail:akita@is.t.kanazawau.ac.jp Preprint submitted to Elsevier 24 November 2007 used in TextileNet system is also effective for precise EMG measurement as electric shield. The combination of TextileNet system and EMG measurement device will implement the cable-free, battery-free wearable EMG measurement system.

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“…This vision implies that the sensor nodes should be extremely small and consume so little power that no power source change is required for several years or months. Working towards this vision, the previous work of our group has dealt with issues such as: activity recognition using low-power features and classifier algorithms [4; 5]; optimization of power and size in a multi-sensor context recognition platform [6]; development of micro hybrid power supply to achieve autonomous behaviour [7]; electronic packaging aspects of an ultra miniaturized sensor button [8]; and architectural tradeoffs in wearable systems [9]. A figure of merit to study the design trade offs by three metrics; functionality (depends on the recognition performance), power consumption, and electronic packaging is also proposed [10].…”

Section: Related Workpaper Scopementioning

confidence: 99%

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

Bharatula¹,

Tröster²

2007

Teme

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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 it's possible to achieve autonomous operation by a solar cell having an area of 40 cm 2 . Situationserkennung mit am Körper getragenen autonomen MinisensorenDie 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 cm 2 sicherzustellen.

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Power and Size Optimized Multi-Sensor Context Recognition Platform

Cited by 14 publications

References 4 publications

Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions

Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions

Wearable electromyography measurement system using cable-free network system on conductive fabric

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

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