Optimal design for symbiotic wearable wireless sensors

Priyanka Bagade, Ayan Banerjee, Sandeep Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Sensors aesthetically embedded in accessoriessuch as jewelry, piercings or contact lenses arebeing proposed recently. These symbiotic wearable wirelesssensors are envisioned to operate on scarce harvestedenergy resources from the human body. In addition tothe hardware and software constraints arising from theform-factor and low energy operations, there are safetyrequirements such as avoidance of physical injury. Thedesign implications of these requirements are non-intuitiveand may involve estimation of human physiological dynamics. The physical impact of a sensor operation canbe controlled by appropriate design of multiple sensorcomponents such as processor, radio, and optimization ofdata algorithm. For example, the risk of thermal injury totissue can be reduced by limiting the sensing frequency, the computation power, and the radio duty cycle of bodyworn sensor. Hence, it is a challenging task to trace backa cause of a physical impact to hardware and softwaredesign decisions in a sensor. This paper proposes a novelnon-linear optimization framework to consider safety andsustainability requirements that depend on the humanphysiology and derive system level design parameters of asensor. We demonstrate our methodology using three casestudies: a) continuously monitoring ECG sensor sustainedby body heat, b) thermally safe network of implantedsensors, and c) infusion pump control algorithm to avoidhypo-glycemia.

Original languageEnglish (US)
Title of host publicationProceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014
PublisherIEEE Computer Society
Pages132-137
Number of pages6
ISBN (Print)9781479949328
DOIs
StatePublished - 2014
Event11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014 - Zurich, Switzerland
Duration: Jun 16 2014Jun 19 2014

Other

Other11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014
CountrySwitzerland
CityZurich
Period6/16/146/19/14

Fingerprint

Sensors
Contact lenses
Hardware
Piercing
Electrocardiography
Optimal design
Pumps
Monitoring
Hot Temperature

Keywords

  • Body sensor network
  • safety
  • sustainability
  • wearable sensor design

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Hardware and Architecture

Cite this

Bagade, P., Banerjee, A., & Gupta, S. (2014). Optimal design for symbiotic wearable wireless sensors. In Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014 (pp. 132-137). [6855630] IEEE Computer Society. https://doi.org/10.1109/BSN.2014.31

Optimal design for symbiotic wearable wireless sensors. / Bagade, Priyanka; Banerjee, Ayan; Gupta, Sandeep.

Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014. IEEE Computer Society, 2014. p. 132-137 6855630.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bagade, P, Banerjee, A & Gupta, S 2014, Optimal design for symbiotic wearable wireless sensors. in Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014., 6855630, IEEE Computer Society, pp. 132-137, 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014, Zurich, Switzerland, 6/16/14. https://doi.org/10.1109/BSN.2014.31
Bagade P, Banerjee A, Gupta S. Optimal design for symbiotic wearable wireless sensors. In Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014. IEEE Computer Society. 2014. p. 132-137. 6855630 https://doi.org/10.1109/BSN.2014.31
Bagade, Priyanka ; Banerjee, Ayan ; Gupta, Sandeep. / Optimal design for symbiotic wearable wireless sensors. Proceedings - 11th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2014. IEEE Computer Society, 2014. pp. 132-137
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