Optimization of Brain Mobile Interface Applications Using IoT

Koosha Sadeghi, Ayan Banerjee, Javad Sohankar, Sandeep Gupta

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

9 Citations (Scopus)

Abstract

Pervasive Brain Mobile Interfaces (BMoI) can be made more accurate and time efficient when knowledge from other sensors and computation power from available devices in the Internet of Things (IoT) infrastructure are utilized. This paper takes the example of Neuro-Movie (nMovie), an interactive movie application that blurs movie scenes based on mental state, to illustrate and analyze optimization opportunities when BMoI is interfaced with IoT. The three way trade-off between accuracy, real-time operation, and energy efficiency can be optimized through usage of physiological responses from IoT sensors and prediction algorithms. Latency and power models of BMoI are developed for thorough analysis of the trade-offs. Experiments on 10 volunteers show that: a) utilizing electrocardiogram responses to psychological stimulus increases the accuracy of mental state recognition by almost 10%, b) predictive models cover computation and communication latencies in the system to satisfy real-time requirements, and c) use of predictive models allows duty cycling of smartphone WiFi that potentially saves upto 71.6% communication energy.

Original languageEnglish (US)
Title of host publicationProceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-41
Number of pages10
ISBN (Electronic)9781509054114
DOIs
StatePublished - Feb 1 2017
Event23rd IEEE International Conference on High Performance Computing, HiPC 2016 - Hyderabad, India
Duration: Dec 19 2016Dec 22 2016

Other

Other23rd IEEE International Conference on High Performance Computing, HiPC 2016
CountryIndia
CityHyderabad
Period12/19/1612/22/16

Fingerprint

Brain
Smartphones
Communication
Sensors
Electrocardiography
Energy efficiency
Internet of things
Experiments

Keywords

  • brain-mobile interface
  • interactive movies
  • Internet-of-things
  • multi-modal sensing
  • pervasive systems

ASJC Scopus subject areas

  • Hardware and Architecture

Cite this

Sadeghi, K., Banerjee, A., Sohankar, J., & Gupta, S. (2017). Optimization of Brain Mobile Interface Applications Using IoT. In Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016 (pp. 32-41). [7839667] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HiPC.2016.014

Optimization of Brain Mobile Interface Applications Using IoT. / Sadeghi, Koosha; Banerjee, Ayan; Sohankar, Javad; Gupta, Sandeep.

Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 32-41 7839667.

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

Sadeghi, K, Banerjee, A, Sohankar, J & Gupta, S 2017, Optimization of Brain Mobile Interface Applications Using IoT. in Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016., 7839667, Institute of Electrical and Electronics Engineers Inc., pp. 32-41, 23rd IEEE International Conference on High Performance Computing, HiPC 2016, Hyderabad, India, 12/19/16. https://doi.org/10.1109/HiPC.2016.014
Sadeghi K, Banerjee A, Sohankar J, Gupta S. Optimization of Brain Mobile Interface Applications Using IoT. In Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 32-41. 7839667 https://doi.org/10.1109/HiPC.2016.014
Sadeghi, Koosha ; Banerjee, Ayan ; Sohankar, Javad ; Gupta, Sandeep. / Optimization of Brain Mobile Interface Applications Using IoT. Proceedings - 23rd IEEE International Conference on High Performance Computing, HiPC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 32-41
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