Abstract

Despite the phenomenal advances in the computational power of electronic systems, human-machine interaction has been largely limited to simple control panels, such as keyboards and mice, which only use physical senses. Consequently, these systems either rely critically on close human guidance or operate almost independently. A richer experience can be achieved if cognitive inputs are used in addition to the physical senses. Towards this end, this paper introduces a simple wearable system that consists of a motion processing unit and brain-machine interface. We show that our system can successfully employ cognitive indicators to predict human activity.

Original languageEnglish (US)
Title of host publicationConference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
PublisherIEEE Computer Society
Pages846-850
Number of pages5
ISBN (Electronic)9781538639542
DOIs
StatePublished - Mar 1 2017
Event50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States
Duration: Nov 6 2016Nov 9 2016

Other

Other50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
CountryUnited States
CityPacific Grove
Period11/6/1611/9/16

Fingerprint

Man machine systems
Decoding
Brain
Sensors
Processing

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Geyik, C. S., Dutta, A., Ogras, U., & Bliss, D. (2017). Decoding human intent using a wearable system and multi-modal sensor data. In Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 (pp. 846-850). [7869168] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2016.7869168

Decoding human intent using a wearable system and multi-modal sensor data. / Geyik, Cemil S.; Dutta, Arindam; Ogras, Umit; Bliss, Daniel.

Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016. IEEE Computer Society, 2017. p. 846-850 7869168.

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

Geyik, CS, Dutta, A, Ogras, U & Bliss, D 2017, Decoding human intent using a wearable system and multi-modal sensor data. in Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016., 7869168, IEEE Computer Society, pp. 846-850, 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016, Pacific Grove, United States, 11/6/16. https://doi.org/10.1109/ACSSC.2016.7869168
Geyik CS, Dutta A, Ogras U, Bliss D. Decoding human intent using a wearable system and multi-modal sensor data. In Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016. IEEE Computer Society. 2017. p. 846-850. 7869168 https://doi.org/10.1109/ACSSC.2016.7869168
Geyik, Cemil S. ; Dutta, Arindam ; Ogras, Umit ; Bliss, Daniel. / Decoding human intent using a wearable system and multi-modal sensor data. Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016. IEEE Computer Society, 2017. pp. 846-850
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