Energy efficient system-on-chip architecture for non-invasive mobile monitoring of diabetics

Mohammad Alhawari, Ahsan Khandoker, Baker Mohammad, Hani Saleh, Kinda Khalaf, Mahmoud Al-Qutayri, Murat Kaya Yapici, Shakti Singh, Mohammed Ismail

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

This paper presents an integrated biomedical processor system consists of a biomedical processor chip, MEMS-based ECG and oximetry-based Glucose alert sensors to achieve a non-invasive home diagnostic health monitoring system for diabetics. The biomedical processor integrates various computational engines such as FFT core, CAN severity algorithm classification and wireless interface. The chip targets extremely low power consumption to enable battery-powered operation for extended period of time. The sensors will provide non-invasive monitoring of ECG signals, and blood glucose levels alert at the same physical location on the human body. The unique sensor platform inevitably drives the SoC architecture to be wearable and less intrusive; thereby, providing patients with constant feedback on their critical health parameters.

Original languageBritish English
Title of host publicationProceedings of the 2013 8th International Conference on Design and Technology of Integrated Systems in Nanoscale Era, DTIS 2013
Pages180-181
Number of pages2
DOIs
StatePublished - 2013
Event2013 8th International Conference on Design and Technology of Integrated Systems in Nanoscale Era, DTIS 2013 - Abu Dhabi, United Arab Emirates
Duration: 26 Mar 201328 Mar 2013

Publication series

NameProceedings of the 2013 8th International Conference on Design and Technology of Integrated Systems in Nanoscale Era, DTIS 2013

Conference

Conference2013 8th International Conference on Design and Technology of Integrated Systems in Nanoscale Era, DTIS 2013
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period26/03/1328/03/13

Keywords

  • CAN
  • ECG
  • micromachined sensor

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