Software module development for non-invasive blood glucose measurement using an ultra-wide band and machine learning

Minarul Islam, Chai Ly Min, Nusrat Jahan Shoumy, Md Shawkat Ali, Sabira Khatun, Mohamad Shaiful Abdul Karim, Bifta Sama Bari

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
22 Downloads (Pure)


Diabetes is a chronic disease and in uprising trend worldwide. There is no remedy, hence, blood glucose management is essential by screening blood glucose concentration levels (BGCL) regularly to maintain a healthy life. However, the present way of measuring BGCL is invasive by using a glucometer and drawing a blood sample directly from the human body. To overcome this discomfort-problem, a non-invasive device to measure BGCL is in demand. This paper presents an autonomous software module with a user-friendly graphical user interface (GUI) based on digital signal processing (DSP) and artificial neural network (ANN) to process, classify and recognize the BGL signature from captured ultra-wideband (UWB) signal through human blood medium. To capture the signal, a pair of UWB bio-antenna is placed in between the human earlobe. Received signals are captured and processed through GUI and undergo signal processing, ANN training, testing, and validation. An interface is developed to integrate the hardware (UWB transceiver, bio-antenna, etc.) and the developed software module to make a system. The initial system showed a consistent result with reliability and demonstrated 90.6% accuracy to detect the BGCL. The detection accuracy is 9.6% improved compared to existing work. Besides, this proposed system is cost-effective, user-friendly and suitable to be used by both doctors and home users.
Original languageEnglish
Article number052066
Pages (from-to)1-11
Number of pages11
JournalJournal of Physics: Conference Series
Issue number5
Publication statusPublished - 17 Jun 2020
Event2nd Joint International Conference on Emerging Computing Technology and Sports, JICETS 2019 - Bandung, Indonesia
Duration: 25 Nov 201927 Nov 2019


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