Abstract
This work proposes a smart phone video based approach for the estimation of blood glucose in a non-invasive way. Videos using smartphone camera are collected from the tip of the subject’s finger and the frames are subsequently converted into Photoplethysmography (PPG) waveform. Gaussian filter along with Asymmetric Least Square methods have been applied on the PPG signals to remove the high frequency noise, optical and motion interferences. Different signal features such as Systolic and Diastolic Peaks, the time difference between consecutive peaks (DelT), and First Derivative peaks have been extracted from the processed signal. Finally, Principal Component Regression (PCR) has been applied for the prediction of glucose level from the extracted features. The proposed model while applied to an unbiased dataset could predict the glucose level with a Standard Error of Prediction (SEP) of 18.31 mg/dL.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2019 6th International Conference on Networking, Systems and Security, NSysS 2019 |
| Publisher | Association for Computing Machinery |
| Pages | 104-108 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450376990 |
| DOIs | |
| State | Published - 17 Dec 2019 |
| Externally published | Yes |
| Event | 6th International Conference on Networking, Systems and Security, NSysS 2019 - Dhaka, Bangladesh Duration: 17 Dec 2019 → 19 Dec 2019 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 6th International Conference on Networking, Systems and Security, NSysS 2019 |
|---|---|
| Country/Territory | Bangladesh |
| City | Dhaka |
| Period | 17/12/19 → 19/12/19 |
Bibliographical note
Publisher Copyright:© 2019 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Blood Glucose
- PCR
- PPG
- Photoplethysmography
- Signal Processing
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
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