NDLI: Joint empirical mode decomposition, exponential function estimation and L 1 norm approach for estimating mean value of photoplethysmogram and blood glucose level

Please wait, while we are loading the content...

Joint empirical mode decomposition, exponential function estimation and L 1 norm approach for estimating mean value of photoplethysmogram and blood glucose level

Near orthogonal discrete quaternion Fourier transform components via an optimal frequency rescaling approach

Review of noise removal techniques in ECG signals

Sequential covariance intersection-based Kalman consensus filter with intermittent observations

Sparse distributed learning based on diffusion minimum generalised rank norm

Two-stage spoken term detection system for under-resourced languages

Volume 14 (2020) : Issue 8, Oct

Volume 14 (2020) : Issue 7, Sep

Volume 14 (2020) : Issue 6, Aug

Volume 14 (2020) : Issue 5, Jul

Volume 14 (2020) : Issue 4, Jun

Volume 14 (2020) : Issue 3, May

Volume 14 (2020) : Issue 2, Apr

Volume 14 (2020) : Issue 1, Feb

IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Joint empirical mode decomposition, exponential function estimation and L 1 norm approach for estimating mean value of photoplethysmogram and blood glucose level

Content Provider	IET Digital Library
Author	Zhou, Xueling Ling, Bingo Wing Kuen Tian, Zikang Ho, Yiu Wai Teo, Kok Lay
Abstract	Continuous monitoring of the blood glucose levels is essential and critical for controlling diabetes and its complications. With the improvement of the measurement accuracy of the acquisition devices developed in recent decades, developing the optical-based methods for performing the non-invasive blood glucose estimation for the consumer applications becomes very important. The authors’ previous work is based on the heart rate variability of the electrocardiogram and the existing method is based on applying the random forest to the features extracted from the photoplethysmogram. However, the accuracies of these two methods are not very high. In this study, a joint empirical mode decomposition and exponential function estimation approach is proposed for estimating the mean value of a photoplethysmogram acquired from a wearable non-invasive blood glucose device. Also, the exponential function fitting approach is employed for estimating the blood glucose levels via an L 1 norm formulation. The computer numerical simulation results show that the estimation accuracy based on their proposed method is higher than that based on the state-of-the-art methods. Therefore, their proposed method can be employed for performing blood glucose estimation effectively.
Starting Page	652
Ending Page	665
Page Count	14
ISSN	17519675
Volume Number	14
e-ISSN	17519683
Issue Number	Issue 9, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/14/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2020.0096
Journal	IET Signal Processing
Publisher Date	2020-09-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biochemistry Biology And Medical Computing Biomedical Equipment Biomedical Imaging/measurement Blood Blood Glucose Level Computer Numerical Simulation Continuous Monitoring Diabetes Digital Signal Processing Diseases Estimation Accuracy Exponential Function Estimation Approach Exponential Function Fitting Approach Function Theory And Analysis Hilbert Transform Integral Transforms in Numerical Analysis Joint Empirical Mode Decomposition L1 Norm Approach Mean Value Medical Signal Detection Medical Signal Processing Noninvasive Blood Glucose Estimation Numerical Analysis Numerical Approximation And Analysis Optical And Laser Radiation Optical-based Method Patient Diagnostic Method And Instrumentation Patient Monitoring Photoplethysmogram Photoplethysmography Physical Chemistry of Biomolecular Solutions And Condensed State Signal Detection Sugar Wearable Noninvasive Blood Glucose Device
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Extraction of respiratory rate from PPG using ensemble empirical mode decomposition with Kalman filter

Noninvasive blood pressure analysis using empirical mode decomposition (EMD) - Based oscillometric method

Blood Pressure Estimation by Photoplethysmogram Decomposition into Hyperbolic Secant Waves

Non-invasive detection of alcohol concentration based on photoplethysmogram signals

Dynamically sampled multivariate empirical mode decomposition

Automatic estimation of respiration rate from oronasal pressure using Ensemble empirical mode decomposition, Butterworth filter, and data fusion

Potential value of electrocardiogram and photoplethysmogram for non-invasive blood pressure estimation during exercise

Empirical mode decomposition for noninvasive atrial fibrillation dominant frequency estimation

Recording system and data fusion algorithm for enhancing the estimation of the respiratory rate from photoplethysmogram

Joint empirical mode decomposition, exponential function estimation and L 1 norm approach for estimating mean value of photoplethysmogram and blood glucose level

Similar Documents

Extraction of respiratory rate from PPG using ensemble empirical mode decomposition with Kalman filter

Noninvasive blood pressure analysis using empirical mode decomposition (EMD) - Based oscillometric method

Blood Pressure Estimation by Photoplethysmogram Decomposition into Hyperbolic Secant Waves

Non-invasive detection of alcohol concentration based on photoplethysmogram signals

Dynamically sampled multivariate empirical mode decomposition

Automatic estimation of respiration rate from oronasal pressure using Ensemble empirical mode decomposition, Butterworth filter, and data fusion

Potential value of electrocardiogram and photoplethysmogram for non-invasive blood pressure estimation during exercise

Empirical mode decomposition for noninvasive atrial fibrillation dominant frequency estimation

Recording system and data fusion algorithm for enhancing the estimation of the respiratory rate from photoplethysmogram

Joint empirical mode decomposition, exponential function estimation and L 1 norm approach for estimating mean value of photoplethysmogram and blood glucose level