Design and Validation of a Monte Carlo Method for the Implementation of Noninvasive Wearable Devices for HbA1c Estimation Considering the Skin Effect
Abstract
:1. Introduction
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- Intrinsic and extrinsic noise can be removed by the model (hardware design) itself. Hence, the model will have more accurate estimates of our target parameters.
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- Skin pigments (melanin and bilirubin) and the skin reflection coefficient are also considered in the epidermis of the wrist model.
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- A simple sensor (cylindrical type LED-PD pair) was added to compensate for the skin effect.
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- Calibration can be made simpler due to the Monte Carlo-based model considering different skin properties.
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- The performance of the proposed method was demonstrated by increasing the number of subjects to 50.
2. Methodology
2.1. Skin Effect Analysis of a PPG Sensor (PPG Signal Impurities)
2.2. Proposed Method and Hardware Design for Purifying Impurities
2.3. Data Acquisition System
2.3.1. PPG Data Acquisition System Description
2.3.2. PPG Data Source and Analysis
2.3.3. PPG Data Analysis
2.4. Estimation Process with Monte Carlo Simulation
2.4.1. Overall Estimation Process
2.4.2. Monte Carlo Photon Propagation Simulation
2.5. Calibration Using XGBoost Regression
3. Results and Discussion
3.1. Method 1: Using 3 AC/DC and 3 Cylindrical Values
3.2. Method 2: Using 2 AC/DCs, 1 Ratio, and 3 Cylindrical Values
3.3. Comparison with Previous Studies
3.4. Result Using 50 Subjects’ Data
3.5. Discussion
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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Min | Max | Mean | Median | SD | 25th Percentile | 75th Percentile | |
---|---|---|---|---|---|---|---|
%HbA1c | 5.20 | 7.70 | 6.04 | 5.80 | 0.678 | 5.60 | 6.40 |
MSE | ME | MAD | RMSE | Pearson’s r | %Accuracy | |
---|---|---|---|---|---|---|
Proposed (Method 1, 28 subjects) | 0.0106 | −0.0456 | 0.0490 | 0.1030 | 0.9907 | 99.14 |
MSE | ME | MAD | RMSE | Pearson’s r | %Accuracy | |
---|---|---|---|---|---|---|
Proposed (Method 2, 28 subjects) | 0.0084 | −0.0416 | 0.0451 | 0.0917 | 0.9928 | 99.21 |
Metric | MSE | ME | MAD | RMSE | Pearson’s r | |
---|---|---|---|---|---|---|
Method | ||||||
Shifat et al. [9] (28 subjects) | 0.0500 | 0.0100 | 0.1300 | 0.2100 | 0.9700 | |
Proposed (Method 1, 28 subjects) | 0.0106 | 0.0456 | 0.0490 | 0.1030 | 0.9907 | |
Proposed (Method 2, 28 subjects) | 0.0084 | 0.0416 | 0.0451 | 0.0917 | 0.9928 |
Metric | MSE | ME | MAD | RMSE | Pearson’s r | |
---|---|---|---|---|---|---|
Method | ||||||
Shifat et al. [9] (28 subjects) | 0.0500 | 0.0100 | 0.1300 | 0.2100 | 0.9700 | |
Proposed (Method 1, 28 subjects) | 0.0106 | 0.0456 | 0.0490 | 0.1030 | 0.9907 | |
Proposed (Method 2, 28 subjects) | 0.0084 | 0.0416 | 0.0451 | 0.0917 | 0.9928 | |
Proposed (Method 1, 50 subjects) | 0.0116 | 0.0402 | 0.0877 | 0.1075 | 0.9894 | |
Proposed (Method 2, 50 subjects) | 0.0121 | 0.0451 | 0.0887 | 0.110 | 0.9894 |
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Kwon, T.-H.; Hossain, S.; Turja, M.S.; Kim, K.-D. Design and Validation of a Monte Carlo Method for the Implementation of Noninvasive Wearable Devices for HbA1c Estimation Considering the Skin Effect. Micromachines 2024, 15, 1067. https://doi.org/10.3390/mi15091067
Kwon T-H, Hossain S, Turja MS, Kim K-D. Design and Validation of a Monte Carlo Method for the Implementation of Noninvasive Wearable Devices for HbA1c Estimation Considering the Skin Effect. Micromachines. 2024; 15(9):1067. https://doi.org/10.3390/mi15091067
Chicago/Turabian StyleKwon, Tae-Ho, Shifat Hossain, Mrinmoy Sarker Turja, and Ki-Doo Kim. 2024. "Design and Validation of a Monte Carlo Method for the Implementation of Noninvasive Wearable Devices for HbA1c Estimation Considering the Skin Effect" Micromachines 15, no. 9: 1067. https://doi.org/10.3390/mi15091067