Browsing by Author "Chiang, Pei-Yu"

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A 1.5 mW front-end readout circuit for a small-sized melanin sensor
(2016-06-01)
Cheng, Shih-Song
;
Huang, Sheng-Chieh
;
Tran, Trong-Hieu
;
Shao, Kai-Yu
;
Chao, Paul C. -P.
This study presents a novel readout circuit that serves to evaluate quantity of skin melanin in a noninvasive way via utilizing a photoplethysmography (PPG) optical sensor. PPG sensors are widely used nowadays for noninvasive diagnosis due to their salient features such as low cost and easy-to-useness. PPG signal is known highly correlated with human skin condition and cardiovascular system health. A new readout circuit featuring high-bandwidth, low-noise and low-power is designed in this study to evaluate quantitatively the melanin content of human skin based on PPG signals with high accuracy. This new readout circuit is intended to convert and amplify the electric current of the photo diode in the PPG sensor to voltage signals, and then being further properly amplified to the full dynamic range of the chip circuit fabricated by the TSMC 0.18 mu m process for maximum S/N ratios. The designed circuit has a front-end transimpedance amplifier (TIA), 60 dB in gain, with a degenerate resistor to perform a low noise less than 3 A mu V/aeHz while operating by a 3.3 V supply. In related circuit designs, the mismatch in current sources caused by CMOS process variation is mitigated by a current steering digital-analog-converter (DAC) with least significant bit (LSB) corresponding to 1.25 A mu A. Both TIA and DAC are designed with effort to render high accuracy in the digital outputs for the levels of sensed melanin. The power consumption of chip design is as low as 1.5 mW, while the error rate between measurement and simulation result is less than 3 %.
A 1.5 mW front-end readout circuit for a small-sized melanin sensor
(2016-06)
Cheng, Shih-Song
;
Huang, Sheng-Chieh
;
Tran, Trong-Hieu
;
Shao, Kai-Yu
;
Chao, Paul C. -P.
This study presents a novel readout circuit that serves to evaluate quantity of skin melanin in a noninvasive way via utilizing a photoplethysmography (PPG) optical sensor. PPG sensors are widely used nowadays for noninvasive diagnosis due to their salient features such as low cost and easy-to-useness. PPG signal is known highly correlated with human skin condition and cardiovascular system health. A new readout circuit featuring high-bandwidth, low-noise and low-power is designed in this study to evaluate quantitatively the melanin content of human skin based on PPG signals with high accuracy. This new readout circuit is intended to convert and amplify the electric current of the photo diode in the PPG sensor to voltage signals, and then being further properly amplified to the full dynamic range of the chip circuit fabricated by the TSMC 0.18 mu m process for maximum S/N ratios. The designed circuit has a front-end transimpedance amplifier (TIA), 60 dB in gain, with a degenerate resistor to perform a low noise less than 3 A mu V/aeHz while operating by a 3.3 V supply. In related circuit designs, the mismatch in current sources caused by CMOS process variation is mitigated by a current steering digital-analog-converter (DAC) with least significant bit (LSB) corresponding to 1.25 A mu A. Both TIA and DAC are designed with effort to render high accuracy in the digital outputs for the levels of sensed melanin. The power consumption of chip design is as low as 1.5 mW, while the error rate between measurement and simulation result is less than 3 %.
A Novel Wireless Photoplethysmography Blood-Flow Volume Sensor for Assessing Arteriovenous Fistula of Hemodialysis Patients
(2017-12-01)
Chiang, Pei-Yu
;
Chao, Paul C. -P.
;
Tarng, Der-Cherng
;
Yang, Chih-Yu
;
電控工程研究所
A novel blood-flow volume (BFV) sensor is presented for assessing quality of arteriovenous fistula in hemodialysis patients via noninvasive reflectance-type photoplethysmography (PPG). BFV is nowadays in clinic practices evaluated using an ultrasound Doppler monitor, which is expensive, bulky, and can only be operated by well-trained medical personnels. This study is devoted to develop a low-cost, small-sized, portable, and easy-to-use PPG sensor that is capable of continuous measurement of BFV. New designs of front-end analog circuits, signal processing, and an intelligent neural network calibration method are employed to finally achieve high correlation (R-2 = 0.7176), as opposed to the ultrasound Doppler monitor, with the root-mean-squared errors successfully controlled under 289 ml/min.
A Portable, Wireless Photoplethysomography Sensor for Assessing Health of Arteriovenous Fistula Using Class-Weighted Support Vector Machine
(2018-11-01)
Chao, Paul C. -P.
;
Chiang, Pei-Yu
;
Kao, Yung-Hua
;
Tu, Tse-Yi
;
Yang, Chih-Yu
A portable, wireless photoplethysomography (PPG) sensor for assessing arteriovenous fistula (AVF) by using class-weighted support vector machines (SVM) was presented in this study. Nowadays, in hospital, AVF are assessed by ultrasound Doppler machines, which are bulky, expensive, complicated-to-operate, and time-consuming. In this study, new PPG sensors were proposed and developed successfully to provide portable and inexpensive solutions for AVF assessments. To develop the sensor, at first, by combining the dimensionless number analysis and the optical Beer Lambert's law, five input features were derived for the SVM classifier. In the next step, to increase the signal-noise ratio (SNR) of PPG signals, the front-end readout circuitries were designed to fully use the dynamic range of analog-digital converter (ADC) by controlling the circuitries gain and the light intensity of light emitted diode (LED). Digital signal processing algorithms were proposed next to check and fix signal anomalies. Finally, the class-weighted SVM classifiers employed five different kernel functions to assess AVF quality. The assessment results were provided to doctors for diagonosis and detemining ensuing proper treatments. The experimental results showed that the proposed PPG sensors successfully achieved an accuracy of 89.11% in assessing health of AVF and with a type II error of only 9.59%.
Cloud-Based Fine-Grained Health Information Access Control Framework for Lightweight IoT Devices with Dynamic Auditing and Attribute Revocation
(2018-04-01)
Yeh, Lo-Yao
;
Chiang, Pei-Yu
;
Tsai, Yi-Lang
;
Huang, Jiun-Long
;
資訊工程學系
The eHealth trend has spread globally. Internet of Things (IoT) devices for medical service and pervasive Personal Health Information (PHI) systems play important roles in the eHealth environment. A cloud-based PHI system appears promising but raises privacy and information security concerns. We propose a cloud-based fine-grained health information access control framework for lightweight IoT devices with data dynamics auditing and attribute revocation functions. Only symmetric cryptography is required for IoT devices, such as wireless body sensors. A variant of ciphertext-policy attribute-based encryption, dual encryption, and Merkle hash trees are used to support fine-grained access control, efficient dynamic data auditing, batch auditing, and attribute revocation. Moreover, the proposed scheme also defines and handles the cloud reciprocity problem wherein cloud service providers can help each other avoid fines resulting from data loss. Security analysis and performance comparisons show that the proposed scheme is an excellent candidate for a cloud-based PHI system.
Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device
(2019-08-01)
Chiang, Pei-Yu
;
Chao, Paul C. -P.
;
Tu, Tse-Yi
;
Kao, Yung-Hua
;
Yang, Chih-Yu
The classifier of support vector machine (SVM) learning for assessing the quality of arteriovenous fistulae (AVFs) in hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor device is presented in this work. In clinical practice, there are two important indices for assessing the quality of AVF: the blood flow volume (BFV) and the degree of stenosis (DOS). In hospitals, the BFV and DOS of AVFs are nowadays assessed using an ultrasound Doppler machine, which is bulky, expensive, hard to use, and time consuming. In this study, a newly-developed PPG sensor device was utilized to provide patients and doctors with an inexpensive and small-sized solution for ubiquitous AVF assessment. The readout in this sensor was custom-designed to increase the signal-to-noise ratio (SNR) and reduce the environment interference via maximizing successfully the full dynamic range of measured PPG entering an analog-digital converter (ADC) and effective filtering techniques. With quality PPG measurements obtained, machine learning classifiers including SVM were adopted to assess AVF quality, where the input features are determined based on optical Beer-Lambert's law and hemodynamic model, to ensure all the necessary features are considered. Finally, the clinical experiment results showed that the proposed PPG sensor device successfully achieved an accuracy of 87.84% based on SVM analysis in assessing DOS at AVF, while an accuracy of 88.61% was achieved for assessing BFV at AVF.
Mathematical Derivation, Circuits Design and Clinical Experiments of Measuring Blood Flow Volume (BFV) at Arteriovenous Fistula (AVF) of Hemodialysis (HD) Patients Using a Newly-Developed Photoplethysmography (PPG) Sensor
(2018-01-01)
Paul, Paul C. P.
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Chiang, Pei-Yu
;
Tarng, D. C.
;
Yang, C. Y.
;
電子工程學系及電子研究所
Mathematical derivation of calculating blood flow volume (BFV) at arteriovenous fistula (AVF) using a newly-developed photoplethysmography (PPG) sensor is presented in this work. Also, the readout circuit of the PPG sensor intended to increase the signal-noise ratio (S/NR) is designed and presented in this work. The designed PPG sensor equipped with derived mathematical equations shows high correlation (R-2 = 0.7563) and low error (RMSE = 212 ml/min) as compared to the gold standard.
PHOTOPLETHYSMOGRAPHY SIGNALS PROCESSING USING POLYNOMIAL PROFILE FITTING FOR MEASURING THE BLOOD FLOW VOLUME IN ARTERIOVENOUS FISTULA
(2017-01-01)
Chao, Paul C. -P.
;
Chiang, Pei-Yu
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
In this work, a new photoplethysmography (PPG) signal processing methodology using polynomial profile fitting for measuring blood flow volume (BFV) in arteriovenous fistula (AVF) is proposed. After calibration, the experiment results using proposed method shows higher correlation (R=0.7883) and lower error (RMSE=109 ml/min) compared to the ones using conventional methods (R=0.3212, RMSE=168 ml/min).
Quality Evaluation via PPG on the AVFs of Hemodialysis Patients Based on Both Blood Flow Volume and Degree of Stenosis
(2019-01-01)
Chiang, Pei-Yu
;
Chao, Paul C. -P.
;
Tu, Tse-Yi
;
Kao, Yung-Hua
;
Yang, Chih-Yu
The classifier of support vector machine (SVM) learning for assessing quality of arteriovenous fistula (AVF) at hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor are presented in this work. Based on current medical standard, there are two important indices for assessing AVF quality, the blood flow volume (BFV) and the degree of stenosis (DOS). In current clinical practice, BFV and DOS of AVFs are assessed by using an ultrasound Doppler machine, which is bulky, expensive, hard-to-use and time-consuming. Therefore, a new PPG sensor module is designed to provide patients and doctors an inexpensive and small-sized solution to assess AVF quality. The readout of the sensor is successfully optimized to increase the signal to noise ratio (SNR) and reduce the environment interference, the readout circuitries are designed to fit the full dynamic range of analog-digital converter (ADC) and to filter out the noise. To assess quality of AVF, three different machine learning classifiers are developed, where the input features are selected based on optical Beer Lambert's law and hemodynamic model. Finally, the clinical experiment results show that the proposed PPG sensor successfully achieves an accuracy of 87.838% in assessing AVF quality based on satisfactory DOS and BFV measured.
Theoretical developments and clinical experiments of measuring blood flow volume (BFV) at arteriovenous fistula (AVF) using a photoplethysmography (PPG) sensor
(2018-11-01)
Chiang, Pei-Yu
;
Chao, Paul C. -P.
;
Yang, Chih-Yu
;
Tarng, Der-Cherng
;
電子工程學系及電子研究所
A new theoretical developments of measuring blood flow volume at arteriovenous fistula (AVF) using a photoplethysmography (PPG) sensor is presented in this work. The mathematical equation is derived under the practical perspective, aiming at applying to small-size, portable, inexpensive and easy-to-use PPG sensor, in order to replace bulky, expensive Doppler machines which is the commonly used instruments for accessing AVF noninvasively nowadays. Furthermore, a new, portable and wireless PPG sensor with ambient light compensation and motion artifact detection, is designed for performing clinical validation of the proposed equation. After neural network calibration with the gold standard, dilution concentration sensor, the experiment result reveals that the PPG sensors implementing the proposed equation successfully achieve much higher correlation (R-2=0.8064) and much lower error (RMSE=171.68ml/min, MAPE=15.84%) compared to the commercial Doppler machine and other previous works.