Gilwon Yoon

The nonlinear mechanical response of the red blood cell

We measure the dynamical mechanical properties of human red blood cells. A single cell response is measured with optical tweezers. We investigate both the stress relaxation following a fast deformation and the effect of varying the strain rate. We find a power-law decay of the stress as a function of time, down to a plateau stress, and a power-law increase of the cells elasticity as a function of the strain rate. Interestingly, the exponents of these quantities violate the linear superposition principle, indicating a nonlinear response. We propose that this is due to the breaking of a fraction of the crosslinks during the deformation process. The soft glassy rheology model accounts for the relation between the exponents we observe experimentally. This picture is consistent with recent models of bond remodeling in the red blood cells molecular structure. Our results imply that the blood cells mechanical behavior depends critically on the deformation process.

Comparison between transmittance and reflectance measurements in glucose determination using near infrared spectroscopy

Glucose determination based on near-IR spectroscopy is investigated for reflectance and transmittance measurement. A wavelength range is 1100 to 2500 nm, which includes both the combination and overtone bands of glucose absorption. Intralipid solutions are used as samples, where glucose concentrations vary between 0 and 1000 mg/dl. Sample thickness for reflectance is 10 cm and 1- and 2-mm-thick samples are used for transmission. Partial least-squares regression (PLSR) analyses are performed to predict glucose concentrations. The standard errors of calibration are comparable between reflectance and 2-mm-thick transmittance. The reflectance method is inferior to the transmittance method in terms of the standard errors of prediction. Loading vector analysis for reflectance does not show glucose absorption features. Reflected light may not have enough information of glucose since a major portion of detected light has a short optical path length. In addition, prediction becomes more dependent on medium scattering rather than glucose, compared with transmission measurement. Loading vectors obtained from a PLSR transmittance analysis have glucose absorption profiles. The 1-mm-thick samples give better results than the 2-mm-thick samples for both calibration and prediction models. The transmittance setup is recommended for noninvasive glucose monitoring.

ECG/PPG Integer Signal Processing for a Ubiquitous Health Monitoring System

A compact ubiquitous-health monitor operated by single 8-bit microcontroller was made. An integer signal processing algorithm for this microcontroller was developed and digital filtering of ECG (electrocardiogram) and PPG (photoplethysmogram) was performed. Rounding-off errors due to integer operation was solved by increasing the number of effective integer digits during CPU operation; digital filter coefficients and data expressed in decimal points were multiplied by a certain number and converted into integers. After filter operation, the actual values were retrieved by dividing with the same number and selecting available highest bits. Our results showed comparable accuracies to those computed by a commercial software. Compared with a floating-point calculation by the same microcontroller, the computation speed became faster by 1.45 ∼ 2.0 times depending on various digital filtering cases. Our algorithm was successfully tested for remote health monitoring with multiple users. If our algorithm were not used, our health monitor should have used additional microcontrollers or DSP chip. The proposed algorithm reduced the size and cost of our health monitor substantially.

Prediction of glucose in whole blood by near-infrared spectroscopy: influence of wavelength region, preprocessing, and hemoglobin concentration.

Measurement accuracy for predicting glucose in whole blood was studied based on near-infrared spectroscopy. Optimal wavelength regions, preprocessing, and the influence of hemoglobin were examined using partial least-squares regression. Spectra between 1100 and 2400 nm were measured from 98 whole blood samples. In order to study the influence of hemoglobin, which is the most dominant component in blood, 98 samples were arranged such that glucose and hemoglobin concentrations were distributed in their physiological ranges. Samples were grouped into three depending on hemoglobin level. The results showed that glucose prediction was influenced by hemoglobin concentrations in the calibration model. It was necessary for samples used in the calibration model to represent the entire range of hemoglobin level. The cross-validation errors were the smallest when the wavelength regions of 1390 to 1888 nm and 2044 to 2393 nm were used. However, prediction accuracy was not very dependent on preprocessing methods in this optimal region. The standard error of glucose prediction was 25.5 mgdL and the coefficient of variation in prediction was 11.2%.

Identification of pure component spectra by independent component analysis in glucose prediction based on mid-infrared spectroscopy

We present a method for glucose prediction from mid-IR spectra by independent component analysis (ICA). This method is able to identify pure, or individual, absorption spectra of constituent components from the mixture spectra without a priori knowledge of the mixture. This method was tested with a two-component system consisting of an aqueous solution of both glucose and sucrose, which exhibit distinct but closely overlapped spectra. ICA combined with principal component analysis was able to identify a spectrum for each component, the correct number of components, and the concentrations of the components in the mixture. This method does not need a calibration process and is advantageous in noninvasive glucose monitoring since expensive and time-consuming clinical tests for data calibration are not required.

Nonconstrained Blood Pressure Measurement by Photoplethysmography

Blood pressure was predicted from photoplethysmography (PPG). To obtain PPG, backscattered light from a fingertip was measured and its waveform was analyzed. Systolic upstroke time and diastolic time in the pulse waveform were used as parameters to predict blood pressure. The experiment was carried out with five subjects on five different days. The systolic upstroke time had a correlation coefficient of -0.605 with respect to systolic blood pressure and the diastolic time had a correlation coefficients of -0.764 for diastolic pressure. This PPG method does not require an air-cuff installation on the arm and can predict blood pressure continuously. This simple LED/photo detector setup can be a good candidate for nonconstrained monitoring of blood pressure variations.

Glucose Prediction in the Interstitial Fluid Based on Infrared Absorption Spectroscopy Using Multi-component Analysis

Prediction of glucose concentration in the interstitial fluid (ISF) based on mid-infrared absorption spectroscopy was examined at the glucose fundamental absorption band of 1000 - 1500/cm (10 - 6.67 um) using multi-component analysis. Simulated ISF samples were prepared by including four major ISF components. Sodium lactate had absorption spectra that interfere with those of glucose. The rest NaCl, KCl and

Study of Propagation of Light along an Acupuncture Meridian

CaCl_2

Reagentless Determination of Human Serum Components Using Infrared Absorption Spectroscopy

did not have any signatures. A preliminary experiment based on Design of Experiment, an optimization method, proved that sodium lactate influenced the prediction accuracy of glucose. For the main experiment, 54 samples were prepared whose glucose and sodium lactate concentration varied independently. A partial least squares regression (PLSR) analysis was used to build calibration models. The prediction accuracy was dependent on spectrum preprocessing methods, and Mean Centering produced the best results. Depending on calibration sample sets whose sodium lactate had different concentration levels, the standard error prediction (SEP) of glucose ranged

Noninvasive Hematocrit Monitoring Based on Parameter-optimization of a LED Finger Probe

17.19{\sim}21.02\;mg/dl