Dae-Geun Jang

PPG delineator for real-time ubiquitous applications

This paper presents real-time signal processing algorithm for detection of onsets and peaks in Photoplethysmogram (PPG) waveform. Algorithm relies on the analysis of amplitude, slope and inter-beat intervals. The presented algorithm consists of four stages for characterizing PPG waveform. Preprocessing stage involves transformation of PPG since the original waveform is less impulsive and robust. In second stage, algorithm seeks for valid pulse detection in transformed signal complying with the amplitude threshold and inter-beat interval. On detection of valid pulses, algorithm then searches backward and forward in transformed signal for the detection of peaks and onsets. Further the detection parameters are made adaptive to comply with varying beat morphologies and fluctuations in baseline. All signal processing steps and decision logics are implemented with low computational complexity to make it applicable for compact ubiquitous health monitoring devices. On evaluation with our database, the algorithm achieved sensitivity of 96.89% and positive predictivity of 94.55% within an acceptance level of 12 ms.

A Robust Method for Pulse Peak Determination in a Digital Volume Pulse Waveform With a Wandering Baseline

This paper presents a robust method for pulse peak determination in a digital volume pulse (DVP) waveform with a wandering baseline. A proposed new method uses a modified morphological filter (MMF) to eliminate a wandering baseline signal of the DVP signal with minimum distortion and a slope sum function (SSF) with an adaptive thresholding scheme to detect pulse peaks from the baseline-removed DVP signal. Further in order to cope with over-detected and missed pulse peaks, knowledge based rules are applied as a postprocessor. The algorithm automatically adjusts detection parameters periodically to adapt to varying beat morphologies and fluctuations. Compared with conventional methods (highpass filtering, linear interpolation, cubic spline interpolation, and wavelet adaptive filtering), our method performs better in terms of the signal-to-error ratio, the computational burden (0.125 seconds for one minute of DVP signal analysis with the Intel Core 2 Quad processor @ 2.40 GHz PC), the true detection rate (97.32% with an acceptance level of 4 ms ) as well as the normalized error rate (0.18%). In addition, the proposed method can detect true positions of pulse peaks more accurately and becomes very useful for pulse transit time (PTT) and pulse rate variability (PRV) analyses.

A Gaussian Model-Based Probabilistic Approach for Pulse Transit Time Estimation

In this paper, we propose a new probabilistic approach to pulse transit time (PTT) estimation using a Gaussian distribution model. It is motivated basically by the hypothesis that PTTs normalized by RR intervals follow the Gaussian distribution. To verify the hypothesis, we demonstrate the effects of arterial compliance on the normalized PTTs using the Moens-Korteweg equation. Furthermore, we observe a Gaussian distribution of the normalized PTTs on real data. In order to estimate the PTT using the hypothesis, we first assumed that R-waves in the electrocardiogram (ECG) can be correctly identified. The R-waves limit searching ranges to detect pulse peaks in the photoplethysmogram (PPG) and to synchronize the results with cardiac beats-i.e., the peaks of the PPG are extracted within the corresponding RR interval of the ECG as pulse peak candidates. Their probabilities of being the actual pulse peak are then calculated using a Gaussian probability function. The parameters of the Gaussian function are automatically updated when a new pulse peak is identified. This update makes the probability function adaptive to variations of cardiac cycles. Finally, the pulse peak is identified as the candidate with the highest probability. The proposed approach is tested on a database where ECG and PPG waveforms are collected simultaneously during the submaximal bicycle ergometer exercise test. The results are promising, suggesting that the method provides a simple but more accurate PTT estimation in real applications.

Enhancing the Pulse Contour Analysis-Based Arterial Stiffness Estimation Using a Novel Photoplethysmographic Parameter

In this paper, we propose a novel method for enhancing pulse contour analysis-based arterial stiffness estimation using a simple and low-complexity photoplethysmographic parameter (P2Ocd). The method first eliminates baseline wanders in the digital volume pulse (DVP) by applying a simple morphological filter. The filtered DVP signal is then transformed into a slope sum function signal to simplify the pulse peak detection process by enhancing the upslope of the DVP signal while suppressing its downslope. An adaptive thresholding scheme is applied to detect pulse peaks from the transformed signal. Pulse onsets are then identified as the minimum values between consecutive pulse peaks. The P2Ocd is finally calculated by dividing the time interval between the pulse peak and the pulse onset by the pulse length. In order to assess the agreement of the P2Ocd with an established technique, brachial-ankle pulse wave velocity, we performed Bland-Altman and correlation analyses. Furthermore, we evaluated the P2Ocd-based arterial stiffness estimation in terms of prediction accuracy (% error rate) and repeatability (coefficient of variation). The results show that the proposed measurement agrees well with the established technique and shows a high repeatability; it also has a better predictive accuracy than that of conventional methods. In addition, we show that the proposed parameter further improves the predictive accuracy by combining it with age. The proposed method is therefore highly applicable to small ubiquitous healthcare applications.

A morphological approach to calculation of the second derivative of photoplethysmography

Many previous studies reported that the second derivative of photoplethysmography (SDPTG) is a rational indicator of arterial stiffness. In order to obtain the SDPTG, a photoplethysmography (PPG) and the second derivative operator are required. Since the PPG contain very high frequency components due to quantization effect, pulse signal smoothing has to be preceded before calculation of the second derivative. Over the past few years, several techniques have been proposed and applied for assessing the SDPTG. Although these techniques show high performance in assessment, they require higher order filters according to signal specifications, such as sampling rate. In order to complement this problem, we have proposed a linear fitting algorithm based on morphological approach and have compared performance of our proposed algorithm with that of previous algorithms. In performance evaluation, we can conclude that our proposed algorithm is reasonable to calculate the SDPTG waveform, which is similar to the waveform obtained by previous approach, with low computational complexity.

A Study on the Effects of Chinese Qigong and Kundalini Yoga Meditations on the Heart Rate Variability of Skilled Students

Abstract: In this paper, we have investigated effects of two specific meditations (Chinese qigong meditation and Kun-dalini yoga meditation) on the heart rate variability (HRV), which is a well-known quantitative measure of autonomicbalance, of skilled students. To analyze the effects, the MIT/BIH physionet database was utilized. The databaseincludes RR intervals of eight skilled Chinese qigong meditators (5 women and 3 men; age range 26-35) and fourskilled Kundalini yoga meditators (2 women and 2 men; age range 20-52). RR intervals of each subject were measuredbefore and during the meditations. For HRV analysis, we have used typical four HRV parameters - the low frequencyto high frequency power ratio (LF/HF ratio), SD2/SD1 ratio, sample entropy, and fractal dimension. The LF/HF ratiowas calculated by the autoregressive spectrum and the SD2/SD1 ratio was derived from the Poincare plot. The sam-ple entropy was computed from the phase space plot and the fractal dimension was estimated by the Higuchi’s algo-rithm. In the experiments, the Wilcoxon signed rank test was employed because we used small datasets andcompared HRV parameters before and during the meditations. As a result, we have found increment of the LF/HFand SD2/SD1 ratios in both meditations; whereas the sample entropy is decreased during the meditations. In addition,the fractal dimension is increased during the Chinese qigong meditation; whereas it is decreased during the Kundaliniyoga meditation. The results show that the sympathetic nervous system is generally more activated in skilled Chi-nese qigong and Kundalini yoga meditators, but the activation of the parasympathetic nervous tone is suppressed.Key words: Heart rate variability, Chinese qigong meditation, Yoga meditation, Autonomic nervous system.

Mental health promotion system

Mental activity promotion system is presented that analyzes, quantifies, trains and prescribes based on analysis of logical, memorizing, concentrative, decisive, in conditions where time and space is involved, possibility of dementia, and on evaluation of lifestyle of subjects. Special consideration has been made to make the system motivational, persuasive, attractive and fun to use. The system has been successfully deployed in Bitgeoul Senior health town, Gwangju, South Korea.

A comparison of correction algorithms to pulse parameters for estimation of arterial stiffness

Over the past few years, a considerable number of studies have focused on estimation of arterial stiffness by using a digital volume pulse (DVP). This can generally be achieved by a linear regression analysis with several pulse parameters. Among various pulse parameters, since time-related pulse parameters, such as reflected wave arrival time, are varied with pulse rate, it can provide incorrectly estimated clinical information. In order to complement this problem, many previous studies suggested the following correction algorithms, which are widely used in ECG analysis: Bazetts formula, Fridericias formula, and linear regression equation. Although these correction algorithms has been applied and tested in the ECG signal, they must be validated in the DVP since they can provide different performance in the DVP. Therefore, we have shown a comparison among commonly used correction algorithms for estimation of arterial stiffness in this paper. In order to compare the performance of the correction algorithms, we have carried out the correlation analysis by using a SPSS tool, which is typically used in statistical analysis. As a result, we can notice that it is reasonable to use both the Bazetts formula and linear regression equation for estimation of arterial stiffness by using time-related pulse parameters extracted from the DVP.

An automatic signal detection algorithm for the digital volume pulse

Many previous studies suggested that the digital volume pulse (DVP) can be used to estimate arterial stiffness. The DVP waveform can be rapidly acquired by measuring reflection or absorption of red light (or infrared light) across the photoplehtysmography (PPG). Because of the nature of its measuring principle, the DVP is often contaminated by noise from light sources, such as sunlight, and disturbances due to movement of the recording electrodes. This phenomenon makes us hard to extract pulse features and thus provides incorrect clinical information. In order to screen out this problem, we have developed the automatic signal detection algorithm for the DVP and have evaluated its performance. In the performance evaluation, we have obtained the false negative rate (FNR) of 0.33% and the predictive accuracy rate (PAR) of 97.19%. From the results, we conclude that our proposed signal detection algorithm can be used as a preprocessor before the extraction of pulse features with reasonable performance.

The Effect of Age and Dual Task to Human Postural Control

The purpose of this study is to investigate the effect of aging and dual tasking to the postural control during quiet standing. It was hypothesized that the center of pressure (COP) dynamics would be differently affected by aging and characteristics of the task. Total 60 adults (35 young adults and 25 older adults) participated in this study. They conducted two different standing tasks (dual vs. Non- dual) twice in a random order. Variability, complexity, coupling and symmetric index from the left, right and overall COPs were mea- sured by various parameters in nonlinear, linear and frequency analyses methods. Results demonstrated that older adults had worse performance in postural control with decreased complexity in overall sway movement, and increased coupling between left and right limb COP movement, even though there was no significant difference in symmetric index. These tendencies are generally clearer in nonlinear measures at the dual task condition. Results implied that older adults had compensatory strategy in dual tasking which results in simple and combined postural movement patterns.