• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.1
• /
• pp.51-56
• /
• 2019

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.6
• /
• pp.1102-1108
• /
• 2008

Wearable physiological signal monitoring systems are regarded as an important sensing unit platforms in ubiquitous/mobile healthcare application. In this paper, we suggested the modified bipolar electrodes implemented on the portable heart activity monitoring system, which minimized the distance of electrodes formed on a attachable pad. The proposed electrode configuration is useful in mobile measurement environments, but has a disadvantage of reduced amplitude of the heart action potential. In order to overcome the shortcoming of the suggested electrode configuration, we implemented the amplifying circuit to increase the signal-gain and decrease the artifacts. For evaluations, we analyzed the specificity of measured cardiography using the proposed electrodes through the comparing of heart activity monitoring system with standard clinical ECG(lead2) by pearson correlation coefficients. The result showed that the average correlation coefficient is $0.903{\pm}0.036,\;0.873{\pm}0.072$ at V3, V4 chest lead position, respectively. Thus, the modified bipolar electrode is quite suitable to monitor the electrical activity of the heart in the situation of the mobile environment, and could be considered having high similarity with standard clinical ECG.

• Journal of Biomedical Engineering Research
• /
• v.31 no.2
• /
• pp.170-175
• /
• 2010

A method of measuring heart rate using photoplethysmograph(PPG) signal during exercise is proposed. PPG's are composed of strong base tones and their harmonics, and the strong base tones are trackable by the adaptive notch filter (ANF) which adjusts its coefficients to minimize the output power. The proposed heart rate measurement algorithm continuously notches the frequency component with the maximum power in the measured PPG, so that the fundamental frequency corresponding to heart rate is traced. We also presents methods of detecting degeneration and impulsive noise blocks to minimize the coefficient fluctuation. Experiments were conducted using real PPG signals captured during exercise. Results showed that the proposed algorithm is capable of consistently tracking the heart rate embedded in the noisy PPG's.

• Journal of the Institute of Convergence Signal Processing
• /
• v.16 no.4
• /
• pp.134-138
• /
• 2015

Heart sound is used for a basic clinical examination to check for abnormalities in the lungs and heart that can be heard with a stethoscope or phonocardiography. In this paper, we try to find an easier and non-invasive method to diagnose heart diseases using neural network classifier. The classifier has been developed for one normal heart sound and five murmurs by using Shannon entropy and conjugate scaled back propagation algorithm. The experimental results showed that the classification is possible with 1.63185e-6 of classification error.

• Korean Journal of Radiology
• /
• v.2 no.3
• /
• pp.171-174
• /
• 2001

Shaken baby syndrome (SBS) is a form of child abuse that can cause significant head injuries, of which subdural hematoma (SDH) is the most common manifestation. We report the MRI findings of chronic SDH in three cases of SBS, involving two-, three- and eight-month-old babies. The SDH signal was mostly low on T1-weighted images and high on T2-weighted images, suggesting chronic SDH. In chronic SDH, a focal high signal on T1-weighted images was also noted, suggesting rebleeding. Contrast-enhanced MRI revealed diffuse dural enhancement.

• Journal of Biomedical Engineering Research
• /
• v.12 no.3
• /
• pp.209-214
• /
• 1991

Digital fetal monitoring system based on the personal computer combined with the digital signal processing (DSP) board was implemented. The DSP board acquires and digitally processes ultra- sound fetal Doppler signal for digital signal conditioning, rectification, low -pass filtering, autocorrealtion function calculation and its peak detection. The personal computer interfaced with the DSP board is in charge of graphic display, hardcopy, data transmission and on -line analysis of fetal heart rate change including on - line warning system, base -line estmation, acceleration, deceleration and variability. It is one of the most suitable situation to apply the DSP chip for siganl conditioning, digital filtering of ultrasound fetal Dopier signal and fetal heart rate estimation using autocorrelation technique .

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.493-496
• /
• 2005

For home healthcare, the unconstrained measurement of physiological signal is highly required to avoid the inconvenience of users. The recording and analysis of the fundamental parameters during sleep like respiration and heart beat provide valuable information on his/her healthcare. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The balancing tube between two air cells is used to increase the robustness against postural changes during the measurement period. The meaningful frequency range could be selected by the pneumatic filter with balancing tube. ECG (Electrocardiography) and respiration sensor (plethysmography) were measured for comparison with the signal from air mattress. To extract the heart beat information from air pressure sensor, digital signal processing technique was used. The accuracy for breathing interval and heart beat monitoring was acceptable. It shows the potentials of air mattress sensor system to be the unconstrained home sleep monitoring system.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.6
• /
• pp.277-283
• /
• 2023

Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.

• Journal of Satellite, Information and Communications
• /
• v.9 no.1
• /
• pp.85-89
• /
• 2014

Electrocardiogram (ECG) is a diagnostic test which records the electrical activity of the heart, shows abnormal rhythms and detects heart muscle damages. With this ECG signal, medical centers diagnose patients' heart disease symptoms. A normal resting heart rate for adults rages from 60 to 100 beats a minute. An irregular heartbeat is called "arrhythmia", and arrhythmia is also called "cardiac dysrhythmia". In an arrhythmia, the heartbeat maybe too slow(slower than 60beats), too rapid(faster than 100beats), too irregular, etc. Among these symptoms of arrhythmia, if the heart beat is slower than the normal range, the symptom is called "bradycardia", and if it is faster than the range, it is called "tachycardia" In this letters, we proposed the detection algorithm of cardiac arrhythmia in ECG signal using R-R interval through the detection of R-peak.

• Journal of Biomedical Engineering Research
• /
• v.27 no.4
• /
• pp.154-163
• /
• 2006

A 64-channel magnetocardiogram (MCG) system using low-noise superconducting quantum interference device (SQUID) planar gradiometers was developed for the measurements of cardiac magnetic fields generated by the heart electric activity. Owing to high flux-to-voltage transfers of double relaxation oscillation SQUID (DROS) sensors, the flux-locked loop electronics for SQUID operation could be made simpler than that of conventional DC SQUIDs, and the SQUID control was done automatically through a fiber-optic cable. The pickup coils are first-order planar gradiometers with a baseline of 4 em. The insert has 64 planar gradiometers as the sensing channels and were arranged to measure MCG field components tangential to the chest surface. When the 64-channel insert was in operation everyday, the average boil-off rate of the dewar was 3.6 Lid. The noise spectrum of the SQUID planar gradiometer system was about 5 fT$_{rms}$/$\checkmark$Hz at 100 Hz, operated inside a moderately shielded room. The MCG measurements were done at a sampling rate of 500 Hz or 1 kHz, and realtime display of MCG traces and heart rate were displayed. After the acquisition, magnetic field mapping and current mapping could be done. From the magnetic and current information, parameters for the diagnosis of myocardial ischemia were evaluated to be compared with other diagnostic methods.