• Journal of Digital Convergence
• /
• v.20 no.5
• /
• pp.637-642
• /
• 2022

Self-authentication technology using electrocardiogram (ECG) signals is drawing attention as a self-authentication technology that can replace existing bio-authentication. A device that recognizes a digital electronic key can be mounted on a vehicle to wirelessly exchange data with a car, and a function that can lock or unlock a car door or start a car by using a smartphone can be controlled through a smartphone. However, smart keys are vulnerable to security, so smart keys applied with bio-authentication technology were studied to solve this problem and provide driver convenience. A personal authentication algorithm using electrocardiogram was mounted on a watch-type wearable device to authenticate bio, and when personal authentication was completed, it could function as a smart key of a car. The certification rate was 95 per cent achieved. Drivers do not need to have a smart key, and they propose a smart key as an alternative that can safely protect it from loss and hacking. Smart keys using personal authentication technology using electrocardiogram can be applied to various fields through personal authentication and will study methods that can be applied to identification devices using electrocardiogram in the future.

• Journal of Biomedical Engineering Research
• /
• v.43 no.2
• /
• pp.124-130
• /
• 2022

In this paper, we proposed a portable electronic cardiogram and stethoscope (ECGS) that can simultaneously perform the electrocardiogram (ECG) and auscultation tests to increase the reliability of diagnosis of heart disease. To measure the ECG and heart sound (HS) at the same time, three ECG electrodes and a microphone sensor were combined into a triangular shape with a width of 90 mm and a height of 97 mm that can be held in one hand. In order to prevent skin problems when they contact the patient's skin, a capacitive coupled electrode was selected as the ECG electrode and a silicone material was used in a chest piece with the microphone sensor. For the signals measured from the electrodes and the chest piece, filters were respectively configured to pass only the signals of 0.01-100 Hz and 20-250 Hz, which are frequency bands for ECG and HS. The filtered ECG and HS analog signals were converted into digital signals and transmitted to a PC using wireless communication for monitoring them. The HS could be auscultated simultaneously using an earphone. The monitored ECG had an SNR of about 34 dB and a P-QRS-T waveform is clearly visible. In addition, the HS had an SNR of about 28 dB and both S₁ and S₂ are clearly visible. It is expected that it can aid doctors' inexperience in analyzing the ECG and HS.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.5
• /
• pp.10-15
• /
• 2017

Research interest has strongly focused on developing a method for effectively transmitting bio-signals over a distance using a wireless wearable device. In this paper, we describe a procedure for the design and fabrication of a wearable antenna based on embroidering conductive threads to clothing capable of transmitting electrocardiogram signals. 3D electromagnetic simulation software and embroidery software were used to design and fabricate the conductive thread-based antenna, respectively. The measurement results show that the reflection coefficient of the fabricated antenna prototype exhibits excellent antenna impedance matching characteristics of less than -10dB in the Zigbee 2.4GHz frequency band. We also verified that the electrocardiogram data could be effectively received and monitored in real-time by a receiver 220m away from the transmitter.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.6
• /
• pp.865-871
• /
• 2012

In this study, ambulatory electrocardiogram(ECG) signal and the rhythms of heart beats are visualized in terms of R-R intervals and Heart Rate Variability(HRV) in the environment of an android plaform. With this aim, Graphical User Interface(GUI) is implemented by executing multi-thread Java programming modules including ECG, heart-beats, tachogram and visualization unit. ECG signals are acquired in an android device by receiving the data from ambulatory ECG sensory system. Finite Impulse Response(FIR) filters are implemented to eliminate the baseline wandering noises contained in the ambulatory signals and DC-offset level in R-R interval data. With simulating the normal or stress emotional state of a subject, we can find the fact that HRV can be successfully estimated and visualized in an android smart phone platform.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.1
• /
• pp.70-76
• /
• 2019

Ultra Wideband (UWB) Radar is a high-resolution radar for short distance detection which uses signals transmitted and received by each antennas in order to detect a target. It is possible to detect the respiration and heartbeat of a person without contact It is getting more and more often utilized since it is not affected by physical environment. In this paper, we implement an algorithm to detect human respiration and heartbeat rate using UWB radar signal. We process radar signals reflected from human body using Median filter, Kalman filter, Band Pass filter and so on. We also use CZT to extract breathing and heart rate. ECG (Electrocardiogram) was used for comparison of heartbeat data and we confirm that each data of ECG and UWB Radar were more than 98% identical each other.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.1
• /
• pp.7-11
• /
• 2021

The electrocardiogram(ECG) and heart rates are essential for diagnosing heart disease. However, conventional portable ECG devices are possible to only measure heart rates or have limitations in how and where they are measured. In this paper, a portable ECG system in which ECG waveforms and heart rates are displayed on smartphone screens is developed. A smartphone is used as display equipment instead of a computer screen for continuous monitoring. The developed ECG system filters and amplifies detected analog ECG signals. Next, it converts the amplified analog ECG signals into digital signals, then transmits to the smartphone via Bluetooth communication. This ECG system can display and store biomedical signals on a smartphone through the application. As a result, the waveform and heart rates of the developed portable ECG system has been confirmed to be similar to those of existing medical devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.285-288
• /
• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Journal of Industrial Technology
• /
• v.32 no.A
• /
• pp.15-20
• /
• 2012

For emergency patients as heart disease, fast treatment is very important. This paper describes a smart phone software to detect emergency circumstance and request rescue. Detection of emergency condition of heart disease patients is based on physical motion and biological heart signals as electrocardiogram. Most smart phones have three axis acceleration sensor. On emergency condition, patients remain stationary. Thus the software detect stationary condition by using acceleration sensor data. For more precise detection, it combines electrocardiogram of patients. To request rescue, it sends help messages to designated persons. In addition, it generates emergency sound to surrounding people and plays a video of emergency measure that any person on the place can help the patient temporarily.

• ETRI Journal
• /
• v.35 no.5
• /
• pp.869-879
• /
• 2013

This study is related to the acquisition of physiological signals of human emotions and the recognition of human emotions using such physiological signals. To acquire physiological signals, seven emotions are evoked through stimuli. Regarding the induced emotions, the results of skin temperature, photoplethysmography, electrodermal activity, and an electrocardiogram are recorded and analyzed as physiological signals. The suitability and effectiveness of the stimuli are evaluated by the subjects themselves. To address the problem of the emotions not being recognized, we introduce a methodology for a recognizer using prototype-based learning and particle swarm optimization (PSO). The design involves two main phases: i) PSO selects the P% of the patterns to be treated as prototypes of the seven emotions; ii) PSO is instrumental in the formation of the core set of features. The experiments show that a suitable selection of prototypes and a substantial reduction of the feature space can be accomplished, and the recognizer formed in this manner is characterized by high recognition accuracy for the seven emotions using physiological signals.

• Smart Media Journal
• /
• v.8 no.3
• /
• pp.62-69
• /
• 2019

Electrocardiogram (ECG) signals cannot be counterfeited and can easily acquire signals from both wrists. In this paper, we propose a method of generating a coupling image using direction information of ECG signals as well as its usage in a personal recognition method. The proposed coupling image is generated by using forward ECG signal and rotated inverse ECG signal based on R-peak, and the generated coupling image shows a unique pattern and brightness. In addition, R-peak data is increased through the ECG signal calculation of the same beat, and it is thus possible to improve the recognition performance of the individual. The generated coupling image extracts characteristics of pattern and brightness by using the proposed convolutional neural network and reduces data size by using multiple pooling layers to improve network speed. The experiment uses public ECG data of 47 people and conducts comparative experiments using five networks with top 5 performance data among the public and the proposed networks. Experimental results show that the recognition performance of the proposed network is the highest with 99.28%, confirming potential of the personal recognition.