• Title/Summary/Keyword: Real-time cardiac health monitoring

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Portable Electrocardiograph and Smart Device-based Heart Health Monitoring and Risk Notification System (휴대용 심전도 측정기와 스마트 기기 기반의 심건강 모니터링 및 위험도 알림 시스템)

  • Cho, Jinsoo
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.2
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    • pp.73-78
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    • 2013
  • This paper proposes a portable electrocardiograph and smart device-based heart health monitoring and risk notification system. The proposed system consists of a portable electrocardiograph and a smart device for a system user, and a web-based monitoring system for observers. This system can improve the convenience and efficiency of measurement by using a light-weight portable electrocardiograph and a smart device. In addition, any authorized person such as caregiver or family member who is not related to medical institution can monitor users'heart health in real-time using the web-based monitoring system. Therefore, a user and authorized remote observers can efficiently monitor and manage user's heart health in daily-life even without any medical institution's help, and can preemptively deal with any possible dangerous situations, such as degeneration of a cardiac disorder and sudden cardiac death.

Real-Time Automated Cardiac Health Monitoring by Combination of Active Learning and Adaptive Feature Selection

  • Bashir, Mohamed Ezzeldin A.;Shon, Ho Sun;Lee, Dong Gyu;Kim, Hyeongsoo;Ryu, Keun Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.1
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    • pp.99-118
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    • 2013
  • Electrocardiograms (ECGs) are widely used by clinicians to identify the functional status of the heart. Thus, there is considerable interest in automated systems for real-time monitoring of arrhythmia. However, intra- and inter-patient variability as well as the computational limits of real-time monitoring poses significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is therefore a promising new intelligent diagnostic tool.

Implementation of Real-time Heart Activity Monitoring System Using Heart Sound (심음을 이용한 실시간 심장 활동 상태 모니터링 시스템 구현)

  • Kim, Jin-Hwan;Noh, Yun-Hong;Jeong, Do-Un
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.1
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    • pp.14-19
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    • 2018
  • Recently, the smart health care industry has been rising rapidly and interest and efforts for public health have been greatly increased. As a result, the public does not visit medical specialists and medical facilities, but the desire to check their health condition in everyday life is increased. Therefore, many domestic and foreign companies continuously research and develop wearable devices that can measure body activity information anytime and anywhere And the market. Especially, it is used for heart activity measurement device using pulse wave sensor and electrocardiogram sensor. However, in this study, a monitoring system that can detect cardiac activity using cardiac sounds, heart sound measurement rather than pulse wave measurement and electrocardiogram measurement, was performed and its performance was evaluated. Experimental results confirmed the predictability of cardiac heart rate and heart valve disease during daily living.

Wearable and Implantable Sensors for Cardiovascular Monitoring: A Review

  • Jazba Asad;Jawwad Ibrahim
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.171-185
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    • 2023
  • The cardiovascular syndrome is the dominant reason for death and the number of deaths due to this syndrome has greatly increased recently. Regular cardiac monitoring is crucial in controlling heart parameters, particularly for initial examination and precautions. The quantity of cardiac patients is rising each day and it would increase the load of work for doctors/nurses in handling the patients' situation. Hence, it needed a solution that might benefit doctors/nurses in monitoring the improvement of the health condition of patients in real-time and likewise assure decreasing medical treatment expenses. Regular heart monitoring via wireless body area networks (WBANs) including implantable and wearable medical devices is contemplated as a life-changing technique for medical assistance. This article focuses on the latest development in wearable and implantable devices for cardiovascular monitoring. First, we go through the wearable devices for the electrocardiogram (ECG) monitoring. Then, we reviewed the implantable devices for Blood Pressure (BP) monitoring. Subsequently, the evaluation of leading wearable and implantable sensors for heart monitoring mentioned over the previous six years, the current article provides uncertain direction concerning the description of diagnostic effectiveness, thus intending on making discussion in the technical communal to permit aimed at the formation of well-designed techniques. The article is concluded by debating several technical issues in wearable and implantable technology and their possible potential solutions for conquering these challenges.

Minimizing MR Gradient Artefacts on ECG Signals for Cardiac Gating based on an Adaptive Digital Filter (적응 디지털 필터 기반의 MRI Cardiac Gating을 위한 심전도 신호의 MR Gradient 잡음 최소화 방법)

  • Park, Ho-Dong;Jang, Bong-Ryeol;Lee, Kyoung-Joung
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.817-818
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    • 2006
  • In Magnetic Resonance Imaging(MRI), the QRS complex of ECG is used as a trigger signal for MRI scan. But, gradient and RF(radio frequency) artifacts which are caused to static and dynamic field in MRI scanner cause interference in the ECG. Also, the signal shape of theses artifacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false gating of the MRI. In case of using general FIR or IIR band-pass filters for minimizing the artifacts, artifact-reduction-ratio is not excellent. So, an adaptive real-time digital filter is proposed for reduction of noise by gradient and RF(radio frequency) artifacts. The proposed filter for MRI-Gating is based on the noise-canceller with NLMS(Normalized Least Mean Square) algorithm. The reference signals of the adaptive noise canceller are a combination of the noisy three channel ECG signals. In conclusions, the proposed method showed the acceptable quality of ECG signal with sufficient SNR for gating the MRI and possibility of real time implementation.

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An Exploratory Research for Development of Design of Sensor-based Smart Clothing - Focused on the Healthcare Clothing Based on Bio-monitoring Technology - (센서 기반형 스마트 의류의 디자인 개발을 위한 탐색적 연구 - 생체 신호 센서 기술에 기반한 건강관리용 의류를 중심으로 -)

  • Cho Ha-Kyung;Lee Joo-Hyeon;Lee Chung-Keun;Lee Myoung-Ho
    • Science of Emotion and Sensibility
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    • v.9 no.2
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    • pp.141-150
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    • 2006
  • Since the late 1990s, 'smart clothing' has been developed in a various way to meet the need of users and to help people more friendly interact with computers through its various designs. Recently, various applications of smart clothing concept have been presented by researchers. Among the various applications, smart clothing with a health care system is most likely to gain the highest demand rate in the market. Among them, smart clothing for check-up of health status with its sensors is expected to sell better than other types of smart clothing on the market. Under this circumstance, research and development for this field have been accelerated furthermore. This research institution has invented biometric sensors suitable for the smart clothing, and has developed a design to diagnose various diseases such as cardiac disorder and respiratory diseases. The newly developed smart clothing in this study looks similar to the previous inventions, but people can feel more comfortable in it with its fabric interaction built in it. When people wear it, the health status of the wearers is diagnosed and its signals are transmitted to the connected computer so the result can be easily monitored in real time. This smart clothing is a new kind of clothing as a supporting system for preventing various cardiac disorder and respiratory diseases using its biometric sensor built-in, and is also an archetype to show how smart clothing can work on the market.

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