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Wireless of ECG

J A Michel-Macarty, M A Murillo-Escobar, R M López-Gutiérrez, C Cruz-Hernández, L Cardoza-Avendaño
BACKGROUND AND OBJECTIVES: Currently, telemedicine is levered upon the improvement in communication network technology such as Body Area Sensor Networks (BASN) to provided biomedicine solutions. Nevertheless, information security is an important issue since biomedical data is exchanged through insecure channels, which exposes private information that can be intercepted by malicious intruder. Therefore, secure communication protocols for multiuser networks in telemedicine applications are a big challenge...
August 2018: Computer Methods and Programs in Biomedicine
Ming Tang, Jian Yao, Zekuan Chen, Hai Huang, Chenge Geng
Electrocardiogram (ECG) detection is a routine and effective cardiac problem detection project. Traditional electrocardiogram detection has limitations in cardiac arrhythmia and other heart disease detection and diagnosis, such as effectiveness, real-time and so on. Based on the advanced mobile networking and wearable design concept, this paper designs and implements a dynamic ECG real-time monitoring system with low power embedded system and Bluetooth 4.0 wireless communication. Its main functions include 24-hour dynamic ECG signal real-time acquisition, processing, wireless communication, display and storage, real-time analysis of typical arrhythmia, recording and alarm, professional doctors real-time reading and diagnosis, dynamic ECG sharing and cloud platform automatic analysis and diagnosis...
May 30, 2018: Zhongguo Yi Liao Qi Xie za Zhi, Chinese Journal of Medical Instrumentation
Aasia Moqeem, Mirza Baig, Hamid Gholamhosseini, Farhaan Mirza, Maria Lindén
This research involves the design and development of a novel Android smartphone application for real-time vital signs monitoring and decision support. The proposed application integrates market available, wireless and Bluetooth connected medical devices for collecting vital signs. The medical device data collected by the app includes heart rate, oxygen saturation and electrocardiograph (ECG). The collated data is streamed/displayed on the smartphone in real-time. This application was designed by adopting six screens approach (6S) mobile development framework and focused on user-centered approach and considered clinicians-as-a-user...
2018: Studies in Health Technology and Informatics
Guojing Wang, Weidong Wang, Lei Yu
Based on the heart rate monitor front end AD8232 chips and Zigbee system solutions CC2530 single chip, the wireless ECG monitor has been realized in order to implement the acquisition, processing and wireless transmission of electrocardiogram signal. Meanwhile, the real-time heart rate has been calculated and wirelessly transmitted. The wireless ECG monitor is characterized by low power consumption, small size and simple operation. It can be seen from the experimental results that the wireless ECG monitor designed in this paper can successfully obtain favorable ECG data and real-time heart rate data and display it...
January 30, 2018: Zhongguo Yi Liao Qi Xie za Zhi, Chinese Journal of Medical Instrumentation
Ashish Kumar, Rama Komaragiri, Manjeet Kumar
Heart rate monitoring and therapeutic devices include real-time sensing capabilities reflecting the state of the heart. Current circuitry can be interpreted as a cardiac electrical signal compression algorithm representing the time signal information into a single event description of the cardiac activity. It is observed that some detection techniques developed for ECG signal detection like artificial neural network, genetic algorithm, Hilbert transform, hidden Markov model are some sophisticated algorithms which provide suitable results but their implementation on a silicon chip is very complicated...
May 22, 2018: ISA Transactions
Xin Liu, Qisong Wang, Dan Liu, Yuan Wang, Yan Zhang, Ou Bai, Jinwei Sun
BACKGROUND: Human emotion classification is traditionally achieved using multi-channel electroencephalogram (EEG) signal, which requires costly equipment and complex classification algorithms. OBJECTIVE: The experiments can be implemented in the laboratory environment equipped with high-performance computers for the online analysis; this will hinder the usability in practical applications. METHODS: Considering that other physiological signals are also associated with emotional changes, this paper proposes to use a wearable, wireless system to acquire a single-channel electroencephalogram signal, respiration, electrocardiogram (ECG) signal, and body postures to explore the relationship between these signals and the human emotions...
April 27, 2018: Technology and Health Care: Official Journal of the European Society for Engineering and Medicine
Xuanyu Lu, Maolin Pan, Yang Yu
Cardiovascular disease is the first cause of death around the world. In accomplishing quick and accurate diagnosis, automatic electrocardiogram (ECG) analysis algorithm plays an important role, whose first step is QRS detection. The threshold algorithm of QRS complex detection is known for its high-speed computation and minimized memory storage. In this mobile era, threshold algorithm can be easily transported into portable, wearable, and wireless ECG systems. However, the detection rate of the threshold algorithm still calls for improvement...
2018: Journal of Healthcare Engineering
Kan Luo, Zhipeng Cai, Keqin Du, Fumin Zou, Xiangyu Zhang, Jianqing Li
Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run...
2018: Journal of Healthcare Engineering
Ali Hassan Sodhro, Arun Kumar Sangaiah, Gul Hassan Sodhro, Sonia Lohano, Sandeep Pirbhulal
Rapid progress and emerging trends in miniaturized medical devices have enabled the un-obtrusive monitoring of physiological signals and daily activities of everyone's life in a prominent and pervasive manner. Due to the power-constrained nature of conventional wearable sensor devices during ubiquitous sensing (US), energy-efficiency has become one of the highly demanding and debatable issues in healthcare. This paper develops a single chip-based wearable wireless electrocardiogram (ECG) monitoring system by adopting analog front end (AFE) chip model ADS1292R from Texas Instruments...
March 20, 2018: Sensors
Jeevan K Pant, Sridhar Krishnan
OBJECTIVE: To present a new compressive sensing (CS)-based method for the acquisition of ECG signals and for robust estimation of heart-rate variability (HRV) parameters from compressively sensed measurements with high compression ratio. APPROACH: CS is used in the biosensor to compress the ECG signal. Estimation of the locations of QRS segments is carried out by applying two algorithms on the compressed measurements. The first algorithm reconstructs the ECG signal by enforcing a block-sparse structure on the first-order difference of the signal, so the transient QRS segments are significantly emphasized on the first-order difference of the signal...
March 15, 2018: Physiological Measurement
Noa Betzalel, Paul Ben Ishai, Yuri Feldman
In the interaction of microwave radiation and human beings, the skin is traditionally considered as just an absorbing sponge stratum filled with water. In previous works, we showed that this view is flawed when we demonstrated that the coiled portion of the sweat duct in upper skin layer is regarded as a helical antenna in the sub-THz band. Experimentally we showed that the reflectance of the human skin in the sub-THz region depends on the intensity of perspiration, i.e. sweat duct's conductivity, and correlates with levels of human stress (physical, mental and emotional)...
May 2018: Environmental Research
Vikas Mishra, Nicole M Gautier, Edward Glasscock
In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described...
January 29, 2018: Journal of Visualized Experiments: JoVE
Amale Ankhili, Xuyuan Tao, Cédric Cochrane, David Coulon, Vladan Koncar
A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance...
February 7, 2018: Materials
Jonathan C Erickson, James A Hayes, Mauricio Bustamante, Rajwol Joshi, Alfred Rwagaju, Niranchan Paskaranandavadivel, Timothy R Angeli
OBJECTIVE: Multi-channel electrical recordings of physiologically generated signals are common to a wide range of biomedical fields. The aim of this work was to develop, validate, and demonstrate the practical utility of a high-quality, low-cost 32/64-channel bioamplifier system with real-time wireless data streaming capability. APPROACH: The new 'Intsy' system integrates three main off-the-shelf hardware components: (1) Intan RHD2132 bioamplifier; (2) Teensy 3...
March 29, 2018: Physiological Measurement
Jin-Chul Heo, Beomjoon Kim, Yoon-Nyun Kim, Dae-Kwang Kim, Jong-Ha Lee
Prolonged monitoring by cardiac electrocardiogram (ECG) sensors is useful for patients with emergency heart conditions. However, implant monitoring systems are limited by lack of tissue biocompatibility. Here, we developed an implantable ECG sensor for real-time monitoring of ventricular fibrillation and evaluated its biocompatibility using an animal model. The implantable sensor comprised transplant sensors with two electrodes, a wireless power transmission system, and a monitoring system. The sensor was inserted into the subcutaneous tissue of the abdominal area and operated for 1 h/day for 5 days using a wireless power system...
December 14, 2017: Sensors
Mina Golzar, Faranak Fotouhi-Ghazvini, Hossein Rabbani, Fahimeh Sadat Zakeri
Background: The increasing trend of heart disease has turned the attention of researchers toward the use of portable connected technologies. The necessity of continuous special care for cardiovascular patients is an inevitable fact. Methods: In this research, a new wireless electrocardiographic (ECG) signal-monitoring system based on smartphone is presented. This system has two main sections. The first section consists of a sensor which receives ECG signals via an amplifier, then filters and digitizes the signal, and prepares it to be transmitted...
October 2017: Journal of Medical Signals and Sensors
Kan Luo, Jianqing Li, Zhigang Wang, Alfred Cuschieri
Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sensor network- (WBSN-) enabled ECG monitoring puts forward a higher-level demand for this traditional ECG analysis task. Previously reported methods mainly addressed this requirement with the applications of a shallow structured classifier and expert-designed features. In this study, modified frequency slice wavelet transform (MFSWT) was firstly employed to produce the time-frequency image for heartbeat signal...
2017: Journal of Healthcare Engineering
Paul Chollet, Remi Pallas, Cyril Lahuec, Matthieu Arzel, Fabrice Seguin
Body area sensor networks hold the promise of more efficient and cheaper medical care services through the constant monitoring of physiological markers such as heart beats. Continuously transmitting the electrocardiogram (ECG) signal requires most of the wireless ECG sensor energy budget. This paper presents the analog implantation of a classifier for ECG signals that can be embedded onto a sensor. The classifier is a sparse neural associative memory. It is implemented using the ST 65 nm CMOS technology and requires only 234 pJ per classification while achieving a 93...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Pratik Singh, S Shahnawazuddin, Gayadhar Pradhan
The primary objective of the presented work is to exploit the power of modified empirical mode decomposition (M-EMD) for the denoising of ECG signals. It is well known that the ECG signals get corrupted by a number of noises during the recording process. Especially, during wireless ECG recording and ambulatory patient monitoring, the signal gets corrupted by additive white Gaussian noise (AWGN). Over the years, several techniques have been proposed for ECG denoising. Among those, empirical mode decomposition (EMD) and nonlocal means (NLM) algorithm are noted to be quite effective...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abdullah Ahmed, Waqas Ahmad, Muhammad Jazib Khan, Shoaib Ahmed Siddiqui, Hammad M Cheema
This paper presents a wireless, low power and low cost two part wearable for real-time epileptic seizure detection. Using parameters of Electro-cardiograph (ECG), Electro-dermal Activity (EDA), body motion and breathing rate (BR), a novel multi-criteria-decision-system (MCDS) is proposed that reduces false alarms and true negatives. The combination of a chest and hand worn wearable continuously senses these parameters transmitting the data to a smart phone application via BLE 4.0 where long-short-term-memory (LSTM) based anomaly detection algorithms and logistic classifiers decide on the occurrence of the seizure in real time...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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