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https://www.readbyqxmd.com/read/29204376/mobile-cardiac-health-care-monitoring-and-notification-with-real-time-tachycardia-and-bradycardia-arrhythmia-detection
#1
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
https://www.readbyqxmd.com/read/29065597/patient-specific-deep-architectural-model-for-ecg-classification
#2
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
https://www.readbyqxmd.com/read/29060735/a-sub-nj-cmos-ecg-classifier-for-wireless-smart-sensor
#3
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
https://www.readbyqxmd.com/read/29060518/significance-of-modified-empirical-mode-decomposition-for-ecg-denoising
#4
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
https://www.readbyqxmd.com/read/29060376/a-wearable-sensor-based-multi-criteria-decision-system-for-real-time-seizure-detection
#5
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
https://www.readbyqxmd.com/read/29060102/electromyogram-based-method-to-secure-wireless-body-sensor-networks-for-rehabilitation-systems
#6
Guanghe Zhang, Oluwarotimi Williams Samuel, Fanghua Liu, Shixiong Chen, Hui Zhou, Haoshi Zhang, Guanglin Li
Wireless body sensor networks (WBSNs) provide a platform to track and monitor human health status as well as feedback to the user by capturing and processing certain physiological signals. Since WBSNs need to provide efficient health information privacy, their security has been identified as one of the major challenges, especially for rehabilitation systems. Conventionally, the random numbers (RNs) based on the inter-pulse intervals (IPIs) from electrocardiogram (ECG) recordings have been widely used to secure the data in WBSNs...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29059998/wireless-chest-wearable-vital-sign-monitoring-platform-for-hypertension
#7
G Janjua, D Guldenring, D Finlay, J McLaughlin
Hypertension, a silent killer, is the biggest challenge of the 21(st) century in public health agencies worldwide [1]. World Health Organization (WHO) statistic shows that the mortality rate of hypertension is 9.4 million per year and causes 55.3% of total deaths in cardiovascular (CV) patients [2]. Early detection and prevention of hypertension can significantly reduce the CV mortality. We are presenting a wireless chest wearable vital sign monitoring platform. It measures Electrocardiogram (ECG), Photoplethsmogram (PPG) and Ballistocardiogram (BCG) signals and sends data over Bluetooth low energy (BLE) to mobile phone-acts as a gateway...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29054505/biomonitor-2-pilot-study-early-experience-with-implantation-of-the-biotronik-biomonitor-2-implantable-cardiac-monitor
#8
Sze-Yuan Ooi, Ben Ng, Suresh Singarayar, Kevin Hellestrand, Peter Illes, Uwais Mohamed, Shakeeb Razak, Rukshen Weerasooriya
BACKGROUND: The BioMonitor 2 Pilot Study assessed the implantation procedure, the sensing amplitude and the remote monitoring transmission success rate of the second generation implantable cardiac monitor, the BioMonitor 2 (Biotronik, Berlin, Germany). METHODS: This was a prospective, multi-centre, single-arm, non-randomised study involving seven operators in five sites across Australia. Data were collected at implantation, during clinic visits at 1 week and 1 month post-implantation, and through wireless remote monitoring...
October 6, 2017: Heart, Lung & Circulation
https://www.readbyqxmd.com/read/29043502/an-integrated-approach-using-chaotic-map-sample-value-difference-method-for-electrocardiogram-steganography-and-ofdm-based-secured-patient-information-transmission
#9
Anukul Pandey, Barjinder Singh Saini, Butta Singh, Neetu Sood
This paper presents a patient's confidential data hiding scheme in electrocardiogram (ECG) signal and its subsequent wireless transmission. Patient's confidential data is embedded in ECG (called stego-ECG) using chaotic map and the sample value difference approach. The sample value difference approach effectually hides the patient's confidential data in ECG sample pairs at the predefined locations. The chaotic map generates these predefined locations through the use of selective control parameters. Subsequently, the wireless transmission of the stego-ECG is analyzed using the Orthogonal Frequency Division Multiplexing (OFDM) system in a Rayleigh fading scenario for telemedicine applications...
October 18, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/29037055/computer-aided-diagnosis-sensor-integrated-outdoor-shirts-for-real-time-heart-disease-monitoring
#10
Ji-Ae Park, Hee-Jeong Han, Jin-Chul Heo, Jong-Ha Lee
The typical method of monitoring arrhythmia is to use a body patch type sensor with a wet electrode. It has several problems caused by wet electrodes for long-term monitoring. Thus, a monitoring sensor integrated into clothes with a dry electrode is proposed. In this study, we develop a smart outdoor shirt equipped with a dry electrode electrocardiogram (ECG) sensor for a cardiac arrhythmia computer aided diagnosis system. The sensor can be inserted in a console close to the chest, charged, used to communicate wirelessly, and connected with a smartphone application...
October 16, 2017: Computer Assisted Surgery (Abingdon, England)
https://www.readbyqxmd.com/read/28954566/a-simple-encoding-method-for-sigma-delta-adc-based-biopotential-acquisition-systems
#11
Federico N Guerrero, Enrique M Spinelli
Sigma Delta analogue-to-digital converters allow acquiring the full dynamic range of biomedical signals at the electrodes, resulting in less complex hardware and increased measurement robustness. However, the increased data size per sample (typically 24 bits) demands the transmission of extremely large volumes of data across the isolation barrier, thus increasing power consumption on the patient side. This problem is accentuated when a large number of channels is used as in current 128-256 electrodes biopotential acquisition systems, that usually opt for an optic fibre link to the computer...
September 28, 2017: Journal of Medical Engineering & Technology
https://www.readbyqxmd.com/read/28928046/new-directions-for-ambulatory-monitoring-following-2017-hrs-ishne-expert-consensus
#12
Emanuela T Locati
The main role of ambulatory electrocardiography (AECG) in clinical practice is to detect and characterize the behavior of cardiac electrical activity during ordinary daily life activities. Because certain rhythm abnormalities may be infrequent and paroxysmal, and may occur only during sleep or in association with mental, emotional, or exercise-induced perturbation in cardiac function, AECG needs to be recorded over a long period of time, originally lasting 24h and now expanding up to several weeks and even to months...
August 12, 2017: Journal of Electrocardiology
https://www.readbyqxmd.com/read/28920895/matched-filtering-for-heart-rate-estimation-on-compressive-sensing-ecg-measurements
#13
Giulia Da Poian, Christopher J Rozell, Riccardo Bernardini, Roberto Rinaldo, Gari D Clifford
OBJECTIVE: Compressive Sensing (CS) has recently been applied as a low complexity compression framework for long-term monitoring of electrocardiogram signals using Wireless Body Sensor Networks. Long-term recording of ECG signals can be useful for diagnostic purposes and to monitor the evolution of several widespread diseases. In particular, beat to beat intervals provide important clinical information, and these can be derived from the ECG signal by computing the distance between QRS complexes (R-peaks)...
September 14, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28900815/wavelet-based-encoding-scheme-for-controlling-size-of-compressed-ecg-segments-in-telecardiology-systems
#14
Asiya M Al-Busaidi, Lazhar Khriji, Farid Touati, Mohd Fadlee Rasid, Adel Ben Mnaouer
One of the major issues in time-critical medical applications using wireless technology is the size of the payload packet, which is generally designed to be very small to improve the transmission process. Using small packets to transmit continuous ECG data is still costly. Thus, data compression is commonly used to reduce the huge amount of ECG data transmitted through telecardiology devices. In this paper, a new ECG compression scheme is introduced to ensure that the compressed ECG segments fit into the available limited payload packets, while maintaining a fixed CR to preserve the diagnostic information...
September 12, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28813017/a-wireless-exg-interface-for-patch-type-ecg-holter-and-emg-controlled-robot-hand
#15
Kwangmuk Lee, Yun Young Choi, Dae Jung Kim, Hee Young Chae, Kyeonghwan Park, Young Min Oh, Sung Hun Woo, Jae Joon Kim
This paper presents a wearable electrophysiological interface with enhanced immunity to motion artifacts. Anti-artifact schemes, including a patch-type modular structure and real-time automatic level adjustment, are proposed and verified in two wireless system prototypes of a patch-type electrocardiogram (ECG) module and an electromyogram (EMG)-based robot-hand controller. Their common ExG readout integrated circuit (ROIC), which is reconfigurable for multiple physiological interfaces, is designed and fabricated in a 0...
August 16, 2017: Sensors
https://www.readbyqxmd.com/read/28783079/an-ultra-low-power-turning-angle-based-biomedical-signal-compression-engine-with-adaptive-threshold-tuning
#16
Jun Zhou, Chao Wang
Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems...
August 6, 2017: Sensors
https://www.readbyqxmd.com/read/28546862/block-sparsity-based-joint-compressed-sensing-recovery-of-multi-channel-ecg-signals
#17
Anurag Singh, Samarendra Dandapat
In recent years, compressed sensing (CS) has emerged as an effective alternative to conventional wavelet based data compression techniques. This is due to its simple and energy-efficient data reduction procedure, which makes it suitable for resource-constrained wireless body area network (WBAN)-enabled electrocardiogram (ECG) telemonitoring applications. Both spatial and temporal correlations exist simultaneously in multi-channel ECG (MECG) signals. Exploitation of both types of correlations is very important in CS-based ECG telemonitoring systems for better performance...
April 2017: Healthcare Technology Letters
https://www.readbyqxmd.com/read/28420158/intelligent-medical-garments-with-graphene-functionalized-smart-cloth-ecg-sensors
#18
Murat Kaya Yapici, Tamador Elboshra Alkhidir
Biopotential signals are recorded mostly by using sticky, pre-gelled electrodes, which are not ideal for wearable, point-of-care monitoring where the usability of the personalized medical device depends critically on the level of comfort and wearability of the electrodes. We report a fully-wearable medical garment for mobile monitoring of cardiac biopotentials from the wrists or the neck with minimum restriction to regular clothing habits. The wearable prototype is based on elastic bands with graphene functionalized, textile electrodes and battery-powered, low-cost electronics for signal acquisition and wireless transmission...
April 16, 2017: Sensors
https://www.readbyqxmd.com/read/28368836/dreamer-a-database-for-emotion-recognition-through-eeg-and-ecg-signals-from-wireless-low-cost-off-the-shelf-devices
#19
Stamos Katsigiannis, Naeem Ramzan
In this work, we present DREAMER, a multi-modal database consisting of electroencephalogram (EEG) and electrocardiogram (ECG) signals recorded during affect elicitation by means of audio-visual stimuli. Signals from 23 participants were recorded along with the participants self-assessment of their affective state after each stimuli, in terms of valence, arousal, and dominance. All the signals were captured using portable, wearable, wireless, low-cost and off-the-shelf equipment that has the potential to allow the use of affective computing methods in everyday applications...
March 27, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28269356/real-time-physiological-and-facial-monitoring-for-safe-driving
#20
Yu-Lung Chang, Yen-Cheng Feng, Oscal T-C Chen
This work is to develop an intelligent driver-assistance system which can perceive the physiological state of a driver to avoid fatigue driving. The proposed system includes a camera, a wireless ElectroCardioGram (ECG) sensor patch, and a computation platform. The camera in front of a driver is to catch a face image which is processed to obtain features of a mouth for identifying a yawn. The sensor patch records ECG signals which are computed to yield six Heart Rate Variability (HRV) parameters. Seven healthy subjects of 6 males and 1 female had individually driven a car, which was embedded with our system, for 3 hours at a well-known route, mostly in a freeway road...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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