Influence of psychological stress on Systolic-Diastolic Interval (SDI) interaction characteristics measured from the electrocardiogram (ECG) signal

Author(s):  
Chandan Karmakar ◽  
Mohammad Hasan Imam ◽  
Peng Li ◽  
Marimuthu Palaniswami
Author(s):  
Marius Rosu ◽  
Sever Pasca

Healthcare solutions using anytime, and anywhere remote healthcare surveillance devices, have become a major challenge. The patients with chronic diseases who need only therapeutic supervision are not advised to occupy a hospital bed. Using Wearable Wireless Body/Personal Area Network (WWBAN), intelligent monitoring of heart can supply information about medical conditions. Electrocardiogram (ECG) is the core reference in the diagnosis and medication process. An approach on healthcare solution WBAN based, for real-time ECG signal monitoring and long-term recording will be presented. Low-power wireless sensor nodes with local processing and encoding capabilities in order to achieve maximum mobility and flexibility are our main goal. ZigBee wireless technology will be used for transmission. Sensor device will be programmed to process locally the ECG signal and to raise an alert. Low-power and miniaturization are essential physical requirements.


Heart and Eye are two vital organs in the human system. By knowing the Electrocardiogram (ECG) and Electro-oculogram (EOG), one will be able to tell the stability of the heart and eye respectively. In this project, we have developed a circuit to pick the ECG and EOG signal using two wet electrodes. Here no reference electrode is used. EOG and ECG signals have been acquired from ten healthy subjects. The ECG signal is obtained from two positions, namely wrist and arm position respectively. The picked-up biomedical signal is recorded and heart rate information is extracted from ECG signal using the biomedical workbench. The result found to be promising and acquired stable EOG and ECG signal from the subjects. The total gain required for the arm position is higher than the wrist position for the ECG signal. The total gain necessary for the EOG signal is higher than the ECG signal since the ECG signal is in the range of millivolts whereas EOG signal in the range of microvolts. This two-electrode system is stable, cost-effective and portable while still maintaining high common-mode rejection ratio (CMRR).


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2835 ◽  
Author(s):  
Zhongjie Hou ◽  
Jinxi Xiang ◽  
Yonggui Dong ◽  
Xiaohui Xue ◽  
Hao Xiong ◽  
...  

A prototype of an electrocardiogram (ECG) signal acquisition system with multiple unipolar capacitively coupled electrodes is designed and experimentally tested. Capacitively coupled electrodes made of a standard printed circuit board (PCB) are used as the sensing electrodes. Different from the conventional measurement schematics, where one single lead ECG signal is acquired from a pair of sensing electrodes, the sensing electrodes in our approaches operate in a unipolar mode, i.e., the biopotential signals picked up by each sensing electrodes are amplified and sampled separately. Four unipolar electrodes are mounted on the backrest of a regular chair and therefore four channel of signals containing ECG information are sampled and processed. It is found that the qualities of ECG signal contained in the four channel are different from each other. In order to pick up the ECG signal, an index for quality evaluation, as well as for aggregation of multiple signals, is proposed based on phase space reconstruction. Experimental tests are carried out while subjects sitting on the chair and clothed. The results indicate that the ECG signals can be reliably obtained in such a unipolar way.


2021 ◽  
Vol 10 (1) ◽  
pp. 57
Author(s):  
Daniel Cuevas-González ◽  
Juan Pablo García-Vázquez ◽  
Miguel Bravo-Zanoguera ◽  
Roberto López-Avitia ◽  
Marco A. Reyna ◽  
...  

In this paper, we propose investigating the ability to integrate a portable Electrocardiogram (ECG) device to commercial platforms to analyze and visualize information hosted in the cloud. Our ECG system based on the ADX8232 microchip was evaluated regarding its performance of recordings of a synthetic ECG signal for periods of 1, 2, 12, 24, and 36 h on six different cloud services to investigate whether it maintains reliable ECG records. Our results show that there are few cloud services capable of 24 h or longer ECG recordings. But some existing services are limited to small file sizes of less than 1,000,000 lines or 100 MB, or approximately 45 min of an ECG recording at a sampling rate of 360 Hz, making it difficult an extended time monitoring. Cloud platforms reveal some limitations of storage and visualization in order to provide support to health care specialists to access information related to a patient at any time.


Author(s):  
Anukul Pandey ◽  
Barjinder Singh Saini ◽  
Butta Singh ◽  
Neetu Sood

Signal processing technology comprehends fundamental theory and implementations for processing data. The processed data is stored in different formats. The mechanism of electrocardiogram (ECG) steganography hides the secret information in the spatial or transformed domain. Patient information is embedded into the ECG signal without sacrificing the significant ECG signal quality. The chapter contributes to ECG steganography by investigating the Bernoulli's chaotic map for 2D ECG image steganography. The methodology adopted is 1) convert ECG signal into the 2D cover image, 2) the cover image is loaded to steganography encoder, and 3) secret key is shared with the steganography decoder. The proposed ECG steganography technique stores 1.5KB data inside ECG signal of 60 seconds at 360 samples/s, with percentage root mean square difference of less than 1%. This advanced 2D ECG steganography finds applications in real-world use which includes telemedicine or telecardiology.


2019 ◽  
Vol 29 (08) ◽  
pp. 2050133
Author(s):  
Anas Fouad Ahmed ◽  
Mohammed Abdulmunem Ahmed ◽  
Hussain Mustafa Bierk

This paper introduces an efficient and robust method for heartbeat detection based on the calculated angles between the successive samples of electrocardiogram (ECG) signal. The proposed approach involves three stages: filtering, computing the angles of the signal and thresholding. The suggested method is applied to two different types of ECG databases (QTDB and MIT-BIH). The results were compared with the other algorithms suggested in previous works. The proposed approach outperformed the other algorithms, in spite of its simplicity and their fast calculations. These features make it applicable in real-time ECG diagnostics systems. The suggested method was implemented in real-time using a low cost ECG acquisition system and it shows excellent performance.


Sign in / Sign up

Export Citation Format

Share Document