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Figure 5. Low-pass filter-EKG Through Sound-Card

The low-pass filter, presented in figure 5, allows signals with frequencies up to 34 Hz (cutoff frequency) to pass unaltered while it strongly attenuates those with frequencies exceeding the cut-off frequency. It is an active filter, of the butterworth sallen-key type which contains one of the four operational amplifiers of the TL084 integrated circuit.

Figure 3. The block diagram of the EKG amplifier

The EKG amplifier is made up of the following functional blocks (see Figure 3): • instrumentation amplifier • the circuit which performs the common-mode “right leg” reaction • high-pass filter • low-pass filter • output amplifier • power supply block

Figure 11. Practical realization of the EKG amplifier

The electronic circuit was assembled on two dubly copper placated test plates which were placed on a chassis made up of a hard plastic plate (Figure11). The preamplifier was armoured with an iron plate to reduce the influence of the electric network. The entire assembly was introduced in a plastic box specially designed for electronit fittings. The linking cables of the three electrodes are also armoured and connect to the electronic module via RCA sockets.

opencc-by-4.0Jan 2018View details →

Figure 18. Adjusting the signal input through the microphone socket-EKG Through Sound-Card

After that, the patient will be asked to wait for a few minutes, during which he will relax, and we will adjust the amplitude of the input signal into the computer’s sound-card, through the microphone socket. For this, we will use the program Sound Control from Start → Programs → Accessories → Entertaiment → Sound Control (Figure 18).

opencc-by-4.0Jan 2018View details →

Figure 2. Patient protection in relation to the parasite signals of electric lines-EKG Through Sound-Card

The recorder module applies the signal to the preamplifier’s non-inverted input and then passes through the limiter which establishes the maximum left or right limits of the stylus, to avoid breaking the recording tape. The power supply of the device contains mainly a convertor with an output transformer and a reaction transformer powered either from a network through a downward transformer followed by a rectifier and filter, or from an accumulator battery. To comply with the rules of patient protection, the supply for the electrocardiograph’s preamplifier is done floatingly according to the grounding null (Figure 2). Figure 2.

Figure 1. Bipolar limb derivations-EKG Through Sound-Card

Since the human body is a conductive mass, an electrode attached to the arm is the electric equivalent of a connection to the shoulder and an electrode attached to the foot is the equivalent of a connection to the abdomen. Using this principle, we obtain the following three standard bipolar limb derivations (Figure1): • Derivation I: negative electrode to the right hand and positive electrode to the left hand • Derivation II: positive electrode to the left foot, negative to the right hand • Derivation III: positive electrode to the left foot, negative to the left hand.

opencc-zeroJun 2024View details →

Dataset: First Trust Nasdaq Lux Digital Health Solutions ETF (EKG) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-by-4.0May 2023View details →

Interpretation of EKG with Image Recognition and Convolutional Neural Networks

Dataset used in the training and evaluation of "Interpretation of EKG with Image Recognition and Convolutional Neural Networks" Abstract: Electrocardiograms (EKG) form the backbone of all cardiovascular diagnosis, treatment and follow up. Given the pivotal role it plays in modern medicine, there have been multiple efforts to computerize the EKG interpretation with algorithms to improve efficiency and accuracy. Unfortunately, many of these algorithms are machine specific and run-on proprietary signals generated by that machine, hence not generalizable. We propose the development of an image recognition model which can be used to read standard EKG strips. A convolutional neural network (CNN) was trained to classify 12-lead EKGs between 7 clinically important diagnostic classes. An austere variation of the MobileNetV3 model was trained from the ground up on publicly available labeled training set. The precision per class varies from 52% to 91%. This is a novel approach to EKG interpretation as an image recognition problem.

opencc-by-4.0Jul 2023View details →

The evaluation of ActivityNet-EKG* knowledge graph

Evaluation of ActivityNet-EKG* knowledge graph for 286 multimodal documents.

ClinicalTrials.gov36/100

Atrial Fibrillation (AF) and Electrocardiogram (EKG) Interpretation Project ECHO

ClinicalTrials.gov study NCT05890274. IPD Sharing: YES. Countries: 1. Publications: 3.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov32/100

A Trial for the Earlier Diagnosis of Inferior Wall STEMI Using a Six-lead Handheld EKG Recorder

ClinicalTrials.gov study NCT05777083. IPD Sharing: NO. Countries: 1. Publications: 3.

ClinicalTrials.gov32/100

EKG Criteria and Identification of Acute Coronary Occlusion

ClinicalTrials.gov study NCT03863327. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.

ClinicalTrials.gov32/100

Continuous EKG Monitoring Using S-Patch Ex : Prospective Observational Study (S-patch Registry)

ClinicalTrials.gov study NCT05119725. IPD Sharing: NO. Countries: 1. Publications: 1.

ClinicalTrials.gov28/100

A Study to Detect Hyperkalemia Using Smartphone-enabled Electrocardiogram (EKG)

ClinicalTrials.gov study NCT05441852. IPD Sharing: NO. Countries: 1. Publications: 0.

Optimization of EKG Method for Long Term Central Venous Catheter Tip Placement

ClinicalTrials.gov study NCT01763801. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Observational Clinical Investigation of EKG Diagnostic Performance of the Apple Watch Augmented With an AI Algorithm

ClinicalTrials.gov study NCT05045456. IPD Sharing: NO. Countries: 1. Publications: 0.

The Efficacy of a Novel, Non-contact EKG in the NICU

ClinicalTrials.gov study NCT04269044. IPD Sharing: NO. Countries: 1. Publications: 0.

A Thorough EKG Safety Study of TA-1790 (Avanafil)

ClinicalTrials.gov study NCT00769041. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Analysis of Surface EKG Signals to Identify Myocardial Dysfunction in Patients at Risk for Coronary Artery Disease

ClinicalTrials.gov study NCT02560168. IPD Sharing: Not stated. Countries: 1. Publications: 0.

The Fetal EKG Study

ClinicalTrials.gov study NCT02320279. IPD Sharing: Not stated. Countries: 1. Publications: 0.