scholarly journals A Specialized System for Arrhythmia Detection for Basic Research in Cardiology

2021 ◽  
Author(s):  
Michael Kohlhaas ◽  
Lea Seidlmayer ◽  
Mathias Kaspar
Keyword(s):  
Early Detection ◽  
Mobile Devices ◽  
Cardiac Myocytes ◽  
Cardiac Arrhythmias ◽  
Basic Research ◽  
Use Cases ◽  
Experimental Setup ◽  
Arrhythmia Detection ◽  
Specialized System ◽  
Multiple Algorithms

The detection of cardiac arrhythmias has a long history in medicine, with current developments focusing on early detection using mobile devices. In basic research, however, the use cases and data differ greatly from the experimental setup. We developed a Python-based system to ease detection and analysis of arrhythmic sections in signals measured on extracted and stimulated cardiac myocytes. Multiple algorithms were integrated into the system, tested and evaluated. The best algorithm resulted in an F1-score of 0.97 and was primarily provided in the application.

Framework to Understand and Deploy AI-Based Smart CRM in the Airline Industry

2022 ◽  
pp. 154-165
Author(s):  
Vikram Bawa
Keyword(s):  
Mobile Devices ◽  
Airline Industry ◽  
Critical Analysis ◽  
Use Cases ◽  
Customer Acquisition ◽  
Customer Journey

This is the age of AI. Soon what customers think will be understood by the smart applications on their mobile devices and the information—most of which will be pre-processed based on the customer personas—will be available at the blink of an eye. In this chapter a critical analysis of how AI bolsters CRM capabilities in the airline industry is conducted. To understand that, AI capabilities are surveyed and its transformational effects on CRM and its impact on customer acquisition, retention, loyalty, and experience are explored in depth. In the end, a customer journey-based deployment framework is presented that supports the finding of the AI-CRM implementation use cases.

scholarly journals Stochastic initiation and termination of calcium-mediated triggered activity in cardiac myocytes

2017 ◽  
Vol 114 (3) ◽  
pp. E270-E279 ◽  
Author(s):  
Zhen Song ◽  
Zhilin Qu ◽  
Alain Karma
Keyword(s):  
Action Potential ◽  
Cardiac Myocytes ◽  
Cardiac Arrhythmias ◽  
Action Potentials ◽  
Waiting Times ◽  
Excitation Threshold ◽  
Triggered Activity ◽  
Random Events ◽  
Delayed Afterdepolarization ◽  
A Current

Cardiac myocytes normally initiate action potentials in response to a current stimulus that depolarizes the membrane above an excitation threshold. Aberrant excitation can also occur due to spontaneous calcium (Ca2+) release (SCR) from intracellular stores after the end of a preceding action potential. SCR drives the Na+/Ca2+ exchange current inducing a “delayed afterdepolarization” that can in turn trigger an action potential if the excitation threshold is reached. This “triggered activity” is known to cause arrhythmias, but how it is initiated and terminated is not understood. Using computer simulations of a ventricular myocyte model, we show that initiation and termination are inherently random events. We determine the probability of those events from statistical measurements of the number of beats before initiation and before termination, respectively, which follow geometric distributions. Moreover, we elucidate the origin of randomness by a statistical analysis of SCR events, which do not follow a Poisson process observed in other eukaryotic cells. Due to synchronization of Ca2+ releases during the action potential upstroke, waiting times of SCR events after the upstroke are narrowly distributed, whereas SCR amplitudes follow a broad normal distribution with a width determined by fluctuations in the number of independent Ca2+ wave foci. This distribution enables us to compute the probabilities of initiation and termination of bursts of triggered activity that are maintained by a positive feedback between the action potential upstroke and SCR. Our results establish a theoretical framework for interpreting complex and varied manifestations of triggered activity relevant to cardiac arrhythmias.

scholarly journals Energy efficient convolutional neural networks for arrhythmia detection

2021 ◽  
Author(s):  
Nikoletta Katsaouni ◽  
Florian Aul ◽  
Lukas Krischker ◽  
Sascha Schmalhofer ◽  
Lars Hedrich ◽  
...  
Keyword(s):  
Cardiac Arrhythmias ◽  
Energy Efficient ◽  
Model Parameters ◽  
Portable Devices ◽  
Ecg Monitoring ◽  
Heart Activity ◽  
Small Energy ◽  
Arrhythmia Detection ◽  
Long Time ◽  
Increasing Demand

Electrocardiograms (ECG) record the heart activity and are the most common and reliable method to detect cardiac arrhythmias, such as atrial fibrillation (AFib). Lately, many commercially available devices such as smartwatches are offering ECG monitoring. Therefore, there is increasing demand for designing deep learning models with the perspective to be physically implemented on these small portable devices with limited energy supply. In this paper, a workflow for the design of small, energy-efficient recurrent convolutional neural network (RCNN) architecture for AFib detection is proposed. However, the approach can be well generalized to every type of long time series. In contrast to previous studies, that demand thousands of additional network neurons and millions of extra model parameters, the logical steps for the generation of a CNN with only 114 trainable parameters are described. The model consists of a small segmented CNN in combination with an optimal energy classifier. The architectural decisions are made by using the energy consumption as a metric in an equally important way as the accuracy. The optimisation steps are focused on the software which can be embedded afterwards on a physical chip. Finally, a comparison with some previous relevant studies suggests that the widely used huge CNNs for similar tasks are mostly redundant and unessentially computationally expensive.

Early Detection of Symptomatic Paroxysmal Cardiac Arrhythmias by Trans-Telephonic ECG Monitoring: Impact on Diagnosis and Treatment of Atrial Fibrillation

2016 ◽  
Vol 27 (9) ◽  
pp. 1032-1037 ◽  
Author(s):  
JOHANNA ANCZYKOWSKI ◽  
STEPHAN WILLEMS ◽  
BORIS A. HOFFMANN ◽  
THOMAS MEINERTZ ◽  
STEFAN BLANKENBERG ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Early Detection ◽  
Cardiac Arrhythmias ◽  
Diagnosis And Treatment ◽  
Ecg Monitoring

scholarly journals Saving bandwidth and energy of mobile and IoT devices with link predictions

2020 ◽  
Author(s):  
Gabriel Orsini ◽  
Wolf Posdorfer ◽  
Winfried Lamersdorf
Keyword(s):  
Mobile Devices ◽  
Use Cases ◽  
Sensor Data ◽  
Software Infrastructure ◽  
Distributed Decision Making ◽  
Mobile Middleware ◽  
Novel Approach ◽  
Context Data ◽  
Iot Devices ◽  
The Internet Of Things

Abstract Use cases in the Internet of Things (IoT) and in mobile clouds often require the interaction of one or more mobile devices with their infrastructure to provide users with services. Ideally, this interaction is based on a reliable connection between the communicating devices, which is often not the case. Since most use cases do not adequately address this issue, service quality is often compromised. Aimed to address this issue, this paper proposes a novel approach to forecast the connectivity and bandwidth of mobile devices by applying machine learning to the context data recorded by the various sensors of the mobile device. This concept, designed as a microservice, has been implemented in the mobile middleware CloudAware, a system software infrastructure for mobile cloud computing that integrates easily with mobile operating systems, such as Android. We evaluated our approach with real sensor data and showed how to enable mobile devices in the IoT to make assumptions about their future connectivity, allowing for intelligent and distributed decision making on the mobile edge of the network.

scholarly journals Exploring biometric identification in FinTech applications based on the modified TAM

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jen Sheng Wang
Keyword(s):  
Technology Acceptance ◽  
Mobile Devices ◽  
New Technologies ◽  
Basic Research ◽  
User Acceptance ◽  
Biometric Identification ◽  
Analytic Hierarchy ◽  
Identification Methods ◽  
Perceived Trust ◽  
New Variables

AbstractIn recent years, biometric technologies have been widely embedded in mobile devices; these technologies were originally employed to enhance the security of mobile devices. With the rise of financial technology (FinTech), which uses mobile devices and applications as promotional platforms, biometrics has the important role of strengthening the identification of such applications for security. However, users still have privacy and trust concerns about biometrics. Previous studies have demonstrated that the technology acceptance model (TAM) can rigorously explain and predict user acceptance of new technologies. This study therefore modifies the TAM as a basic research architecture. Based on a literature review, we add two new variables, namely, “perceived privacy” and “perceived trust,” to extend the traditional TAM to examine user acceptance of biometric identification in FinTech applications. First, we apply the analytic hierarchy process (AHP) to evaluate the defined objects and relevant criteria of the research framework. Second, we use the AHP results in the scenario analysis to explore biometric identification methods that correspond to objects and criteria. The results indicate that face and voice recognition are the two most preferred identification methods in FinTech applications. In addition, there are significant changes in the results of the perceived trust and perceived privacy dominant scenarios.

scholarly journals FAT10 protects against ischemia-induced ventricular arrhythmia by decreasing Nedd4-2/Nav1.5 complex formation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xiao Liu ◽  
Jin Ge ◽  
Chen Chen ◽  
Yang Shen ◽  
Jinyan Xie ◽  
...  
Keyword(s):  
Ventricular Arrhythmia ◽  
Cardiac Myocytes ◽  
Cardiac Arrhythmias ◽  
Protein A ◽  
Human Leukocyte ◽  
Ubiquitin Proteasome System ◽  
Leukocyte Antigen ◽  
Ubiquitin E3 Ligase ◽  
Lysine Residues ◽  
Ubiquitin Proteasome

AbstractThe human leukocyte antigen F-associated transcript 10 (FAT10) is a member of the small ubiquitin-like protein family that binds to its target proteins and subjects them to degradation by the ubiquitin–proteasome system (UPS). In the heart, FAT10 plays a cardioprotective role and affects predisposition to cardiac arrhythmias after myocardial ischemia (MI). However, whether and how FAT10 influences cardiac arrhythmias is unknown. We investigated the role of FAT10 in regulating the sodium channel Nav1.5, a major regulator of cardiac arrhythmias. Fat10 was conditionally deleted in cardiac myocytes using Myh6-Cre and Fat10F/F mice (cFat10−/−). Compared with their wild-type littermates, cFat10−/− mice showed prolonged RR, PR, and corrected QT (QTc) intervals, were more likely to develop ventricular arrhythmia, and had increased mortality after MI. Patch-clamp studies showed that the peak Na+ current was reduced, and the late Na+ current was significantly augmented, resulting in a decreased action potential amplitude and delayed depolarization. Immunoblot and immunofluorescence analyses showed that the expression of the membrane protein Nav1.5 was decreased. Coimmunoprecipitation experiments demonstrated that FAT10 stabilized Nav1.5 expression by antagonizing Nav1.5 ubiquitination and degradation. Specifically, FAT10 bound to the lysine residues in the C-terminal fragments of Nav1.5 and decreased the binding of Nav1.5 to the Nedd4-2 protein, a ubiquitin E3 ligase, preventing degradation of the Nav1.5 protein. Collectively, our findings showed that deletion of the Fat10 in cardiac myocytes led to increased cardiac arrhythmias and increased mortality after MI. Thus, FAT10 protects against ischemia-induced ventricular arrhythmia by binding to Nav1.5 and preventing its Neddylation and degradation by the UPS after MI.

scholarly journals Model Perancangan Sistem Informasi Akuntansi Budidaya Perikanan Berbasis SAK EMKM dan Android

2018 ◽  
Vol 3 (2) ◽  
pp. 301-315
Author(s):  
S Supriyati ◽  
Dicky Muhamad Rizky
Keyword(s):  
Information System ◽  
Research Design ◽  
Research Method ◽  
Survey Methods ◽  
Data Gathering ◽  
Basic Research ◽  
Use Cases ◽  
Development Tools ◽  
Research Designs ◽  
The Times

The times when this is so rapid that we should always follow developments there. Moreover many systems of information circulating out there. But still many employers who have both information system for help in the recording in the operations. With these researchers are trying to make an information system based on android in the field of fisheries that will help entrepreneurs in the future. The research design was used in the survey is the design. This type of research is used in is basic research. This type of data is used in applicable data kualiatif. Types of research designs used in this research is descriptive-analistis. This research method used in survey methods, methods apply descriptive and exploratory methods. This data gathering techniques used in is observation and interview techniques. Model of development of the system that is used in is a waterfall. Development tools used in this system is to use the BPMN and diagrams use cases. This application is expected can help to manage every recording transactions that occurred in the business activities oprasional could make the books of financial something with the standards SAK EMKM.

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