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Predicting the Risk of Depression Based on ECG Using RNN

Sumaiya Tarannum Noor, Syeda Tasmiah Asad, Mohammad Monirujjaman Khan, Gurjot Singh Gaba, Jehad F. Al-Amri, Mehedi Masud, Syed Hassan Ahmed
2021 Computational Intelligence and Neuroscience  
In studies, it was found that patients suffering from depression may have a different kind of heartbeat than the normal ones. In most cases, it is PVC (Premature Ventricular Contraction) heartbeats.  ...  Therefore, the target is to predict abnormal heartbeats and PVC heartbeats.  ...  Here, in this system, the ECG heartbeat rate data is used as the dataset.  ... 
doi:10.1155/2021/1299870 fatcat:vkktpffzxbdx7herwf6czp5r3m

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers

Huifang Huang, Jie Liu, Qiang Zhu, Ruiping Wang, Guangshu Hu
2014 BioMedical Engineering OnLine  
Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data.  ...  The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases.  ...  Therefore, the results in this study provided a valid assessment of the predictive capability for unknown data.  ... 
doi:10.1186/1475-925x-13-72 pmid:24903422 pmcid:PMC4086987 fatcat:sjyihbxuuzhapiqiaimsz37zfa

A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

Huifang Huang, Jie Liu, Qiang Zhu, Ruiping Wang, Guangshu Hu
2014 BioMedical Engineering OnLine  
In addition, this classification process was relatively fast. Conclusions: A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB.  ...  This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods.  ...  In clinical applications, labeled ECG data are used to build a heartbeat classification system. Then this system is used to determine the types of heartbeats in unknown patients' ECG recordings.  ... 
doi:10.1186/1475-925x-13-90 pmid:24981916 pmcid:PMC4085082 fatcat:z6a3gtsnorel5i2c2mk2lk3dpq

A Double-Layer Heartbeat Detection Algorithm Orienting to Embedded Heterogeneous Cluster

Zhu Wei, Zhuang Yi, Xu Chaoqun
2015 International Journal of Grid and Distributed Computing  
The experiment results show that, DLHB is more accurate in prediction compared with DHB, and can detect faults concurrently occurring on multiple nodes with less time compared with the heartbeat ring algorithm  ...  This algorithm divides the nodes in the embedded heterogeneous cluster into different areas by their physical positions. In each node area, a node is selected as the master control node.  ...  Each node in the cluster will inform each other of its own health status by sending a network exchange data packet called the heartbeat packet on a regular basis.  ... 
doi:10.14257/ijgdc.2015.8.3.16 fatcat:mie3tkva2fam3fyduexo6va6vi

Analysis on Healthcare System using IoT

Su Hlaing Phyo, Kyaw Zin Latt
2019 Zenodo  
Node MCU board collects temperature and heartbeat data from the sensors and transfer wirelessly to IoT website via internet connection 1 .  ...  This data can be transmitted to the data set linked with SPSS software and this software can be calculated the future data for people using linear regression method.  ...  Survey data insert input data in my research to be predicted future data. Input data is used to analyse in SPSS software by using linear regression method.  ... 
doi:10.5281/zenodo.3591056 fatcat:mrprnoyrsfde5gtnqnnno6ya6a

Interoceptive Ability Predicts Survival on a London Trading Floor

Narayanan Kandasamy, Sarah N. Garfinkel, Lionel Page, Ben Hardy, Hugo D. Critchley, Mark Gurnell, John M. Coates
2016 Scientific Reports  
Do individual diferences in interoceptive ability predict performance in actual high-stakes risk taking?  ...  Studies have found that higher scores on heartbeat detection predict superior performance on some laboratory gambling tasks 22-25 .  ...  If heartbeat detection score predicts traders' P&L, does it also predict how long traders survive in the inancial markets?  ... 
doi:10.1038/srep32986 pmid:27641692 pmcid:PMC5027524 fatcat:talutnnzdbba5jridoehamn2pq

A Heartbeat Classifier for Continuous Prediction Using a Wearable Device

Eko Sakti Pramukantoro, Akio Gofuku
2022 Sensors  
This paper proposes a heartbeat classifier based on RR interval data for real-time and continuous heartbeat monitoring using the Polar H10 wearable device.  ...  It has gold-standard heartbeat recording and communication ability but still lacks analytical processing of the recorded data.  ...  Acknowledgments: We would like to thank all the colleagues working in the same laboratory who were involved in the experiment. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22145080 pmid:35890769 pmcid:PMC9320854 fatcat:bu5f6ljlnzeppewww4ff337gmy

IOT based Heart Disease Prediction

Mrs. Shital. P. Chattar
2021 International Journal for Research in Applied Science and Engineering Technology  
This paper uses various data mining techniques in an effort to help diagnose the disease in question.  ...  As these systems generate a large amount of data in various forms but this data is rarely visited and remains unused. Therefore, in this process much effort is required to make wise decisions.  ...  The value of machine learning in health care is its ability to process large data sets beyond human capacity, and to reliably translate that data into clinical data that assists physicians in planning  ... 
doi:10.22214/ijraset.2021.32976 fatcat:pnng2mlazrc33fnk7hfuxucnbi

Automatic Classification of Arrhythmic Heartbeats using the Linear Prediction Model

Chun-Cheng Lin, Weichih Hu, Chunmin Yang
2013 International Conference on Computing in Cardiology  
The ECG data were divided into training and testing datasets, each containing about 50,000 heartbeats.  ...  This study developed an automatic heartbeat classification system based on the morphological features extracted using the first-order linear prediction model with two optimal filter coefficients and the  ...  Methods of heartbeat classification ECG data All the ECG data used in this study were obtained from the MIT-BIH Arrhythmia Database [9] which contains common and life-threatening arrhythmic heartbeats  ... 
dblp:conf/cinc/LinHY13 fatcat:2cklde5ymfgpbkdxz6hy6os35q

Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach

Vijayakumar T, Vinothkanna R, Duraipandian M
2021 Journal of Artificial Intelligence and Capsule Networks  
Then the classification of more amount of heartbeat for different category of normal, abnormal, irregular heartbeats to detect cardiovascular diseases.  ...  This interference is high in many handheld devices which can be eliminated by de-noising filters.  ...  The data is filtered with a range of frequencies is mentioned as equation below, here is used to classify the data based on the training set and class labels in the proposed structure and it helps to predicts  ... 
doi:10.36548/jaicn.2021.1.001 fatcat:vd3dnm75g5cl7g2zlfb55f5qmm

Simultaneous ECG Heartbeat Segmentation and Classification with Feature Fusion and Long Term Context Dependencies [chapter]

Xi Qiu, Shen Liang, Yanchun Zhang
2020 Lecture Notes in Computer Science  
Among them, most methods work in three steps: preprocessing, heartbeat segmentation and beat-wise classification. However, this methodology has two drawbacks.  ...  To achieve simultaneous segmentation and classification, we present a Faster R-CNN based model that has been customized to handle ECG data.  ...  Region Pooling Block and Region Classification Network In the heartbeat classification task, the region pooling block generates heartbeat feature maps for the predicted heartbeat regions [2] .  ... 
doi:10.1007/978-3-030-47436-2_28 fatcat:ujse4deo6vf4hfef7uj346mhde

Cardio-audio synchronization drives neural surprise response

Christian Pfeiffer, Marzia De Lucia
2017 Scientific Reports  
Implicit neural monitoring of temporal regularities across interoceptive and exteroceptive signals drives prediction of future events in auditory sequences.  ...  Human participants passively listened to sound sequences presented in synchrony or asynchrony to their heartbeat while concomitant electroencephalography was recorded.  ...  Acknowledgements We thank Rupert Ortner for helping programming the task and Serena Caverzasio and Marc Briquet for help with data acquisition.  ... 
doi:10.1038/s41598-017-13861-8 pmid:29093486 pmcid:PMC5665990 fatcat:gjnya5sqsje7xki4nmxqjried4

Proactive Fault Tolerance using Heartbeat Strategy for Fault Detection

2019 International Journal of Engineering and Advanced Technology  
In this paper, we propose to mark the nodes whose processes have failed to send the heartbeat message and prepare a count (confidence factor, α) for the same.  ...  of heartbeat message arrival) and later marked for failure recovery (if found faulty).  ...  Data centres with huge data storage support have been promoting technologies such as data deduplication, storage virtualization and storage convergence, which helps in both decreases in carbon footprint  ... 
doi:10.35940/ijeat.a2079.019119 fatcat:y7zc72wx2nfh5joat2xtuwawb4

Ensemble learning on heartbeat type classification

Xiao Dong Zeng, Sam Chao, Fai Wong
2011 Proceedings 2011 International Conference on System Science and Engineering  
In this paper, the use of SBCB algorithm to effectively deal with the classification of heartbeat on ECG signal is presented as a case study.  ...  Ensemble learning, known as multiple classifier system, combines the predictions from multiple base classifiers (or learners) altogether to conclude a final decision.  ...  In the stage of data preparation, as discussed in section 3, all the heartbeat types in MIT/BIH Arrhythmia database can be categorized into five main classes.  ... 
doi:10.1109/icsse.2011.5961921 fatcat:55fhdc7bgzbb7ernfqvsd3uw7i

Machine Learning Framwork for Performance Anomaly in OpenMP Multi-Threaded Systems [article]

Weidong Wang, Wangda Luo
2020 arXiv   pre-print
However, it is difficult to identify anomalies in the dynamic and noisy data collected by OpenMP multi-threaded monitoring infrastructures.  ...  Such performance anomaly can result in failure and inefficiencies, and are among the main challenges in system resiliency.  ...  -th heartbeat data in the target heartbeat sequence = 1 , 2 , · · · , .  ... 
arXiv:2011.02914v1 fatcat:aq6o2zycbza2hp3ektyc77qmmi
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