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Morphological Arrhythmia Automated Diagnosis Method Using Gray-Level Co-occurrence Matrix Enhanced Convolutional Neural Network

Weifang Sun, Nianyin Zeng, Yuchao He
2019 IEEE Access  
In this method, the gray-level co-occurrence matrix (GLCM) is employed for features vector description because of its extraordinary statistical feature extraction ability.  ...  The experimental results of the recognition for morphological arrhythmias show the feasibility and effectiveness of the proposed method and could be used to reduce the rate of the misdiagnosed computerized  ...  THE PROPOSED MORPHOLOGICAL ARRHYTHMIA AUTOMATED DIAGNOSIS METHOD As mentioned before, GLCM possesses a powerful ability for complex features extraction.  ... 
doi:10.1109/access.2019.2918361 fatcat:rsxf7yqgabflbkuuytwwnipxoq

Intelligent Exercise Guidance System Based on Smart Clothing

Chung-Chih Lin, Yi-Shin Liou, Zhuhuang Zhou, Shuicai Wu
2018 Journal of Medical and Biological Engineering  
beats) were proposed for the system.  ...  The MAPEs of the preset and trained QPRMs were respectively 6.37% and 3.84% for increasing HR and 5.25% and 3.57% for decreasing HR.  ...  This work was supported by the Ministry of Science and Technology (National Science Council) of Taiwan  ... 
doi:10.1007/s40846-018-0450-6 fatcat:hysksuexbrfp3bptwlqptlmb5e

Identification of ECG Arrhythmias Using Phase Space Reconstruction [chapter]

Felice M. Roberts, Richard J. Povinelli, Kristina M. Ropella
2001 Lecture Notes in Computer Science  
The ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment, as well as, for understanding the electrophysiological mechanisms of the arrhythmias  ...  This paper proposes a novel approach to efficiently and accurately identify normal sinus rhythm and various ventricular arrhythmias through a combination of phase space reconstruction and machine learning  ...  We hypothesize that the patterns of the quasi-periodic [24] attractors of heart rhythms change immediately prior to (within a 10-minute time period) the onset of a serious ventricular arrhythmia.  ... 
doi:10.1007/3-540-44794-6_34 fatcat:i4gktd4i7naptjo75paipivcjm

Development of Listenership for Indian Hindustani Music By Using Mimetic Comprehension

Rachit Gupta, Angel Blanco
2019 Zenodo  
How can we train adults in listenership for Indian Hindustani music belonging to a different culture?  ...  We developed a rhythm training setup to perform a music cognitive study and investigate the effects of visual feedback enforced mimetic comprehension of Hindustani Rhythmic Beat Patterns (also called Talas  ...  It has sixteen (16) beats in four equal divisions (4+4+4+4). Every "Tal" has its own method of counting by using hand gestures.  ... 
doi:10.5281/zenodo.3408151 fatcat:7ilh4z246rfgfecoynhyoieewu

A commentary on Micah Bregman et al.: A method for testing synchronization to a musical beat in domestic horses (Equus ferus caballus)

Sandy Venneman
2013 Empirical Musicology Review  
This commentary provides additional information related to equines and suggestions for strengthening the proposed protocol for testing synchronization to a musical beat in this species.  ...  For this reason it might be beneficial to look at the beat on the dominant forelimb in addition to the current protocol of counting the footfalls of both forelimbs.  ...  However, a strength of the proposed musical protocol is insuring that the test music chosen has a strong beat and that each horse has the physical ability to trot to the tempo chosen.  ... 
doi:10.18061/emr.v7i3-4.3749 fatcat:ca4la4kprzh7hkfpobm7mhursy

Hybrid Features and Classifier for Classification of ECG Signal

K. Muthuvel, L. Padma Suresh
2015 Research Journal of Applied Sciences Engineering and Technology  
In this research, we have proposed an efficient technique to classify beat from ECG database.  ...  The beat signals are initially taken from the physiobank ATM and in the pre-processing stage the beat signals are made suitable for feature extraction.  ...  In our proposed method we use a hybrid technique for both feature extraction and classification.  ... 
doi:10.19026/rjaset.9.2597 fatcat:zq4n7ccuwjepzaab3yq673d644

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  
The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats.  ...  It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in clinical practice.  ...  Although the proposed method was used for the detection of VEB and SVEB, class F beat and a few heartbeat types in a class could be detected in terms of the core idea of the method.  ... 
doi:10.1186/1475-925x-13-90 pmid:24981916 pmcid:PMC4085082 fatcat:z6a3gtsnorel5i2c2mk2lk3dpq

Short term prediction of Atrial Fibrillation from ambulatory monitoring ECG using a deep neural network

Jagmeet P. Singh, Julien Fontanarava, Grégoire de Massé, Tanner Carbonati, Jia Li, Christine Henry, Laurent Fiorina
2022 European Heart Journal - Digital Health  
Methods We identified a training set of Holter recordings of 7 to 15 days duration, in which no AF could be found in the first 24 h.  ...  We trained a neural network to predict the presence or absence of AF in the 15 following days, using only the first 24 h of the recording.  ...  Acknowledgments Christophe Gardella provided advice for the study design.  ... 
doi:10.1093/ehjdh/ztac014 fatcat:6jhljrynyzef3ck5lrwdo3nf2m

Quality Assessment of 12 Lead ECG Signals based on Beat Detection Pattern

Muhammad Yazid
2017 JAREE (Journal on Advanced Research in Electrical Engineering)  
Abstract—This paper proposed a new method for assessing signal quality from 12 lead ECG signal.  ...  The proposed method is verified on PhysioNet/Computing in Cardiology Chal- lenge 2011 12 lead ECG signals database, achieving a result of 89.98 percent accuracy when tested against the training dataset  ...  PROPOSED ECG SIGNAL QUALITY ASSESSMENT METHOD This paper propose a method of assessing quality of ECG signal based on anomaly in beat detection results.  ... 
doi:10.12962/j25796216.v1.i2.17 fatcat:vaduq3fjwzejnoarhj2wawwwbu

Deconstruct, analyse, reconstruct: How to improve tempo, beat, and downbeat estimation

Sebastian Böck, Matthew Davies
2020 Zenodo  
To this end, we devise a novel multi-task approach for the simultaneous estimation of tempo, beat, and downbeat.  ...  We additionally reflect this outlook when training the network, and include a simple data augmentation strategy to increase the network's exposure to a wider range of tempi, and hence beat and downbeat  ...  For two-level counting, we can mark the three beats of the bar of a waltz as follows: 1 2 3 1 2 3 1. . . , where the 1 indicates the first beat of each bar, the downbeat.  ... 
doi:10.5281/zenodo.4245497 fatcat:562a4tnkmzgdvfsplrqngasvv4

GA-NN approach for ECG feature selection in rule based arrhythmia classification

G. Aslantas, F. Gürgen, A. A. Salah
2014 Neural Network World  
In this study, a novel genetic algorithm-neural network (GA-NN) approach is proposed as a classifier, and compared with other classification methods.  ...  Computer-aided ECG analysis is very important for early diagnosis of heart diseases.  ...  As an example of this, Hu et al. used MLPs in a cascade for beat classification of one normal and 12 abnormal classes [15] .  ... 
doi:10.14311/nnw.2014.24.016 fatcat:sb7t6edp5vdh7njdz4lnlst5cy

Automated Heartbeat Classification Exploiting Convolutional Neural Network with Channel-wise Attention

Feiteng Li, Jiaquan Wu, Menghan Jia, Zhijian Chen, Yu Pu.
2019 IEEE Access  
In addition to an average accuracy and specificity of over 99%, this method achieves a sensitivity of 95.4% and a positive predictivity of 97.1% for VEB class, and a sensitivity of 81.1% and a positive  ...  The proposed method classifies heartbeats into five classes (normal beat (N), supraventricular ectopic beat (SVEB), ventricular ectopic beat (VEB), fusion beat (F), and unclassifiable beat (Q)).  ...  To avoid this disadvantage of random selection of training samples, a method of intrarecord sample clustering is proposed to ensure that the representative beats of each class (N beats, SVEBs, and VEBs  ... 
doi:10.1109/access.2019.2938617 fatcat:ghvkwgbymbcuhk3jdbzaxv44bq

Multi-Task Learning of Tempo and Beat: Learning One to Improve the Other

Sebastian Böck, Matthew Davies, Peter Knees
2019 Zenodo  
In this paper, we propose a multi-task learning approach for simultaneous tempo estimation and beat tracking of musical audio.  ...  The benefit of this approach is investigated by the inclusion of training data for which tempo-only annotations are available, and which is shown to provide improvements in beat tracking accuracy.  ...  In light of the challenges of obtaining highquality annotated data for training beat tracking systems, the ability to profit from alternative training data which is both far more prevalent and easier to  ... 
doi:10.5281/zenodo.3527849 fatcat:w7a3sjlvord3zacq2w3qbqumrq

Audio Tag Annotation and Retrieval Using Tag Count Information [chapter]

Hung-Yi Lo, Shou-De Lin, Hsin-Min Wang
2011 Lecture Notes in Computer Science  
To address the noisy label problem, we propose a novel method that exploits the tag count information.  ...  This can be achieved by training a binary classifier for each tag based on the labeled music data.  ...  Conclusion We have proposed a novel method for exploiting tag count information in audio tagging tasks, and discussed several factors that affect the counts of tags assigned to an audio clip.  ... 
doi:10.1007/978-3-642-17832-0_32 fatcat:dt3nhih6qfh4bawqcyvo32qtaq

Compositional Generalization for Primitive Substitutions

Yuanpeng Li, Liang Zhao, Jianyu Wang, Joel Hestness
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
Conventional methods use a single representation for the input sentence, making it hard to apply prior knowledge of compositionality.  ...  It also beats human performance on a few-shot learning task. We hope the proposed approach can help ease future research towards human-level compositional language learning.  ...  Acknowledgments We thank Kenneth Church, Mohamed Elhoseiny, Ka Yee Lun and others for helpful suggestions.  ... 
doi:10.18653/v1/d19-1438 dblp:conf/emnlp/LiZWH19 fatcat:nx7jm6it65gbdavc56o6gt3edm
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