scholarly journals Characterizing artifacts in RR stress test time series

2016 ◽  
Author(s):  
Fabian Astudillo-Salinas ◽  
Kenneth Palacio-Baus ◽  
Lizandro Solano-Quinde ◽  
Ruben Medina ◽  
Sara Wong
Keyword(s):  
Time Series ◽  
Stress Test ◽  
Test Time

scholarly journals Cardiac Rehabilitation and Physical Performance in Patients after Myocardial Infarction: Preliminary Research

2021 ◽  
Vol 10 (11) ◽  
pp. 2253
Author(s):  
Agnieszka Grochulska ◽  
Sebastian Glowinski ◽  
Aleksandra Bryndal
Keyword(s):  
Myocardial Infarction ◽  
Cardiac Rehabilitation ◽  
Physical Performance ◽  
Stress Test ◽  
Maximal Oxygen Consumption ◽  
Exercise Stress Test ◽  
Health Condition ◽  
Exercise Stress ◽  
Test Time ◽  
Before And After

(1) Background: Cardiovascular diseases, in particular, myocardial infarction (MI), are the main threats to human health in modern times. Cardiac rehabilitation (CR), and especially increased physical activity, significantly prevent the consequences of MI. The aim of this study was to assess physical performance in patients after MI before and after CR. (2) Methods: 126 patients after MI were examined. They were admitted to the cardiac rehabilitation ward twice: in the 3rd month after MI, and then in the 6th month after the last rehabilitation session. CR lasted 20 treatment days (4 weeks with 5 treatment days and 2 days’ break). The exercise stress test on the treadmill and a 6-minute walk test (6MWT) were used to assess physical performance. Patients were assigned to an appropriate rehabilitation model due to their health condition. (3) Results: In the studied group, the exercise stress test time and the metabolic equivalent of task (MET), the maximal oxygen consumption (VO2max), and 6MWT score increased significantly (p = 0.0001) at two time-points of observation. (4) Conclusion: CR significantly improves physical performance in patients after MI.

scholarly journals STUDI KOMPARATIF SENAM KAKI DAN SENAM KEBUGARAN DIABETES TERHADAP KADAR GLUKOSA DARAH SEWAKTU LANSIA DI SLEMAN YOGYAKARTA

1970 ◽  
Vol 5 (1) ◽  
Author(s):  
Nimsi Melati ◽  
Charolina Merlida Indriastuti
Keyword(s):  
Diabetes Mellitus ◽  
Time Series ◽  
Repeated Measures ◽  
Test Time ◽  
Purposive Sampling ◽  
Post Test ◽  
Quasi Experimental

Latar Belakang: Tantangan kesehatan utama saat ini adalah penyakit tidak menular, seperti diabetes mellitus (DM). Tahun 2014 jumlah penderita DM di dunia sebanyak 194 juta jiwa. Penderita yang tidak mampu mengontrol penyakit DM dapat menimbulkan berbagai komplikasi. Pengelolaan dan pencegahan komplikasi DM memerlukan 4 pilar, salah satunya adalah olahraga seperti senam. Tujuan:Untuk mengetahui perbedaan senam kaki dan senam kebugaran diabetes terhadap kadar glukosa darah sewaktu lansia di Sleman Yogyakarta 2017. Metode Penelitian: Penelitian ini menggunakan desain quasi experimental two group pre-post test time series. Teknik sampling menggunakan purposive sampling sebanyak 34 responden, 17 responden senam kaki dan 17 responden senam kebugaran diabetes. Analisisdata menggunakan uji General Linier Model Repeated Measures (GLM-RM). Hasil: Hasil uji GLM-RM kelompok senam kaki p= 0,008 (p

Can Pre-Treatment with β-Agonists Reduce Stress Test Time and the Use of Atropine in Dobutamine Stress Testing?

Cardiology ◽  
2001 ◽  
Vol 95 (3) ◽  
pp. 156-160
Author(s):  
Milind Y. Desai ◽  
Erasmo De la Peña-Almaguer ◽  
Finn Mannting
Keyword(s):  
Stress Testing ◽  
Stress Test ◽  
Dobutamine Stress ◽  
Test Time ◽  
Dobutamine Stress Testing ◽  
Pre Treatment

Increasing the sensitivity of real-time method for diagnostic of autogenerators phase synchronization based on their non-stationary time series

2021 ◽  
Vol 29 (6) ◽  
pp. 892-904
Author(s):  
Aleksandr Kurbako ◽  
◽  
Danil Kulminskiy ◽  
Ekaterina Borovkova ◽  
Anton Kiselev ◽  
...  
Keyword(s):  
Experimental Data ◽  
Time Series ◽  
Computational Complexity ◽  
Real Time ◽  
Phase Synchronization ◽  
Statistical Properties ◽  
Stationary Time Series ◽  
Test Time ◽  
Stationary Time ◽  
Proposed Modification

Purpose of this work is to of the research – Increasing the sensitivity of a method for diagnosing phase synchronization of autogenerators based on their non-stationary time series in real time, and also a comparison of the statistical properties of the proposed modification of the method with the well-known method for diagnostics of loop synchronization, which has proven itself in the analysis of experimental data. Methods.The paper compares the probabilities of the appearance of an error of the second kind of the developed modified method for diagnostics of phase synchronization with the probabilities of occurrence of an error of the second kind of the known method at equal values of sensitivity. When comparing the methods, generated test time realizations with a priori known boundaries of the phase synchronization sections are used, which repeat the statistical properties of the experimental data. It also compares the computational complexity of the two methods. Results. A modification of the method for diagnosing phase synchronization of autonomic regulation circuits in real time is proposed. It is shown that the proposed modification provides similar values of sensitivity and probability of appearance of errors of the second kind as the previously proposed approach. The developed method has less computational complexity than the previously proposed method. The values of free parameters corresponding to different values of sensitivity and probability of appearance of errors of the second kind are obtained. Conclusion. The area of application of the developed method with modification is formulated. The low computational complexity of the proposed method, as well as the possibility of switching devices to integer computations in calculations, makes it possible to use it for wearable registrations performing calculations in real time, based on small-sized low-power processors that do not support floating-point arithmetic operations.

Continental scale SBAS-DInSAR processing for the generation of Sentinel-1 deformation time series within a cloud computing environment: achieved results and lessons learned

2020 ◽  
Author(s):  
Riccardo Lanari ◽  
Manuela Bonano ◽  
Sabatino Buonanno ◽  
Francesco Casu ◽  
Claudio De Luca ◽  
...  
Keyword(s):  
Time Series ◽  
Cloud Computing ◽  
Surface Deformation ◽  
Stress Test ◽  
Sar Interferometry ◽  
Continental Scale ◽  
Spatial Coverage ◽  
Small Baseline Subset ◽  
Sar Data ◽  
Small Baseline

<p>The Sentinel-1 constellation of the Copernicus Program already represents a big revolution within the Earth Observation (EO) scenario. This result is mainly due to the capability of this constellation to acquire huge volumes of SAR data all over the globe, with a wide spatial coverage, a short revisit time (12 or 6 days in the case of one or two operating satellites, respectively), and a free and open access data policy. In particular, the availability of such a large amount of SAR data acquired through the TOPS mode, characterized by a short “orbital tube” (with a 200m nominal diameter) and a specific design for ensuring differential SAR interferometry (DInSAR) applications, has opened the possibility to investigate Earth surface deformation phenomena at unprecedented spatial scale and with a high temporal rate.</p><p> </p><p>Among several advanced DInSAR algorithms, a widely used approach is the Small BAseline Subset (SBAS) technique, which has already proven its effectiveness to investigate surface displacements with centimeter- to millimeter-level accuracy in different scenarios. Moreover, a parallel algorithmic solution for the SBAS approach, referred to as Parallel Small BAseline Subset (P-SBAS), has been recently developed. This approach permits to generate, in an automatic and unsupervised way, advanced DInSAR products by taking full benefit from parallel computing architectures, such as cluster, grid and, above all, cloud computing infrastructures.</p><p> </p><p>In this work we present the results of a DInSAR experiment, based on the P-SBAS approach, carried out at the European scale. In particular, we exploited the entire available Sentinel-1 dataset collected through the TOPS acquisition mode between March 2015 and September 2018 from descending orbits over large part of Europe. Moreover, the overall analysis wasbcarried out by using the Copernicus Data and Information Access Services (DIAS) and, in particular, those provided by the ONDA DIAS platform, which was selected through a public tender. This activity, carried out as stress test of the EPOSAR service included in the Satellite Data Thematic Core Service of the EPOS infrastructure, permitted to investigate the DIAS capacity to operationally serve systematic and automatic DInSAR processing services, such as the one based on the P-SBAS approach.</p><p> </p><p>Our experiment was successfully completed, allowing the retrieval of the deformation time-series of the overall investigated area with the final products having the main characteristics summarized in the following:</p><p> </p><ul><li>Exploited Sentinel-1 data: ~72.000</li> <li>Covered Area: ~4.500.000 km<sup>2</sup></li> <li>Coherent (multilook) SAR pixels: ~120.000.000</li> <li>Final products pixel dimension: ~80 m</li> <li>Time elapsed: ~6 months</li> </ul><p> </p><p>The presented discussion will highlight the main pros and cons of the exploited solution for such wide area DInSAR experiment. Moreover, the analysis of the achieved results will also show the high quality of the retrieved DInSAR results, that can be of interest for the Solid Earth scientific community, and the potentially positive impact of the presented solution for what concerns the future development of the European Ground Motion Service.</p><p>This work is supported by: the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement; the H2020 EPOS-SP project (GA 871121); the I-AMICA (PONa3_00363) project; and the IREA-CNR/DGSUNMIG agreement.</p>

scholarly journals Semiautomatic validation of RR time series in an ECG stress test database

2015 ◽  
Author(s):  
Jairo Armijos ◽  
David García ◽  
Darwin Astudillo ◽  
Kenneth Palacio-Baus ◽  
Rubén Medina ◽  
...  
Keyword(s):  
Time Series ◽  
Stress Test ◽  
Test Database
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