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Journal: Data in Brief
Article Title: A dataset of a stimulated biceps muscle of electromyogram signal by using rossler chaotic equation
doi: 10.1016/j.dib.2023.109438
Figure Lengend Snippet:
Article Snippet: How the data were acquired , For seating, a chair with a 90° backrest was utilized. The height of the chairs could be adjusted according to the individuals' height. SKINTACT brand surface-type electrodes were employed. The simulation exertion device used was the BNC-2090 model from National Instruments, and the EMG signal recording device was the
Techniques: Control
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Illustration of the research strategy. Blue flowchart: Division between data acquisition and data processing/analysis process; Grey flowchart: Data acquisition by the attached chest device (heart rate monitors - HRM) with analysis in the mobile phone application (APP); Yellow flowchart: Data acquisition by the coupled electrocardiogram (ECG) with analysis in the ECG software; Green flowchart: Data acquisition by coupled ECG and chest device with analysis with a validated common external/alternative software.
Article Snippet: The
Techniques: Software
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Characteristics of the healthy individuals (28 men and 28 women) evaluated for heart rate variability simultaneously using smartphone application and electrocardiogram.
Article Snippet: The
Techniques:
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Correlation between RR intervals obtained simultaneously during a 5-min period by electrocardiogram (ECG) and by mobile phone application (APP). The data are shown as averages of each interval [number of XY pairs=404]. Pearson's correlation was performed with 95% confidence interval (0.99 to 0.99).
Article Snippet: The
Techniques:
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Correlation between the frequency domain variables [low and high frequency (LF and HF)] separately calculated by each software [application (APP) and electrocardiogram (ECG)]. Data are reported as means of each registry [n=56]. Pearson's correlation was performed and the 95% confidence intervals were LF=(0.78 to 0.91) and HF=(0.76 to 0.91). nu: normalized units.
Article Snippet: The
Techniques: Software
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Bland-Altman agreement analysis between electrocardiogram (ECG), smartphone application (APP), and external software measurements of the frequency domain bands (low and high frequency - LF and HF). Solid lines indicate average differences and dotted lines refer to 95% limits of agreement (±1.96*SD). nu: normalized units.
Article Snippet: The
Techniques: Software
Journal: Brazilian Journal of Medical and Biological Research
Article Title: Different acquisition systems for heart rate variability analysis may lead to diverse outcomes
doi: 10.1590/1414-431X2021e11720
Figure Lengend Snippet: Comparison of the heart rate variability parameters obtained separately with a smartphone application (chest HRM) and electrocardiogram (ECG) and analyzed with a common or different analysis software.
Article Snippet: The
Techniques: Comparison, Software