HEART RHYTHM ANALYSIS USING A NONLINEAR DYNAMICS PERSPECTIVE

Author(s):  
Augusto Cheffer ◽  
Marcelo A. Savi ◽  
Tiago Leite Pereira ◽  
Aline Souza de Paula
JAMA ◽  
1973 ◽  
Vol 226 (11) ◽  
pp. 1362
Author(s):  
Massimo Calabresi
Keyword(s):  

2021 ◽  
Vol 62 (08) ◽  
pp. 415-423 ◽  
Author(s):  
SH Lim ◽  
TS Chee ◽  
FC Wee ◽  
SH Tan ◽  
JH Loke ◽  
...  

Basic Cardiac Life Support and Automated External Defibrillation (BCLS+AED) refers to the skills required in resuscitating cardiac arrest casualties. On recognising cardiac arrest, the rescuer should call for ‘995’ for Emergency Ambulance and immediately initiate chest compressions. Good-quality chest compressions are performed with arms extended, elbows locked, shoulders directly perpendicular over the casualty’s chest, and the heel of the palm placed on the lower half of the sternum. The rescuer compresses hard and fast at 4–6 cm depth for adults at a compression rate of 100–120 per minute, with complete chest recoil after each compression. Two quick ventilations of 400–600 mL each can be delivered via a bag-valve-mask after every 30 chest compressions. Alternatively, a trained, able and willing rescuer can provide mouth-to-mouth ventilation. Cardiopulmonary resuscitation should be stopped only when the casualty wakes up, the emergency team takes over care, or when an automated external defibrillator prompts for heart rhythm analysis or delivery of a shock.


2021 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
Alfonso Maria Ponsiglione ◽  
Francesco Amato ◽  
Maria Romano

In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers.


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