On the computational complexity of the empirical mode decomposition algorithm

YH Wang, CH Yeh, HWV Young, K Hu, MT Lo - Physica A: Statistical …, 2014 - Elsevier
It has been claimed that the empirical mode decomposition (EMD) and its improved version
the ensemble EMD (EEMD) are computation intensive. In this study we will prove that the …

The Fourier decomposition method for nonlinear and non-stationary time series analysis

P Singh, SD Joshi, RK Patney… - Proceedings of the …, 2017 - royalsocietypublishing.org
for many decades, there has been a general perception in the literature that Fourier methods
are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we …

High-quality cardiopulmonary resuscitation

JP Nolan - Current opinion in critical care, 2014 - journals.lww.com
There is evidence for increasing survival rates following out-of-hospital cardiac arrest and
this is associated with increasing rates of bystander CPR. The quality of CPR provided by …

Arrhythmia evaluation in wearable ECG devices

M Sadrawi, CH Lin, YT Lin, Y Hsieh, CC Kuo, JC Chien… - Sensors, 2017 - mdpi.com
This study evaluates four databases from PhysioNet: The American Heart Association
database (AHADB), Creighton University Ventricular Tachyarrhythmia database (CUDB) …

Ventricular fibrillation waveform measures combined with prior shock outcome predict defibrillation success during cardiopulmonary resuscitation

J Coult, H Kwok, L Sherman, J Blackwood… - Journal of …, 2018 - Elsevier
Abstract Aim Amplitude Spectrum Area (AMSA) and Median Slope (MS) are ventricular
fibrillation (VF) waveform measures that predict defibrillation shock success …

Instantaneous respiratory estimation from thoracic impedance by empirical mode decomposition

FT Wang, HL Chan, CL Wang, HM Jian, SH Lin - Sensors, 2015 - mdpi.com
Impedance plethysmography provides a way to measure respiratory activity by sensing the
change of thoracic impedance caused by inspiration and expiration. This measurement …

Combining amplitude spectrum area with previous shock information using neural networks improves prediction performance of defibrillation outcome for subsequent …

M He, Y Lu, L Zhang, H Zhang, Y Gong, Y Li - PloS one, 2016 - journals.plos.org
Objective Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful
tool to optimize defibrillation. However, whether combining VF features with additional …

Short ECG segments predict defibrillation outcome using quantitative waveform measures

J Coult, L Sherman, H Kwok, J Blackwood… - Resuscitation, 2016 - Elsevier
Aim Quantitative waveform measures of the ventricular fibrillation (VF) electrocardiogram
(ECG) predict defibrillation outcome. Calculation requires an ECG epoch without chest …

Quantifying spasticity with limited swinging cycles using pendulum test based on phase amplitude coupling

CH Yeh, HWV Young, CY Wang… - … on Neural Systems …, 2016 - ieeexplore.ieee.org
Parameters derived from the goniometer measures in the Pendulum test are insufficient in
describing the function of abnormal muscle activity in the spasticity. To explore a quantitative …

[HTML][HTML] Estimating the amplitude spectrum area of ventricular fibrillation during cardiopulmonary resuscitation using only ECG waveform

F Zuo, Y Ding, C Dai, L Wei, Y Gong… - Annals of …, 2021 - ncbi.nlm.nih.gov
Background Amplitude spectrum area (AMSA) calculated from ventricular fibrillation (VF)
can be used to monitor the effectiveness of chest compression (CC) and optimize the timing …