AIMC Topic: Electrocardiography

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Patient-Specific Classification of ICU Sedation Levels From Heart Rate Variability.

Critical care medicine
OBJECTIVE: To develop a personalizable algorithm to discriminate between sedation levels in ICU patients based on heart rate variability.

[Research on Clinical Electrocardiogram Classification Algorithm Based on Ensemble Learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
With the increasing number of electrocardiogram(ECG)data,extensive application requirements of computer-aided ECG analysis have occurred.In the paper,we propose a variety of strategies to improve the performance of clinical ECG classification algorit...

An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

Bio-medical materials and engineering
In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid t...

Efficient compressive sensing of ECG segments based on machine learning for QRS-based arrhythmia detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A novel method for efficient telemonitoring of arrhythmia based on using QRS complexes is proposed. Two features, namely, sum of absolute differences (SAD) and maximum of absolute differences (MAD) are efficiently computed for each ECG segment in the...

Evaluation of periodic breathing in respiratory flow signal of elderly patients using SVM and linear discriminant analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aging population is a major concern that is reflected in the increase of chronic diseases. Heart Failure (HF) is one of the most common chronic diseases of elderly people that is punctuated with acute episodes, which result in hospitalization. The pe...

Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minu...

Monitoring and detecting atrial fibrillation using wearable technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial fibrillation (AFib) is diagnosed by analysis of the morphological and rhythmic properties of the electrocardiogram. It was recently shown that accurate detection of AFib is possible using beat-to-beat interval variations. This raises the quest...

Risk prediction for cardiovascular disease using ECG data in the China kadoorie biobank.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We set out to use machine learning techniques to analyse ECG data to improve risk evaluation of cardiovascular disease in a very large cohort study of the Chinese population. We performed this investigation by (i) detecting "abnormality" using 3 one-...

Electrocardiogram signal denoising based on a new improved wavelet thresholding.

The Review of scientific instruments
Good quality electrocardiogram (ECG) is utilized by physicians for the interpretation and identification of physiological and pathological phenomena. In general, ECG signals may mix various noises such as baseline wander, power line interference, and...

Using ordinal partition transition networks to analyze ECG data.

Chaos (Woodbury, N.Y.)
Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patter...