Evidence map›Paper›PMID 36826631›Full record

ArticleMedical & biological engineering & computing2023

A fast sample entropy for pulse rate variability analysis.

Lijuan Chou, Shengrong Gong, Haiping Yang, Jicheng Liu, Yongxin Chou

Abstract read
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In one paragraph

Article in Medical & biological engineering & computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lijuan ChouSchool of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, 215500, Jiangsu, China.
Shengrong GongSchool of Computer and Information Technology, Northeast Petroleum University, Daqing, 163318, Heilongjiang, China.
Haiping YangSchool of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, 215500, Jiangsu, China.
Jicheng LiuSchool of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, 215500, Jiangsu, China.
Yongxin ChouSchool of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, 215500, Jiangsu, China. cslgchouyx@cslg.edu.cn.

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 61901062
6 · The paper itself

Abstract

Sample entropy is an effective nonlinear index for analyzing pulse rate variability (PRV) signal, but it has problems with a large amount of calculation and time consumption. Therefore, this study proposes a fast sample entropy calculation method to analyze the PRV signal according to the microprocessor process of data updating and the principle of sample entropy. The simulated data and PRV signal are employed as experimental data to verify the accuracy and time consumption of the proposed method. The experimental results on simulated data display that the proposed improved sample entropy can improve the operation rate of the entropy value by a maximum of 47.6 times and an average of 28.6 times and keep the entropy value unchanged. Experimental results on PRV signal display that the proposed improved sample entropy has great potential in the real-time processing of physiological signals, which can increase approximately 35 times.

Indexed as

PulseSignal Processing, Computer-AssistedEntropyHeart RateLow time-consumptionPulse rate variabilityPulse signalSample entropySignal processing in real time

Identifiers

PMID36826631

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.