Biomedical Science and Engineering

ISSN (Print): 2373-1257

ISSN (Online): 2373-1265


Current Issue» Volume 2, Number 3 (2014)


Sample Entropy based HRV: Effect of ECG Sampling Frequency

1Department of Electronics and Communication Engineering, Guru Nanak Dev University, Regional Campus, Jalandhar, India

2Research Scholar Punjab Technical University Jalandhar and Department of Electronics and Communication Engineering, Guru Nanak Dev University Regional Campus, Jalandhar, India

3Amrirtsar College of Engineering and Technology, Amritsar, India

Biomedical Science and Engineering. 2014, 2(3), 68-72
DOI: 10.12691/bse-2-3-3
Copyright © 2014 Science and Education Publishing

Cite this paper:
Butta Singh, Manjit Singh, Vijay Kumar Banga. Sample Entropy based HRV: Effect of ECG Sampling Frequency. Biomedical Science and Engineering. 2014; 2(3):68-72. doi: 10.12691/bse-2-3-3.

Correspondence to: Butta  Singh, Department of Electronics and Communication Engineering, Guru Nanak Dev University, Regional Campus, Jalandhar, India. Email:


Biomedical signals carry important information about the behaviour of the living systems under study. A proper processing of these signals in principle enhances their physiological and clinical information. Analysis of variations in the instantaneous heart rate time series using the beat to-beat RR intervals (the RR tachogram) is known as heart rate variability (HRV) analysis. Sample entropy (SampEn), refined version of approximate entropy (ApEn), is a nonlinear complexity measure used to quantify the irregularity of a RR interval time series without biasing. An increase in SampEn is an indicator of increases in complexity. Linear HRV parameters are very sensitive to ECG sampling frequency and low sampling frequency may result in clinically misinterpretation of HRV. In this study consequences of errors in SampEn based HRV induced by ECG sampling frequency have been investigated. The error induced in SampEn based HRV was found to be a function of ECG sampling frequency and RR interval data length. The relative error in SampEn was approximately 3.5%.for medium and long term data (N=500, 1000 respectively) and less than 2% for short term data (N=200) at low ECG sampling frequency of 125 Hz with respect to reference values at 2000 Hz. Therefore the SampEn based HRV indices computed from RR interval time series with low ECG sampling should be regarded with caution. The finding of this study can be partly used as a reference for the optimal ECG sampling frequency for the SampEn-based HRV assessment.



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Review Article: Non-Invasive Fetal Heart Rate Monitoring Techniques

1Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, Irbid, Jordan

Biomedical Science and Engineering. 2014, 2(3), 53-67
DOI: 10.12691/bse-2-3-2
Copyright © 2014 Science and Education Publishing

Cite this paper:
Enas W. Abdulhay, Rami J. Oweis, Asal M. Alhaddad, Fadi N. Sublaban, Mahmoud A. Radwan, Hiyam M. Almasaeed. Review Article: Non-Invasive Fetal Heart Rate Monitoring Techniques. Biomedical Science and Engineering. 2014; 2(3):53-67. doi: 10.12691/bse-2-3-2.

Correspondence to: Rami  J. Oweis, Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, Irbid, Jordan. Email:


Fetal heart rate monitoring is a process carried out during pregnancy and/or labor to keep track of the fetal heart rate and in some devices the uterine contractions. A variety of techniques has been studied and is used on a daily basis in many hospitals. This review discusses and compares the operating principle, the key signal processing techniques, advantages and drawbacks of five of those techniques: fetal electrocardiography (FECG) using abdominal surface electrodes, photoplethysmography (PPG) using near infrared (NIR) light, Doppler ultrasound, ultrasound based cardiotocography (CTG) known as electronic fetal monitoring and fetal magnetocardiography (FMCG). The review leads to the conclusion that the PPG overcomes almost all of the drawbacks of the other methods and thus deserves the most attention in future biomedical research.



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Relation between Planck Length and Origin of Consciousness in Life Sciences-A Mathematical Proof

1Independent Researcher, Bheemunipatnam, India

Biomedical Science and Engineering. 2014, 2(3), 48-52
DOI: 10.12691/bse-2-3-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Siva Prasad Kodukula. Relation between Planck Length and Origin of Consciousness in Life Sciences-A Mathematical Proof. Biomedical Science and Engineering. 2014; 2(3):48-52. doi: 10.12691/bse-2-3-1.

Correspondence to: Siva  Prasad Kodukula, Independent Researcher, Bheemunipatnam, India. Email:


A novel attempt has been made to define the difference between living and non living things in terms of physics. This is the relation between the bio energy in the form of consciousness associated to any living thing and Planck length of quantum physics. Consciousness, a parameter which differentiates living and non living thing has been explained by physics with the use of ‘Siva’s equation of consciousnes’. ‘Planck length’ of Quantum physics has been derived by substituting the value of ‘d’ mass of ‘K-Suryon’ in ‘Siva’s equation of consciousness’. The final result is a substantial mathematical proof says that the consciousness wave originates from a point in our four dimensional space time continuum whose diameter is 1.6 times higher than ‘Planck length’ of physics. This consciousness wave obeys all the definitions of electromagnetic wave without collapsing in to Planck hole. This will be useful in making substantial theories of consciousness and ‘Neuro Quantology’.



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