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Shi X, Niida N, Yamamoto K, Ohtsuki T, Matsui Y, Owada K. A Robust Approach Assisted by Signal Quality Assessment for Fetal Heart Rate Estimation from Doppler Ultrasound Signal. SENSORS (BASEL, SWITZERLAND) 2023; 23:9698. [PMID: 38139544 PMCID: PMC10747258 DOI: 10.3390/s23249698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 12/02/2023] [Accepted: 12/06/2023] [Indexed: 12/24/2023]
Abstract
Fetal heart rate (FHR) monitoring, typically using Doppler ultrasound (DUS) signals, is an important technique for assessing fetal health. In this work, we develop a robust DUS-based FHR estimation approach complemented by DUS signal quality assessment (SQA) based on unsupervised representation learning in response to the drawbacks of previous DUS-based FHR estimation and DUS SQA methods. We improve the existing FHR estimation algorithm based on the autocorrelation function (ACF), which is the most widely used method for estimating FHR from DUS signals. Short-time Fourier transform (STFT) serves as a signal pre-processing technique that allows the extraction of both temporal and spectral information. In addition, we utilize double ACF calculations, employing the first one to determine an appropriate window size and the second one to estimate the FHR within changing windows. This approach enhances the robustness and adaptability of the algorithm. Furthermore, we tackle the challenge of low-quality signals impacting FHR estimation by introducing a DUS SQA method based on unsupervised representation learning. We employ a variational autoencoder (VAE) to train representations of pre-processed fetal DUS data and aggregate them into a signal quality index (SQI) using a self-organizing map (SOM). By incorporating the SQI and Kalman filter (KF), we refine the estimated FHRs, minimizing errors in the estimation process. Experimental results demonstrate that our proposed approach outperforms conventional methods in terms of accuracy and robustness.
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Affiliation(s)
- Xintong Shi
- Graduate School of Science and Technology, Keio University, Yokohama 223-8522, Japan; (X.S.); (N.N.)
| | - Natsuho Niida
- Graduate School of Science and Technology, Keio University, Yokohama 223-8522, Japan; (X.S.); (N.N.)
| | - Kohei Yamamoto
- Department of Information and Computer Science, Keio University, Yokohama 223-8522, Japan;
| | - Tomoaki Ohtsuki
- Department of Information and Computer Science, Keio University, Yokohama 223-8522, Japan;
| | - Yutaka Matsui
- Atom Medical Co., Tokyo 113-0021, Japan; (Y.M.); (K.O.)
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Wang Y, Zheng C, Zhou Y, Li L, Peng H, Zhang C. Novel Method for Fetal and Maternal Heart Rate Measurements Using 2-D Ultrasound Color Doppler Flow Images. ULTRASOUND IN MEDICINE & BIOLOGY 2022; 48:2029-2039. [PMID: 35879181 DOI: 10.1016/j.ultrasmedbio.2022.05.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 05/15/2022] [Accepted: 05/19/2022] [Indexed: 06/15/2023]
Abstract
Fetal heart rate (FHR) and maternal heart rate (MHR) are important indicators of fetal well-being during pregnancy. A common method in clinical examination is to estimate the FHR using the Doppler shift of echoes from umbilical artery blood flow based on an ultrasound pulsed-wave (PW) Doppler technique. Similarly, a sampling gate can be located at the maternal blood flow to measure MHR using PW Doppler. Ultrasound color Doppler flow imaging (CDFI) is one of the most commonly used imaging modes for clinical fetal examinations. Color coding is employed to display the blood flow velocity and direction in color grades according to the Doppler shift. Continuous CDF images contain dynamic changes characteristics of the blood flow. The periodic characteristics can be used to obtain heart rate information. Therefore, here we propose a novel method to measure FHR and MHR simultaneously using CDF images. The proposed method calculates the histogram of color similarity of CDF images to initially extract the periodic characteristics of the CDF image sequence. The histogram of color similarity function is then processed by a bandpass filter and autocorrelation operation to reduce noise and enhance periodicity. Finally, peak detection is performed on the processed signal to obtain the period and estimate the heart rate. The proposed method can measure the FHR and MHR in parallel after selecting two regions containing the umbilical artery and maternal blood flow, respectively. Thus, the method has high computational efficiency. The proposed method was evaluated on a Doppler flow phantom and clinical CDF images and then compared with the PW Doppler method. The correlation analysis and Bland-Altman plots reveal that the proposed method agrees well with the PW Doppler. It is a sanity check method for real-time clinical FHR and MHR measurements.
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Affiliation(s)
- Yadan Wang
- School of Mechanical Engineering, Hefei University of Technology, Hefei, China
| | - Chichao Zheng
- Department of Biomedical Engineering, Hefei University of Technology, Hefei, China
| | - Yi Zhou
- Department of Ultrasound, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Liang Li
- Department of Ultrasound, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Hu Peng
- Department of Biomedical Engineering, Hefei University of Technology, Hefei, China
| | - Chaoxue Zhang
- Department of Ultrasound, First Affiliated Hospital of Anhui Medical University, Hefei, China.
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The role of ultrasound and MRI in diagnosing of obstetrics cardiac disorders: A systematic review. JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2022. [DOI: 10.1016/j.jrras.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Ogenyi P, Chiegwu HU, England A, Akanegbu UE, Ogbonna OS, Abubakar A, Luntsi G, Zira DJ, Dauda M. Appraisal of trimester-specific fetal heart rate and its role in gestational age prediction. Radiography (Lond) 2022; 28:926-932. [PMID: 35820355 DOI: 10.1016/j.radi.2022.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 06/21/2022] [Accepted: 06/23/2022] [Indexed: 10/31/2022]
Abstract
INTRODUCTION The aim of this study was to evaluate and report normal sonographic FHR values among low-risk singleton women across the three trimesters of pregnancy and determine FHR role in gestational age prediction. METHOD A prospective cross-sectional study of 2727 low-risk singleton pregnant women was undertaken. FHR measurements were obtained by a consultant radiologist and three experienced sonographers using transabdominal approach from January 2019 to December 2020. Two FHR measurements were taken for each participant. The fetal lie and presentation were also documented in the first trimester. Data were analysed using SPSS version 24 (IBM, Armonk, NY, USA). RESULT The maternal mean ± SD age was 25.8 ± 6.5 years and mean FHR for first, second and third trimesters were 151 ± 16, 145 ± 6 and 125±6 bpm respectively. The mean ± SD gestational age were 10 ± 2, 19 ± 3 and 34 ± 2 weeks for the first, second and third trimester respectively. Using ANOVA, there were statistically significant differences in FHR across the three trimesters (p ≤ 0.05). A positive correlation existed between maternal age and FHR (r = 0.57, p ≤ 0.05). CONCLUSION This study has established normal values for FHR in first, second and third trimester respectively. Referring physicians, radiologists, sonographers, obstetricians and gynaecologists may consider FHR of (135-167) bpm (139-151) bpm and (119-131) bpm as normal FHR ranges for the first, second and third trimester respectively. This study has also revealed the possibility of gestational age prediction using FHR with the equation [Gestational Age = 87.8 - (0.47) FHR]. IMPLICATIONS FOR PRACTICE This paper provides the most up-to-date sonographic FHR recommendations for fetal management. More importantly, findings from this study also suggests that ultrasound practitioners can use FHR measurements as a reliable alternative for fetal dating.
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Affiliation(s)
- P Ogenyi
- Radiology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
| | - H U Chiegwu
- Department of Radiography, Nnamdi Azikiwe University, Awka
| | - A England
- School of Medicine, University College Cork, Ireland
| | - U E Akanegbu
- Department of Radiography, Nnamdi Azikiwe University, Awka
| | - O S Ogbonna
- Department of Radiography, Nnamdi Azikiwe University, Awka
| | - A Abubakar
- Department of Radiography, University of Maiduguri, Nigeria
| | - G Luntsi
- Department of Radiography, University of Maiduguri, Nigeria
| | - D J Zira
- Department of Radiography, Federal University Lafia, Nigeria
| | - M Dauda
- Department of Medical Physics, Nasarawa State University, Keffi, Nigeria
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Kodkin V. Cardiotocography in Obstetrics: New Solutions for "Routine" Technology. SENSORS (BASEL, SWITZERLAND) 2022; 22:5126. [PMID: 35890806 PMCID: PMC9320740 DOI: 10.3390/s22145126] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 06/21/2022] [Accepted: 07/04/2022] [Indexed: 06/15/2023]
Abstract
This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 years. During this time, it has undergone many upgrades and has been characterized several times as a hopelessly outdated routine technology. Over the past 5-7 years, many in-depth studies and review papers on cardiotocography have appeared, which revealed both the problems and prospects of the technology. Basically, hopes are associated with artificial intelligence, which should increase the accuracy of the analysis of initially inaccurate measurements obtained using ultrasonic testing. At the same time, after the introduction of pulsed operating modes and the appearance of multi-chip sensors, the quality of the original signal remains practically unchanged. This circumstance makes the prospects of the technology very problematic. However, until now, there has not been a reliable replacement for this screening, which is equally safe, non-invasive, and accessible to a wide range of specialists, medical institutions, and patients. The paper discusses and substantiates proposals for improving the technology based on original (different from traditional CTG) methods of processing information received from ultrasonic sensors, which, in the author's opinion, allow for solving the main problems of CTG: identifying the correct direction of radiation to the fetal heart and to reliably evaluate beat-to-beat heart rate.
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Affiliation(s)
- Vladimir Kodkin
- Department of Electric Drive and Mechatronics, South Ural State University, 454080 Chelyabinsk, Russia
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Mertes G, Long Y, Liu Z, Li Y, Yang Y, Clifton DA. A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography. SENSORS (BASEL, SWITZERLAND) 2022; 22:3303. [PMID: 35591004 PMCID: PMC9103336 DOI: 10.3390/s22093303] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 05/28/2021] [Accepted: 06/01/2021] [Indexed: 06/15/2023]
Abstract
Non-invasive foetal electrocardiography (NI-FECG) has become an important prenatal monitoring method in the hospital. However, due to its susceptibility to non-stationary noise sources and lack of robust extraction methods, the capture of high-quality NI-FECG remains a challenge. Recording waveforms of sufficient quality for clinical use typically requires human visual inspection of each recording. A Signal Quality Index (SQI) can help to automate this task but, contrary to adult ECG, work on SQIs for NI-FECG is sparse. In this paper, a multi-channel signal quality classifier for NI-FECG waveforms is presented. The model can be used during the capture of NI-FECG to assist technicians to record high-quality waveforms, which is currently a labour-intensive task. A Convolutional Neural Network (CNN) is trained to distinguish between NI-FECG segments of high and low quality. NI-FECG recordings with one maternal channel and three abdominal channels were collected from 100 subjects during a routine hospital screening (102.6 min of data). The model achieves an average 10-fold cross-validated AUC of 0.95 ± 0.02. The results show that the model can reliably assess the FECG signal quality on our dataset. The proposed model can improve the automated capture and analysis of NI-FECG as well as reduce technician labour time.
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Affiliation(s)
- Gert Mertes
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX1 2JD, UK; (G.M.); (Z.L.); (D.A.C.)
- Oxford Suzhou Centre for Advanced Research, Suzhou 215123, China
| | - Yuan Long
- Department of Cardiovascular Medicine, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Huazhong University of Science and Technology, Wuhan 430015, China;
| | - Zhangdaihong Liu
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX1 2JD, UK; (G.M.); (Z.L.); (D.A.C.)
- Oxford Suzhou Centre for Advanced Research, Suzhou 215123, China
| | - Yuhui Li
- Department of Oncology, Central Hospital of Wuhan, Huazhong University of Science and Technology, Wuhan 430014, China;
| | - Yang Yang
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX1 2JD, UK; (G.M.); (Z.L.); (D.A.C.)
- Oxford Suzhou Centre for Advanced Research, Suzhou 215123, China
| | - David A. Clifton
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford OX1 2JD, UK; (G.M.); (Z.L.); (D.A.C.)
- Oxford Suzhou Centre for Advanced Research, Suzhou 215123, China
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Vargas-Calixto J, Warrick P, Kearney R. Estimation and Discriminability of Doppler Ultrasound Fetal Heart Rate Variability Measures. Front Artif Intell 2021; 4:674238. [PMID: 34490419 PMCID: PMC8417534 DOI: 10.3389/frai.2021.674238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/27/2021] [Indexed: 11/20/2022] Open
Abstract
Continuous electronic fetal monitoring and the access to databases of fetal heart rate (FHR) data have sparked the application of machine learning classifiers to identify fetal pathologies. However, most fetal heart rate data are acquired using Doppler ultrasound (DUS). DUS signals use autocorrelation (AC) to estimate the average heartbeat period within a window. In consequence, DUS FHR signals loses high frequency information to an extent that depends on the length of the AC window. We examined the effect of this on the estimation bias and discriminability of frequency domain features: low frequency power (LF: 0.03–0.15 Hz), movement frequency power (MF: 0.15–0.5 Hz), high frequency power (HF: 0.5–1 Hz), the LF/(MF + HF) ratio, and the nonlinear approximate entropy (ApEn) as a function of AC window length and signal to noise ratio. We found that the average discriminability loss across all evaluated AC window lengths and SNRs was 10.99% for LF 14.23% for MF, 13.33% for the HF, 10.39% for the LF/(MF + HF) ratio, and 24.17% for ApEn. This indicates that the frequency domain features are more robust to the AC method and additive noise than the ApEn. This is likely because additive noise increases the irregularity of the signals, which results in an overestimation of ApEn. In conclusion, our study found that the LF features are the most robust to the effects of the AC method and noise. Future studies should investigate the effect of other variables such as signal drop, gestational age, and the length of the analysis window on the estimation of fHRV features and their discriminability.
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Affiliation(s)
| | - Philip Warrick
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.,PeriGen Inc., Montreal, QC, Canada
| | - Robert Kearney
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
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Non-Invasive Fetal Electrocardiogram Monitoring Techniques: Potential and Future Research Opportunities in Smart Textiles. SIGNALS 2021. [DOI: 10.3390/signals2030025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
During the pregnancy, fetal electrocardiogram (FECG) is deployed to analyze fetal heart rate (FHR) of the fetus to indicate the growth and health of the fetus to determine any abnormalities and prevent diseases. The fetal electrocardiogram monitoring can be carried out either invasively by placing the electrodes on the scalp of the fetus, involving the skin penetration and the risk of infection, or non-invasively by recording the fetal heart rate signal from the mother’s abdomen through a placement of electrodes deploying portable, wearable devices. Non-invasive fetal electrocardiogram (NIFECG) is an evolving technology in fetal surveillance because of the comfort to the pregnant women and being achieved remotely, specifically in the unprecedented circumstances such as pandemic or COVID-19. Textiles have been at the heart of human technological progress for thousands of years, with textile developments closely tied to key inventions that have shaped societies. The relatively recent invention of smart textiles is set to push boundaries again and has already opened the potential for garments relevant to medicine, and health monitoring. This paper aims to discuss the different technologies and methods used in non-invasive fetal electrocardiogram (NIFECG) monitoring as well as the potential and future research directions of NIFECG in the smart textiles area.
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Biloborodova T, Scislo L, Skarga-Bandurova I, Sachenko A, Molgad A, Povoroznjuk O, Yevsieiva Y. Fetal ECG signal processing and identification of hypoxic pregnancy conditions in-utero. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:4919-4942. [PMID: 34198472 DOI: 10.3934/mbe.2021250] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The fetal heart rate (fHR) variability and fetal electrocardiogram (fECG) are considered the most important sources of information about fetal wellbeing. Non-invasive fetal monitoring and analysis of fECG are paramount for clinical trials. They enable examining the fetal health status and detecting the heart rate changes associated with insufficient oxygenation to cut the likelihood of hypoxic fetal injury. Despite the fact that significant advances have been achieved in electrocardiography and adult ECG signal processing, the analysis of fECG is still in its infancy. Due to accurate fetal morphology extraction techniques have not been properly developed, many areas require particular attention on the way of fully understanding the changes in variability in the fetus and implementation of the non-invasive techniques suitable for remote home care which is increasingly in demand for high-risk pregnancy monitoring. In this paper, we introduce an integrated approach for fECG signal extraction and processing based on various methods for fetal welfare investigation and hypoxia risk estimation. To the best of our knowledge, this is the first attempt to introduce the auto-generated risk scoring in fECG to achieve early warning on fetus' safety and provide the physician with additional information about the possible fetal complications. The proposed method includes the following stages: fECG extraction, fHR and fetal heart rate variability (fHRV) calculation, hypoxia index (HI) evaluation and risk estimation. The extracted signals were examined by assessing Signal to Noise Ratio (SNR) and mean square error (MSE) values. The results obtained demonstrated great potential, but more profound research and validation, as well as a consistent clinical study, are needed before implementation into the hospital and at-home monitoring.
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Affiliation(s)
- Tetiana Biloborodova
- Department of Computer Science and Engineering, Volodymyr Dahl East Ukrainian National University, 43 Donetska Street, Severodonetsk 93400, Ukraine
| | - Lukasz Scislo
- Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24 Street, Cracow 31155, Poland
| | - Inna Skarga-Bandurova
- School of Engineering, Computing and Mathematics, Oxford Brookes University, Wheatley Campus, Oxford, OX33 1HX, UK
| | - Anatoliy Sachenko
- Department of Informatics, Kazimierz Pulaski University of Technology and Humanities in Radom, Radom 26600, Poland
- Research Institute for Intelligent Computer Systems, West Ukrainian National University, Ternopil 46009, Ukraine
| | - Agnieszka Molgad
- Department of Informatics, Kazimierz Pulaski University of Technology and Humanities in Radom, Radom 26600, Poland
| | - Oksana Povoroznjuk
- Department of Computer Engineering and Programming, National Technical University "Kharkiv Polytechnic Institute," 2 Kyrpychova Street, Kharkiv 61002, Ukraine
| | - Yelyzaveta Yevsieiva
- School of Medicine, V. N. Karazin Kharkiv National University, 4 Svobody Square, Kharkiv 61002, Ukraine
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Katebi N, Marzbanrad F, Stroux L, Valderrama CE, Clifford GD. Unsupervised hidden semi-Markov model for automatic beat onset detection in 1D Doppler ultrasound. Physiol Meas 2020; 41:085007. [PMID: 32585651 DOI: 10.1088/1361-6579/aba006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE One dimensional (1D) Doppler ultrasound (DUS) is commonly used for fetal health assessment, during both regular prenatal visits and labor. It is used in preference to ECG and other modalities because of its simplicity and cost. To date, all analysis of such data has been confined to a smoothed, windowed heart rate estimation derived from the 1D DUS signal, reducing the potential of short-term variability information. A first step in improving the assessment of short-term variability of the fetal heart rate (FHR) is through implementing an accurate beat detector for 1D DUS signals. APPROACH This work presents an unsupervised probabilistic segmentation method enabled by a hidden semi-Markov model (HSMM). The proposed method employs envelope and spectral features for an online segmentation of fetal 1D DUS signal. The beat onsets and fetal cardiac beat-to-beat intervals are then estimated from the segmentations. For this work, two data sets were used, including 1D DUS recordings from five fetuses recorded in Germany, comprising 6521 beats and 45.06 minutes of data (dataset 1). Simultaneous fetal ECG (fECG) was used as the reference for beat timing. Dataset 2, comprising 4044 beats captured from 17 subjects in the UK was hand scored for beat location and was used as an independent held-out test set. Leave-one-out subject cross-validation was used for parameter tuning on dataset 1. No retraining was performed for dataset 2. To assess the performance of the beat onset detection, the root mean square error (RMSE), F1 score, sensitivity, positive predictivity (PPV) and the error in several standard common heart rate variability metrics were used. These metrics were evaluated on three fiducial points: (1) beat onset, (2) beat offset, and (3) middle of beat interval. MAIN RESULTS In dataset 1, the proposed method provided an RMSE of 20 ms, F1 score of 97.5 %, a Se of 97.6%, and a PPV of 97.3%. In dataset 2, the proposed method achieved an RMSE of 26 ms, an F1 score of 98.5 %, a Se of 98.0 % and a PPV of 98.9 %. It was also determined that the best beat-to-beat interval was derived from the onset of each beat. For the dataset 2, significant correlations were found in all short term heart rate variability metrics tested, both in the time and frequency domain. Only the proportion of successive normal-to-normal interval differences greater than 20 ms (pNN20) exhibited a significant absolute difference. SIGNIFICANCE This work presents the first-ever description of an algorithm to identify cardiac beats with 1D DUS, closely matching the fetal ECG-derived beats, to enable short-term heart rate variability analysis. The novel algorithm proposed requires no human labeling of data, and could have applicability beyond 1D DUS to other similar highly variable time series.
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Affiliation(s)
- Nasim Katebi
- Department of Biomedical Informatics, Emory University, Atlanta, GA, United States of America
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Bibbo D, Klinkovsky T, Penhaker M, Kudrna P, Peter L, Augustynek M, Kašík V, Kubicek J, Selamat A, Cerny M, Bielcik D. A New Approach for Testing Fetal Heart Rate Monitors. SENSORS 2020; 20:s20154139. [PMID: 32722397 PMCID: PMC7436177 DOI: 10.3390/s20154139] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/21/2020] [Accepted: 07/22/2020] [Indexed: 11/24/2022]
Abstract
In this paper, a new approach for the periodical testing and the functionality evaluation of a fetal heart rate monitor device based on ultrasound principle is proposed. The design and realization of the device are presented, together with the description of its features and functioning tests. In the designed device, a relay element, driven by an electric signal that allows switching at two specific frequencies, is used to simulate the fetus and the mother’s heartbeat. The simulator was designed to be compliant with the standard requirements for accurate assessment and measurement of medical devices. The accuracy of the simulated signals was evaluated, and it resulted to be stable and reliable. The generated frequencies show an error of about 0.5% with respect to the nominal one while the accuracy of the test equipment was within ±3% of the test signal set frequency. This value complies with the technical standard for the accuracy of fetal heart rate monitor devices. Moreover, the performed tests and measurements show the correct functionality of the developed simulator. The proposed equipment and testing respect the technical requirements for medical devices. The features of the proposed device make it simple and quick in testing a fetal heart rate monitor, thus providing an efficient way to evaluate and test the correlation capabilities of commercial apparatuses.
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Affiliation(s)
- Daniele Bibbo
- Department of Engineering, University of Roma Tre, Via Vito Volterra, 62, 00146 Rome, Italy
- Correspondence: ; Tel.: +39-06-5733-7298
| | - Tomas Klinkovsky
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Marek Penhaker
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Petr Kudrna
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, nam. Sitna 3105, 272 01 Kladno, Czech Republic;
| | - Lukas Peter
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Martin Augustynek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Vladimír Kašík
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Jan Kubicek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Ali Selamat
- Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia;
| | - Martin Cerny
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
| | - Daniel Bielcik
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic; (T.K.); (M.P.); (L.P.); (M.A.); (V.K.); (J.K.); (M.C.); (D.B.)
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New Method for Beat-to-Beat Fetal Heart Rate Measurement Using Doppler Ultrasound Signal. SENSORS 2020; 20:s20154079. [PMID: 32707863 PMCID: PMC7435740 DOI: 10.3390/s20154079] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/10/2020] [Accepted: 07/20/2020] [Indexed: 11/17/2022]
Abstract
The most commonly used method of fetal monitoring is based on heart activity analysis. Computer-aided fetal monitoring system enables extraction of clinically important information hidden for visual interpretation—the instantaneous fetal heart rate (FHR) variability. Today’s fetal monitors are based on monitoring of mechanical activity of the fetal heart by means of Doppler ultrasound technique. The FHR is determined using autocorrelation methods, and thus it has a form of evenly spaced—every 250 ms—instantaneous measurements, where some of which are incorrect or duplicate. The parameters describing a beat-to-beat FHR variability calculated from such a signal show significant errors. The aim of our research was to develop new analysis methods that will both improve an accuracy of the FHR determination and provide FHR representation as time series of events. The study was carried out on simultaneously recorded (during labor) Doppler ultrasound signal and the reference direct fetal electrocardiogram Two subranges of Doppler bandwidths were separated to describe heart wall movements and valve motions. After reduction of signal complexity by determining the Doppler ultrasound envelope, the signal was analyzed to determine the FHR. The autocorrelation method supported by a trapezoidal prediction function was used. In the final stage, two different methods were developed to provide signal representation as time series of events: the first using correction of duplicate measurements and the second based on segmentation of instantaneous periodicity measurements. Thus, it ensured the mean heart interval measurement error of only 1.35 ms. In a case of beat-to-beat variability assessment the errors ranged from −1.9% to −10.1%. Comparing the obtained values to other published results clearly confirms that the new methods provides a higher accuracy of an interval measurement and a better reliability of the FHR variability estimation.
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Hamelmann P, Vullings R, Kolen AF, Bergmans JWM, van Laar JOEH, Tortoli P, Mischi M. Doppler Ultrasound Technology for Fetal Heart Rate Monitoring: A Review. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:226-238. [PMID: 31562079 DOI: 10.1109/tuffc.2019.2943626] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Fetal well-being is commonly assessed by monitoring the fetal heart rate (fHR). In clinical practice, the de facto standard technology for fHR monitoring is based on the Doppler ultrasound (US). Continuous monitoring of the fHR before and during labor is performed using a US transducer fixed on the maternal abdomen. The continuous fHR monitoring, together with simultaneous monitoring of the uterine activity, is referred to as cardiotocography (CTG). In contrast, for intermittent measurements of the fHR, a handheld Doppler US transducer is typically used. In this article, the technology of Doppler US for continuous fHR monitoring and intermittent fHR measurements is described, with emphasis on fHR monitoring for CTG. Special attention is dedicated to the measurement environment, which includes the clinical setting in which fHR monitoring is commonly performed. In addition, to understand the signal content of acquired Doppler US signals, the anatomy and physiology of the fetal heart and the surrounding maternal abdomen are described. The challenges encountered in these measurements have led to different technological strategies, which are presented and critically discussed, with a focus on the US transducer geometry, Doppler signal processing, and fHR extraction methods.
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14
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Hamelmann P, Mischi M, Kolen AF, van Laar JOEH, Vullings R, Bergmans JWM. Fetal Heart Rate Monitoring Implemented by Dynamic Adaptation of Transmission Power of a Flexible Ultrasound Transducer Array. SENSORS 2019; 19:s19051195. [PMID: 30857218 PMCID: PMC6427711 DOI: 10.3390/s19051195] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 02/28/2019] [Accepted: 03/04/2019] [Indexed: 11/16/2022]
Abstract
Fetal heart rate (fHR) monitoring using Doppler Ultrasound (US) is a standard method to assess fetal health before and during labor. Typically, an US transducer is positioned on the maternal abdomen and directed towards the fetal heart. Due to fetal movement or displacement of the transducer, the relative fetal heart location (fHL) with respect to the US transducer can change, leading to frequent periods of signal loss. Consequently, frequent repositioning of the US transducer is required, which is a cumbersome task affecting clinical workflow. In this research, a new flexible US transducer array is proposed which allows for measuring the fHR independently of the fHL. In addition, a method for dynamic adaptation of the transmission power of this array is introduced with the aim of reducing the total acoustic dose transmitted to the fetus and the associated power consumption, which is an important requirement for application in an ambulatory setting. The method is evaluated using an in-vitro setup of a beating chicken heart. We demonstrate that the signal quality of the Doppler signal acquired with the proposed method is comparable to that of a standard, clinical US transducer. At the same time, our transducer array is able to measure the fHR for varying fHL while only using 50% of the total transmission power of standard, clinical US transducers.
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Affiliation(s)
- Paul Hamelmann
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.
| | | | | | - Rik Vullings
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.
| | - Jan W M Bergmans
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.
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15
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Valderrama CE, Stroux L, Katebi N, Paljug E, Hall-Clifford R, Rohloff P, Marzbanrad F, Clifford GD. An open source autocorrelation-based method for fetal heart rate estimation from one-dimensional Doppler ultrasound. Physiol Meas 2019; 40:025005. [PMID: 30699403 PMCID: PMC8325598 DOI: 10.1088/1361-6579/ab033d] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Open research on fetal heart rate (FHR) estimation is relatively rare, and evidence for the utility of metrics derived from Doppler ultrasound devices has historically remained hidden in the proprietary documentation of commercial entities, thereby inhibiting its assessment and improvement. Nevertheless, recent studies have attempted to improve FHR estimation; however, these methods were developed and tested using datasets composed of few subjects and are therefore unlikely to be generalizable on a population level. The work presented here introduces a reproducible and generalizable autocorrelation (AC)-based method for FHR estimation from one-dimensional Doppler ultrasound (1D-DUS) signals. APPROACH Simultaneous fetal electrocardiogram (fECG) and 1D-DUS signals generated by a hand-held Doppler transducer in a fixed position were captured by trained healthcare workers in a European hospital. The fECG QRS complexes were identified using a previously published fECG extraction algorithm and were then over-read to ensure accuracy. An AC-based method to estimate FHR was then developed on this data, using a total of 721 1D-DUS segments, each 3.75 s long, and parameters were tuned with Bayesian optimization. The trained FHR estimator was tested on two additional (independent) hand-annotated Doppler-only datasets recorded with the same device but on different populations: one composed of 3938 segments (from 99 fetuses) acquired in rural Guatemala, and another composed of 894 segments (from 17 fetuses) recorded in a hospital in the UK. MAIN RESULTS The proposed AC-based method was able to estimate FHR within 10% of the reference FHR values 96% of the time, with an accuracy of 97% for manually identified good quality segments in both of the independent test sets. SIGNIFICANCE This is the first work to publish open source code for FHR estimation from 1D-DUS data. The method was shown to satisfy estimations within 10% of the reference FHR values and it therefore defines a minimum accuracy for the field to match or surpass. Our work establishes a basis from which future methods can be developed to more accurately estimate FHR variability for assessing fetal wellbeing from 1D-DUS signals.
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Affiliation(s)
- Camilo E Valderrama
- Department of Biomedical Informatics, Emory University, Atlanta, GA, United States of America
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16
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Tang H, Wang T, Li M, Yang X. The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2018; 2018:8568617. [PMID: 30627211 PMCID: PMC6305052 DOI: 10.1155/2018/8568617] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2018] [Accepted: 11/12/2018] [Indexed: 11/30/2022]
Abstract
Mobile medical care is a hot issue in current medical research. Due to the inconvenience of going to hospital for fetal heart monitoring and the limited medical resources, real-time monitoring of fetal health on portable devices has become an urgent need for pregnant women, which helps to protect the health of the fetus in a more comprehensive manner and reduce the workload of doctors. For the feature acquisition of the fetal heart rate (FHR) signal, the traditional feature-based classification methods need to manually read the morphological features from the FHR curve, which is time-consuming and costly and has a certain degree of calibration bias. This paper proposes a classification method of the FHR signal based on neural networks, which can avoid manual feature acquisition and reduce the error caused by human factors. The algorithm will directly learn from the FHR data and truly realize the real-time diagnosis of FHR data. The convolution neural network classification method named "MKNet" and recurrent neural network named "MKRNN" are designed. The main contents of this paper include the preprocessing of the FHR signal, the training of the classification model, and the experiment evaluation. Finally, MKNet is proved to be the best algorithm for real-time FHR signal classification.
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Affiliation(s)
- Haijing Tang
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 10081, China
| | - Taoyi Wang
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 10081, China
| | - Mengke Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 10081, China
| | - Xu Yang
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing 10081, China
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17
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Jaros R, Martinek R, Kahankova R. Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal. SENSORS 2018; 18:s18113648. [PMID: 30373259 PMCID: PMC6263968 DOI: 10.3390/s18113648] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 10/18/2018] [Accepted: 10/24/2018] [Indexed: 11/16/2022]
Abstract
Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.
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Affiliation(s)
- Rene Jaros
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic.
| | - Radek Martinek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic.
| | - Radana Kahankova
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic.
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18
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Marzbanrad F, Stroux L, Clifford GD. Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring. Physiol Meas 2018; 39:08TR01. [PMID: 30027897 PMCID: PMC6237616 DOI: 10.1088/1361-6579/aad4d1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
One-dimensional Doppler ultrasound (1D-DUS) provides a low-cost and simple method for acquiring a rich signal for use in cardiovascular screening. However, despite the use of 1D-DUS in cardiotocography (CTG) for decades, there are still challenges that limit the effectiveness of its users in reducing fetal and neonatal morbidities and mortalities. This is partly due to the noisy, transient, complex and nonstationary nature of the 1D-DUS signals. Current challenges also include lack of efficient signal quality metrics, insufficient signal processing techniques for extraction of fetal heart rate and other vital parameters with adequate temporal resolution, and lack of appropriate clinical decision support for CTG and Doppler interpretation. Moreover, the almost complete lack of open research in both hardware and software in this field, as well as commercial pressures to market the much more expensive and difficult to use Doppler imaging devices, has hampered innovation. This paper reviews the basics of fetal cardiac function, 1D-DUS signal generation and processing, its application in fetal monitoring and assessment of fetal development and wellbeing. It also provides recommendations for future development of signal processing and modeling approaches, to improve the application of 1D-DUS in fetal monitoring, as well as the need for annotated open databases.
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Affiliation(s)
- Faezeh Marzbanrad
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC, Australia
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19
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Foetal heart rate estimation by empirical mode decomposition and MUSIC spectrum. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2018.01.024] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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20
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Kording F, Schoennagel BP, de Sousa MT, Fehrs K, Adam G, Yamamura J, Ruprecht C. Evaluation of a Portable Doppler Ultrasound Gating Device for Fetal Cardiac MR Imaging: Initial Results at 1.5T and 3T. Magn Reson Med Sci 2018; 17:308-317. [PMID: 29467359 PMCID: PMC6196307 DOI: 10.2463/mrms.mp.2017-0100] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Purpose: Fetal cardiac MRI has the potential to play an important role in the assessment of fetal cardiac pathologies, but it is up to now not feasible due to a missing gating method. The purpose of this work was the evaluation of Doppler ultrasound (DUS) for external fetal cardiac gating with regard to compatibility, functionality, and reliability. Preliminary results were assessed performing fetal cardiac MRI. Methods: An MRI conditional DUS device was developed to obtain a gating signal from the fetal heart. The MRI compatibility was evaluated at 1.5T and 3T using B1 field maps and gradient echo images. The quality and sensitivity of the DUS device to detect the fetal heart motion for cardiac gating were evaluated outside the MRI room in 15 fetuses. A dynamic fetal cardiac phantom was employed to evaluate distortions of the DUS device and gating signal due to electromagnetic interferences at 1.5T and 3T. In the first in vivo experience, dynamic fetal cardiac images were acquired in four-chamber view at 1.5T and 3T in two fetuses. Results: The maximum change in the B1 field and signal intensity with and without the DUS device was <6.5% for 1.5T and 3T. The sensitivity of the DUS device to detect the fetal heartbeat was 99.1%. Validation of the DUS device using the fetal cardiac phantom revealed no electromagnetic interferences at 1.5T or 3T and a high correlation to the simulated heart frequencies. Fetal cardiac cine images were successfully applied and showed good image quality. Conclusion: An MR conditional DUS gating device was developed and evaluated revealing safety, compatibility, and reliability for different field strengths. In a preliminary experience, the DUS device was successfully applied for in vivo fetal cardiac imaging at 1.5T and 3T.
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Affiliation(s)
- Fabian Kording
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf.,northh medical GmbH
| | - Bjoern P Schoennagel
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf
| | | | - Kai Fehrs
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf.,northh medical GmbH
| | - Gerhard Adam
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf
| | - Jin Yamamura
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf
| | - Christian Ruprecht
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf.,northh medical GmbH
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21
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Alnuaimi SA, Jimaa S, Khandoker AH. Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions. Front Bioeng Biotechnol 2017; 5:82. [PMID: 29312932 PMCID: PMC5743703 DOI: 10.3389/fbioe.2017.00082] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Accepted: 12/11/2017] [Indexed: 11/13/2022] Open
Abstract
The fetal Doppler Ultrasound (DUS) is commonly used for monitoring fetal heart rate and can also be used for identifying the event timings of fetal cardiac valve motions. In early-stage fetuses, the detected Doppler signal suffers from noise and signal loss due to the fetal movements and changing fetal location during the measurement procedure. The fetal cardiac intervals, which can be estimated by measuring the fetal cardiac event timings, are the most important markers of fetal development and well-being. To advance DUS-based fetal monitoring methods, several powerful and well-advanced signal processing and machine learning methods have recently been developed. This review provides an overview of the existing techniques used in fetal cardiac activity monitoring and a comprehensive survey on fetal cardiac Doppler signal processing frameworks. The review is structured with a focus on their shortcomings and advantages, which helps in understanding fetal Doppler cardiogram signal processing methods and the related Doppler signal analysis procedures by providing valuable clinical information. Finally, a set of recommendations are suggested for future research directions and the use of fetal cardiac Doppler signal analysis, processing, and modeling to address the underlying challenges.
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Affiliation(s)
| | - Shihab Jimaa
- Department of Electrical and Computer Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Ahsan H. Khandoker
- Department of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
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22
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Hurnanen T, Lehtonen E, Tadi MJ, Kuusela T, Kiviniemi T, Saraste A, Vasankari T, Airaksinen J, Koivisto T, Pankaala M. Automated Detection of Atrial Fibrillation Based on Time–Frequency Analysis of Seismocardiograms. IEEE J Biomed Health Inform 2017; 21:1233-1241. [DOI: 10.1109/jbhi.2016.2621887] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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23
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Al-Angari HM, Kimura Y, Hadjileontiadis LJ, Khandoker AH. A Hybrid EMD-Kurtosis Method for Estimating Fetal Heart Rate from Continuous Doppler Signals. Front Physiol 2017; 8:641. [PMID: 28912727 PMCID: PMC5582307 DOI: 10.3389/fphys.2017.00641] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2017] [Accepted: 08/15/2017] [Indexed: 11/13/2022] Open
Abstract
Monitoring of fetal heart rate (FHR) is an important measure of fetal wellbeing during the months of pregnancy. Previous works on estimating FHR variability from Doppler ultrasound (DUS) signal mainly through autocorrelation analysis showed low accuracy when compared with heart rate variability (HRV) computed from fetal electrocardiography (fECG). In this work, we proposed a method based on empirical mode decomposition (EMD) and the kurtosis statistics to estimate FHR and its variability from DUS. Comparison between estimated beat-to-beat intervals using the proposed method and the autocorrelation function (AF) with respect to RR intervals computed from fECG as the ground truth was done on DUS signals from 44 pregnant mothers in the early (20 cases) and late (24 cases) gestational weeks. The new EMD-kurtosis method showed significant lower error in estimating the number of beats in the early group (EMD-kurtosis: 2.2% vs. AF: 8.5%, p < 0.01, root mean squared error) and the late group (EMD-kurtosis: 2.9% vs. AF: 6.2%). The EMD-kurtosis method was also found to be better in estimating mean beat-to-beat with an average difference of 1.6 ms from true mean RR compared to 19.3 ms by using the AF method. However, the EMD-kurtosis performed worse than AF in estimating SNDD and RMSSD. The proposed EMD-kurtosis method is more robust than AF in low signal-to-noise ratio cases and can be used in a hybrid system to estimate beat-to-beat intervals from DUS. Further analysis to reduce the estimated beat-to-beat variability from the EMD-kurtosis method is needed.
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Affiliation(s)
- Haitham M Al-Angari
- Department of Biomedical Engineering, Khalifa University of Science and TechnologyAbu Dhabi, United Arab Emirates
| | | | - Leontios J Hadjileontiadis
- Department of Electrical and Computer Engineering, Khalifa University of Science and TechnologyAbu Dhabi, United Arab Emirates.,Department of Electrical and Computer Engineering, Aristotle University of ThessalonikiThessaloniki, Greece
| | - Ahsan H Khandoker
- Department of Biomedical Engineering, Khalifa University of Science and TechnologyAbu Dhabi, United Arab Emirates
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24
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Jezewski J, Wrobel J, Matonia A, Horoba K, Martinek R, Kupka T, Jezewski M. Is Abdominal Fetal Electrocardiography an Alternative to Doppler Ultrasound for FHR Variability Evaluation? Front Physiol 2017; 8:305. [PMID: 28559852 PMCID: PMC5432618 DOI: 10.3389/fphys.2017.00305] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Accepted: 04/27/2017] [Indexed: 12/02/2022] Open
Abstract
Great expectations are connected with application of indirect fetal electrocardiography (FECG), especially for home telemonitoring of pregnancy. Evaluation of fetal heart rate (FHR) variability, when determined from FECG, uses the same criteria as for FHR signal acquired classically—through ultrasound Doppler method (US). Therefore, the equivalence of those two methods has to be confirmed, both in terms of recognizing classical FHR patterns: baseline, accelerations/decelerations (A/D), long-term variability (LTV), as well as evaluating the FHR variability with beat-to-beat accuracy—short-term variability (STV). The research material consisted of recordings collected from 60 patients in physiological and complicated pregnancy. The FHR signals of at least 30 min duration were acquired dually, using two systems for fetal and maternal monitoring, based on US and FECG methods. Recordings were retrospectively divided into normal (41) and abnormal (19) fetal outcome. The complex process of data synchronization and validation was performed. Obtained low level of the signal loss (4.5% for US and 1.8% for FECG method) enabled to perform both direct comparison of FHR signals, as well as indirect one—by using clinically relevant parameters. Direct comparison showed that there is no measurement bias between the acquisition methods, whereas the mean absolute difference, important for both visual and computer-aided signal analysis, was equal to 1.2 bpm. Such low differences do not affect the visual assessment of the FHR signal. However, in the indirect comparison the inconsistencies of several percent were noted. This mainly affects the acceleration (7.8%) and particularly deceleration (54%) patterns. In the signals acquired using the electrocardiography the obtained STV and LTV indices have shown significant overestimation by 10 and 50% respectively. It also turned out, that ability of clinical parameters to distinguish between normal and abnormal groups do not depend on the acquisition method. The obtained results prove that the abdominal FECG, considered as an alternative to the ultrasound approach, does not change the interpretation of the FHR signal, which was confirmed during both visual assessment and automated analysis.
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Affiliation(s)
- Janusz Jezewski
- Institute of Medical Technology and Equipment ITAMZabrze, Poland
| | - Janusz Wrobel
- Institute of Medical Technology and Equipment ITAMZabrze, Poland
| | - Adam Matonia
- Institute of Medical Technology and Equipment ITAMZabrze, Poland
| | - Krzysztof Horoba
- Institute of Medical Technology and Equipment ITAMZabrze, Poland
| | - Radek Martinek
- Department of Cybernetics and Biomedical Engineering, VSB-Technical University of OstravaOstrava, Czechia
| | - Tomasz Kupka
- Institute of Medical Technology and Equipment ITAMZabrze, Poland
| | - Michal Jezewski
- Institute of Electronics, Silesian University of TechnologyGliwice, Poland
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25
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Jafari Tadi M, Lehtonen E, Hurnanen T, Koskinen J, Eriksson J, Pänkäälä M, Teräs M, Koivisto T. A real-time approach for heart rate monitoring using a Hilbert transform in seismocardiograms. Physiol Meas 2016; 37:1885-1909. [PMID: 27681033 DOI: 10.1088/0967-3334/37/11/1885] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Heart rate monitoring helps in assessing the functionality and condition of the cardiovascular system. We present a new real-time applicable approach for estimating beat-to-beat time intervals and heart rate in seismocardiograms acquired from a tri-axial microelectromechanical accelerometer. Seismocardiography (SCG) is a non-invasive method for heart monitoring which measures the mechanical activity of the heart. Measuring true beat-to-beat time intervals from SCG could be used for monitoring of the heart rhythm, for heart rate variability analysis and for many other clinical applications. In this paper we present the Hilbert adaptive beat identification technique for the detection of heartbeat timings and inter-beat time intervals in SCG from healthy volunteers in three different positions, i.e. supine, left and right recumbent. Our method is electrocardiogram (ECG) independent, as it does not require any ECG fiducial points to estimate the beat-to-beat intervals. The performance of the algorithm was tested against standard ECG measurements. The average true positive rate, positive prediction value and detection error rate for the different positions were, respectively, supine (95.8%, 96.0% and ≃0.6%), left (99.3%, 98.8% and ≃0.001%) and right (99.53%, 99.3% and ≃0.01%). High correlation and agreement was observed between SCG and ECG inter-beat intervals (r > 0.99) for all positions, which highlights the capability of the algorithm for SCG heart monitoring from different positions. Additionally, we demonstrate the applicability of the proposed method in smartphone based SCG. In conclusion, the proposed algorithm can be used for real-time continuous unobtrusive cardiac monitoring, smartphone cardiography, and in wearable devices aimed at health and well-being applications.
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Affiliation(s)
- Mojtaba Jafari Tadi
- Department of Cardiology and Cardiovascular Medicine, Faculty of Medicine, University of Turku, Finland. Technology Research Center, University of Turku, Turku, Finland
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26
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Lee KJ, Lee B. Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG. SENSORS 2016; 16:s16071020. [PMID: 27376296 PMCID: PMC4970070 DOI: 10.3390/s16071020] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 06/24/2016] [Accepted: 06/29/2016] [Indexed: 11/16/2022]
Abstract
Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.
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Affiliation(s)
- Kwang Jin Lee
- Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea.
| | - Boreom Lee
- Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea.
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Quintana DS, Alvares GA, Heathers JAJ. Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH): recommendations to advance research communication. Transl Psychiatry 2016; 6:e803. [PMID: 27163204 PMCID: PMC5070064 DOI: 10.1038/tp.2016.73] [Citation(s) in RCA: 222] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 03/18/2016] [Accepted: 03/23/2016] [Indexed: 12/11/2022] Open
Abstract
The number of publications investigating heart rate variability (HRV) in psychiatry and the behavioral sciences has increased markedly in the last decade. In addition to the significant debates surrounding ideal methods to collect and interpret measures of HRV, standardized reporting of methodology in this field is lacking. Commonly cited recommendations were designed well before recent calls to improve research communication and reproducibility across disciplines. In an effort to standardize reporting, we propose the Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH), a checklist with four domains: participant selection, interbeat interval collection, data preparation and HRV calculation. This paper provides an overview of these four domains and why their standardized reporting is necessary to suitably evaluate HRV research in psychiatry and related disciplines. Adherence to these communication guidelines will help expedite the translation of HRV research into a potential psychiatric biomarker by improving interpretation, reproducibility and future meta-analyses.
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Affiliation(s)
- D S Quintana
- Division of Mental Health and Addiction, NORMENT, KG Jebsen Centre for Psychosis Research, University of Oslo, Oslo University Hospital, Oslo, Norway,Division of Mental Health and Addiction, NORMENT, KG Jebsen Centre for Psychosis Research, University of Oslo, Oslo University Hospital, Building 49, Oslo University Hospital, Ullevål, Kirkeveien 166, PO Box 4956, Nydalen, Oslo N-0424, Norway. E-mail:
| | - G A Alvares
- Telethon Kids Institute, University of Western Australia, Perth, WA, Australia,Cooperative Research Centre for Living with Autism (Autism CRC), Brisbane, QLD, Australia
| | - J A J Heathers
- School of Psychology, University of Sydney, Sydney, NSW, Australia,Department of Cardiology and Intensive Therapy, Poznań University of Medical Sciences, Poznań, Poland
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Sikdar A, Behera SK, Dogra DP. Computer-Vision-Guided Human Pulse Rate Estimation: A Review. IEEE Rev Biomed Eng 2016; 9:91-105. [PMID: 27071193 DOI: 10.1109/rbme.2016.2551778] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Human pulse rate (PR) can be estimated in several ways, including measurement instruments that directly count the PR through contact- and noncontact-based approaches. Over the last decade, computer-vision-assisted noncontact-based PR estimation has evolved significantly. Such techniques can be adopted for clinical purposes to mitigate some of the limitations of contact-based techniques. However, existing vision-guided noncontact-based techniques have not been benchmarked with respect to a challenging dataset. In view of this, we present a systematic review of such techniques implemented over a uniform computing platform. We have simultaneously recorded the PR and video of 14 volunteers. Five sets of data have been recorded for every volunteer using five different experimental conditions by varying the distance from the camera and illumination condition. Pros and cons of the existing noncontact image- and video-based PR techniques have been discussed with respect to our dataset. Experimental evaluation suggests that image- or video-based PR estimation can be highly effective for nonclinical purposes, and some of these approaches are very promising toward developing clinical applications. The present review is the first in this field of contactless vision-guided PR estimation research.
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Evaluating the fetal heart rate baseline estimation algorithms by their influence on detection of clinically important patterns. Biocybern Biomed Eng 2016. [DOI: 10.1016/j.bbe.2016.06.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Horoba K, Wrobel J, Jezewski J, Kupka T, Roj D, Jezewski M. Automated detection of uterine contractions in tocography signals – Comparison of algorithms. Biocybern Biomed Eng 2016. [DOI: 10.1016/j.bbe.2016.08.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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31
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Comparison of the effect of different sampling modes on computer analysis of cardiotocograms. Comput Biol Med 2015; 64:62-6. [DOI: 10.1016/j.compbiomed.2015.06.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2015] [Revised: 05/25/2015] [Accepted: 06/15/2015] [Indexed: 11/19/2022]
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Kording F, Schoennagel B, Lund G, Ueberle F, Jung C, Adam G, Yamamura J. Doppler ultrasound compared with electrocardiogram and pulse oximetry cardiac triggering: A pilot study. Magn Reson Med 2014; 74:1257-65. [DOI: 10.1002/mrm.25502] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2014] [Revised: 10/01/2014] [Accepted: 10/06/2014] [Indexed: 11/07/2022]
Affiliation(s)
- Fabian Kording
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
| | - Bjoern Schoennagel
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
| | - Gunnar Lund
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
| | | | - Caroline Jung
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
| | - Gerhard Adam
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
| | - Jin Yamamura
- University Medical Centre Hamburg-Eppendorf, Centre for Radiology and Endoscopy, Department of Diagnostic and Interventional Radiology; Germany
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Babbs CF. Noninvasive measurement of cardiac stroke volume using pulse wave velocity and aortic dimensions: a simulation study. Biomed Eng Online 2014; 13:137. [PMID: 25238910 PMCID: PMC4271357 DOI: 10.1186/1475-925x-13-137] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 09/16/2014] [Indexed: 12/02/2022] Open
Abstract
Background Concerns about the cost-effectiveness of invasive hemodynamic monitoring in critically ill patients using pulmonary artery catheters motivate a renewed search for effective noninvasive methods to measure stroke volume. This paper explores a new approach based on noninvasively measured pulse wave velocity, pulse contour, and ultrasonically determined aortic cross sectional area. Methods The Bramwell-Hill equation relating pulse wave velocity to aortic compliance is applied. At the time point on the noninvasively measured pulse contour, denoted th, when pulse amplitude has fallen midway between systolic and diastolic values, the portion of stroke volume remaining in the aorta, and in turn the entire stroke volume, can be estimated from the compliance and the pulse waveform. This approach is tested and refined using a numerical model of the systemic circulation including the effects of blood inertia, nonlinear compliance, aortic tapering, varying heart rate, and varying myocardial contractility, in which noninvasively estimated stroke volumes were compared with known stroke volumes in the model. Results The Bramwell-Hill approach correctly allows accurate calculation of known, constant aortic compliance in the numerical model. When nonlinear compliance is present the proposed noninvasive technique overestimates true aortic compliance when pulse pressure is large. However, a reasonable correction for nonlinearity can be derived and applied to restore accuracy for normal and for fast heart rates (correlation coefficient > 0.98). Conclusions Accurate estimates of cardiac stroke volume based on pulse wave velocity are theoretically possible and feasible. The precision of the method may be less than desired, owing to the dependence of the final result on the square of measured pulse wave velocity and the first power of ultrasonically measured aortic cross sectional area. However, classical formulas for propagation of random errors suggest that the method may still have sufficient precision for clinical applications. It remains as a challenge for experimentalists to explore further the potential of noninvasive measurement of stroke volume using pulse wave velocity. The technique is non-proprietary and open access in full detail, allowing future users to modify and refine the method as guided by practical experience.
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Affiliation(s)
- Charles F Babbs
- Weldon School of Biomedical Engineering, Purdue University, 206 South Martin Jische Drive, West Lafayette, Indiana 47907-2032, USA.
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Chudáček V, Spilka J, Burša M, Janků P, Hruban L, Huptych M, Lhotská L. Open access intrapartum CTG database. BMC Pregnancy Childbirth 2014; 14:16. [PMID: 24418387 PMCID: PMC3898997 DOI: 10.1186/1471-2393-14-16] [Citation(s) in RCA: 96] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2013] [Accepted: 12/06/2013] [Indexed: 11/10/2022] Open
Abstract
Background Cardiotocography (CTG) is a monitoring of fetal heart rate and uterine contractions. Since 1960 it is routinely used by obstetricians to assess fetal well-being. Many attempts to introduce methods of automatic signal processing and evaluation have appeared during the last 20 years, however still no significant progress similar to that in the domain of adult heart rate variability, where open access databases are available (e.g. MIT-BIH), is visible. Based on a thorough review of the relevant publications, presented in this paper, the shortcomings of the current state are obvious. A lack of common ground for clinicians and technicians in the field hinders clinically usable progress. Our open access database of digital intrapartum cardiotocographic recordings aims to change that. Description The intrapartum CTG database consists in total of 552 intrapartum recordings, which were acquired between April 2010 and August 2012 at the obstetrics ward of the University Hospital in Brno, Czech Republic. All recordings were stored in electronic form in the OB TraceVue®;system. The recordings were selected from 9164 intrapartum recordings with clinical as well as technical considerations in mind. All recordings are at most 90 minutes long and start a maximum of 90 minutes before delivery. The time relation of CTG to delivery is known as well as the length of the second stage of labor which does not exceed 30 minutes. The majority of recordings (all but 46 cesarean sections) is – on purpose – from vaginal deliveries. All recordings have available biochemical markers as well as some more general clinical features. Full description of the database and reasoning behind selection of the parameters is presented in the paper. Conclusion A new open-access CTG database is introduced which should give the research community common ground for comparison of results on reasonably large database. We anticipate that after reading the paper, the reader will understand the context of the field from clinical and technical perspectives which will enable him/her to use the database and also understand its limitations.
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Affiliation(s)
- Václav Chudáček
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
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Oweis RJ, As'ad H, Aldarawsheh A, Al-Khdeirat R, Lwissy K. A PC-aided optical foetal heart rate detection system. J Med Eng Technol 2013; 38:23-31. [PMID: 24195701 DOI: 10.3109/03091902.2013.849299] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Safe monitoring of foetal heart rate is a valuable tool for the healthy evolution and wellbeing of both foetus and mother. This paper presents a non-invasive optical technique that allows for foetal heart rate detection using a photovoltaic infrared (IR) detector placed on the mother's abdomen. The system presented here consists of a photoplethysmography (PPG) circuit, abdomen circuit and a personal computer equipped with MATLAB. A near IR beam having a wavelength of 880 nm is transmitted through the mother's abdomen and foetal tissue. The received abdominal signal that conveys information pertaining to the mother and foetal heart rate is sensed by a low noise photodetector. The PC receives the signal through the National Instrumentation Data Acquisition Card (NIDAQ). After synchronous detection of the abdominal and finger PPG signals, the designed MATLAB-based software saves, analyses and extracts information related to the foetal heart rate. Extraction is carried out using recursive least squares adaptive filtration. Measurements on eight pregnant women with gestational periods ranging from 35-39 weeks were performed using the proposed system and CTG. Results show a correlation coefficient of 0.978 and a correlation confidence interval between 88-99.6%. The t test results in a p value of 0.034, which is less than 0.05. Low power, low cost, high signal-to-noise ratio, reduction of ambient light effect and ease of use are the main characteristics of the proposed system.
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Affiliation(s)
- Rami J Oweis
- Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology , PO Box 3030, Irbid 22110 , Jordan
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Wróbel J, Horoba K, Pander T, Jeżewski J, Czabański R. Improving fetal heart rate signal interpretation by application of myriad filtering. Biocybern Biomed Eng 2013. [DOI: 10.1016/j.bbe.2013.09.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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