{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:33:36Z","timestamp":1760708016140,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2009,1,16]],"date-time":"2009-01-16T00:00:00Z","timestamp":1232064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The aim of the present study is to obtain a highly objective automatic fetal heart rate (FHR) diagnosis. The neural network software was composed of three layers with the back propagation, to which 8 FHR data, including sinusoidal FHR, were input and the system was educated by the data of 20 cases with a known outcome. The output was the probability of a normal, intermediate, or pathologic outcome. The neural index studied prolonged monitoring. The neonatal states and the FHR score strongly correlated with the outcome probability. The neural index diagnosis was correct. The completed software was transferred to other computers, where the system function was correct.<\/jats:p>","DOI":"10.3390\/a2010019","type":"journal-article","created":{"date-parts":[[2009,1,16]],"date-time":"2009-01-16T10:49:08Z","timestamp":1232102948000},"page":"19-30","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Neural Network Analysis and Evaluation of the Fetal Heart Rate"],"prefix":"10.3390","volume":"2","author":[{"given":"Yasuaki","family":"Noguchi","sequence":"first","affiliation":[{"name":"Department of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan"}]},{"given":"Fujihiko","family":"Matsumoto","sequence":"additional","affiliation":[{"name":"Department of Applied Physics, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan"}]},{"given":"Kazuo","family":"Maeda","sequence":"additional","affiliation":[{"name":"Professor Emeritus, Department of Obstetrics and Gynecology, Tottori University. Home: 3-125, Nadamachi, Yonago, Tottori, 683-0835, Japan"}]},{"given":"Takashi","family":"Nagasawa","sequence":"additional","affiliation":[{"name":"Department of Information Technology, TOITU Ltd., 1-5-10, Ebisu-west, Shibuyaku, Tokyo, 150-0021, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2009,1,16]]},"reference":[{"key":"ref_1","unstructured":"Maeda, K. Fetal heart sound recorded by using slow down tape technique. Proc. 8th Int. Conf. Med. Biol. Eng., Session 19-2."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1111\/j.1471-0528.1971.tb00212.x","article-title":"Configuration of the fetal electrocardiogram in relation to the fetal acid-base balance and plasma electrolytes","volume":"78","author":"Symonds","year":"1971","journal-title":"J. Obstetet. Gynaecol. Brit. Commonw."},{"key":"ref_3","unstructured":"Gentner, O., and Hammacher, K. An improved method for the determination of the instantaneous fetal heart frequency from the fetal phonocardiogram. Proc. 7th Int. Conf. Med. Biol. Eng., No. 140."},{"key":"ref_4","unstructured":"Maeda, K., and Ezaki, I. Fetal cardiotachography recorded with fetal heart sound during pregnancy and labor. Proc. 7th Int. Conf. Med. Biol. Eng., No. 144."},{"key":"ref_5","first-page":"17","article-title":"Einf\u00fchrung in die Cardiotokographie. 5. Teil: Die Herzfrequenzmessung mit US = Ultraschall","volume":"74","author":"Hammacher","year":"1976","journal-title":"Die Schweizer Hebamme"},{"key":"ref_6","first-page":"1327","article-title":"Auto correlation method for fetal heart rate measurement from ultrasonic Doppler fetal signal","volume":"Vol. 3B \u201cEngineering Aspect\u201d","author":"White","year":"1977","journal-title":"Ultrasound in Medicine"},{"key":"ref_7","first-page":"99","article-title":"Survey on the perinatal variables and the incidence of cerebral palsy for 12 years before and after the application of the fetal monitoring system","volume":"42","author":"Tsuzaki","year":"1990","journal-title":"Nippon Sanka Fujinka Gakkai Zasshi"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1159\/000110181","article-title":"Cerebral palsy in Tottori, Japan. Benefits and risks of progress in perinatal medicine","volume":"4","author":"Takeshita","year":"1989","journal-title":"Neuroepidemiology"},{"key":"ref_9","first-page":"1214","article-title":"Computer-aided fetal heart rate analysis and automatic fetal-distress diagnosis during labor and pregnancy utilizing external techniques in fetal monitoring","volume":"80","author":"Maeda","year":"1980","journal-title":"MEDINFO"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1515\/jpme.1991.19.1-2.47","article-title":"System 8000: computerized antenatal FHR analysis","volume":"19","author":"Dawes","year":"1991","journal-title":"J. Perinat. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1515\/jpme.1991.19.1-2.61","article-title":"The Porto system for automated cardiotocogaphic signal analysis","volume":"19","author":"Bernardes","year":"1991","journal-title":"J. Perinat. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"S51","DOI":"10.1007\/BF02523327","article-title":"Suitability of artificial neural networks for feature extraction from cardiotocogram during labor","volume":"32","author":"Keith","year":"1994","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/S0933-3657(97)00052-3","article-title":"Neural networks for recognizing patterns in cardiotocograms","volume":"12","author":"Ulbricht","year":"1998","journal-title":"Artif. Intell. Med."},{"key":"ref_14","first-page":"3728","article-title":"Evalation of fetal heart rate baseline estimation method using testing signals based on a statistical model","volume":"1","author":"Kupka","year":"2006","journal-title":"Proc. IEEE Eng. Med. Biol. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jezewski, M., Wrobel, J., Labaj, P., Leski, J., Henzel, N., Horoba, K., and Jezewski, J. (2007). Some practical remarks on neural networks approach to fetal cardiotocograms classification. Proc. IEEE Eng. Med. Biol. Soc., 5170\u20135173.","DOI":"10.1109\/IEMBS.2007.4353506"},{"key":"ref_16","first-page":"1487","article-title":"Quantitative fetal heart rate evaluation without pattern classification: FHR score and artificial neural network analysis","volume":"Vol. 2","author":"Kurjak","year":"2006","journal-title":"Textbook of Perinatal Medicine"},{"key":"ref_17","unstructured":"Krause, W. (1981). Computerdiagnostik in der Geburtsmedizin, Friedrich-Schiller-Universit\u00e4t."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1515\/jpme.1994.22.1.39","article-title":"Differentiation between physiologic and pathologic sinusoidal FHR pattern by fetal actocardiogram","volume":"221","author":"Ito","year":"1994","journal-title":"J. Perinat. Med."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1159\/000086807","article-title":"Automatic computerized diagnosis of fetal sinusoidal heart rate","volume":"20","author":"Maeda","year":"2006","journal-title":"Fetal Diag. Ther."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Rumelhart, D.E., and McClelland, J.L. (1986). Parallel Distributed Processing, The MIT Press.","DOI":"10.7551\/mitpress\/5236.001.0001"},{"key":"ref_21","first-page":"318","article-title":"Learning Internal Representations by Error Propagation","volume":"Vol. 1","author":"Rumelhart","year":"1986","journal-title":"Parallel Distributed Processing"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning Representations by Back-Propagating Errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"key":"ref_23","first-page":"163","article-title":"Neural network computer analysis of fetal heart rate","volume":"8","author":"Maeda","year":"1998","journal-title":"J. Matern. Fetal Invest."},{"key":"ref_24","unstructured":"Maeda, K., Kimura, S., Fukui, Y., Ozawa, S., Kosaka, T., Wang, C.F.M., Tamura, M., Takata, D., Nakano, H., and Mitoma, M. (1969). Pathophysiology of Fetus, Fukuoka Printing."},{"key":"ref_25","first-page":"1623","article-title":"Automated fetal heart rate analysis and its trend gram in relation to the gas analysis and acid-base balance of umbilical arterial blood","volume":"38","author":"Irie","year":"1986","journal-title":"Nippon Sanka Fujinka Gakkai Zasshi"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1159\/000071982","article-title":"Evaluation of prolonged fetal monitoring with normal and pathologic outcome probabilities determined by artificial neural network","volume":"18","author":"Maeda","year":"2003","journal-title":"Fetal Diag. Ther."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1673","DOI":"10.1016\/S0893-6080(97)00023-3","article-title":"Global bifurcation structure of chaotic neural networks and its application to traveling salesman problems","volume":"10","author":"Tokuda","year":"1997","journal-title":"Neural Networks"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1016\/0893-6080(96)00032-9","article-title":"An adaptive structure neural networks application to EEG automatic seizure detection","volume":"9","author":"Weng","year":"1996","journal-title":"Neural Networks"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1674","DOI":"10.1016\/S0022-5347(01)67502-5","article-title":"Neural network analysis of quantitative histological factors to predict pathological stage in clinical stage I nonseminomatous testicular cancer","volume":"153","author":"Moul","year":"1995","journal-title":"J. Urol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1192\/bjp.166.1.19","article-title":"A neural model of memory impairment in diffuse cerebral atrophy","volume":"166","author":"Ruppin","year":"1995","journal-title":"Br. J. Psychiatry"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"755","DOI":"10.3171\/jns.1997.86.5.0755","article-title":"Prediction of posterior fossa tumor type in children by means of magnetic resonance image properties, spectroscopy, and neural networks","volume":"86","author":"Arle","year":"1997","journal-title":"J. Neurosurg."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1111\/j.1600-0714.1996.tb00291.x","article-title":"Performance of a computer-simulated neural network trained to categorize normal, premalignant and malignant oral smears","volume":"25","author":"Brickley","year":"1996","journal-title":"J. Oral. Pathol. Med."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1038\/eye.1994.65","article-title":"Visual field interpretation with a personal computer-aided neural network","volume":"8","author":"Mutlukan","year":"1994","journal-title":"Eye"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1097\/00000542-199212000-00005","article-title":"Intelligent alarms reduce anesthesiologist\u2019s response time to critical faults","volume":"77","author":"Westenskow","year":"1992","journal-title":"Anesthesiology"},{"key":"ref_35","first-page":"272","article-title":"Application of artificial neural network to computer-aided diagnosis of coronary artery disease in myocardial SPECT bull\u2019s eye images","volume":"33","author":"Fujita","year":"1992","journal-title":"J. Nucl. Med."},{"key":"ref_36","first-page":"615","article-title":"Analysis of the secondary structure of the human immunodeficiency virus (HIV) proteins p17, gp120 and gp41 by computer modeling based on neural network methods","volume":"3","author":"Andreassen","year":"1990","journal-title":"J. Acquir. Immune Def. Syndr."},{"key":"ref_37","first-page":"256","article-title":"Predicting the duration of the first stage of spontaneous labor using a neural network","volume":"5","author":"Samuel","year":"1996","journal-title":"J. Mat. Fet. Med."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1016\/0002-9378(92)91621-G","article-title":"The use of a neural network for the ultrasonographic estimation of fetal weight in the macrosomic fetus","volume":"166","author":"Farmer","year":"1992","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/TBME.2005.859809","article-title":"Comparison of entropy-bases regularity estimators: application to the fetal heart rate signal for the identification of fetal distress","volume":"53","author":"Ferrario","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s10916-006-9037-9","article-title":"On the creation of a new diagnostic model for fetal well-being on the base of wavelet analysis of cardiotocograms","volume":"30","author":"Cattani","year":"2006","journal-title":"J. Med. Sys."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1109\/TBME.2006.889772","article-title":"Use of sample entropy approach to study heart rate variability in obstructive sleep apnea syndrome","volume":"54","author":"Sahakian","year":"2007","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/TBME.2006.883728","article-title":"Extraction of fetal electrocardiogram using adaptive neuro-fuzzy inference systems","volume":"54","author":"Assaleh","year":"2007","journal-title":"IEEE Trans. Biomed. 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