References
- Abdulaziz, Y., & Ahmad, S. (2010). An accurate infant cry classification system based on continuous Hidden Markov Model. In Information Technology (ITSim), 2010 International Symposium in (Vol. 3, pp. 1648-1652).
- ACM. (2014). ACM Digital Library. Retrieved from http://dl.acm.org/dl.cfm Amaro-Camargo, E., & Reyes-Garcia, C. A. (2007). Applying statistical vectors of acoustic characteristics for the automatic classification of infant cry. Advances in Pattern Recognition, 4681, 1078-1085.
- Arch-Tirado, E., Mandujano, M., Garcia-Torices, L., Martinez-Cruz, C. F., Reyes- García, C. A., & Taboada-Picazo, V. (2004). Cry analysis of hypoacoustic children and normal hearing children. Cirugia y Cirujanos, 72(4), 271-276.
- Aucouturier, J.-J., Nonaka, Y., Katahira, K., & Okanoya, K. (2011). Segmentation of expiratory and inspiratory sounds in baby cry audio recordings using hidden Markov models. Journal of the Acoustical Society of America, 130(5), 2969-2977.
- Barajas, S. E., & Reyes, C. A. (2005). Your fuzzy relational neural network parameters optimization with a genetic algorithm. FUZZ-IEEE 2005: Proceedings of the IEEE International Conference on Fuzzy Systems: BIGGEST LITTLE CONFERENCE IN THE WORLD, 684-689.
- Barajas-Montiel, S., & Reyes-Garcia, C. (2005). Identifying Pain and Hunger in Infant Cry with Classifiers Ensembles. In Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on (Vol. 2, pp. 770-775).
- 2012. Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on.
- Blinick, G., Tavolga, W. N., & Antopol, W. (1971). Variations in birth cries of newborn infants from narcotic-addicted and normal mothers. American Journal of Obstetrics and Gynecology, 110(7), 948-958. Boersma, P. (1993). Accurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound. In Proceedings of the Institute of Phonetic Sciences, Amsterdam (Vol. 17, pp. 97-110).
- Boersma, P. (2009). Should Jitter Be Measured by Peak Picking or by Waveform Matching? Folia Phoniatrica et Logopaedica, 61(5), 305-308.
- Boersma, P. & Weenink, D. (2013). Praat: doing phonetics by computer. Version 5.3.39.
- Boersma, P. & Weenink, D. (2013). Praat: doing phonetics by computer: Manual. Retrieved from http://www.fon.hum.uva.nl/praat/manual/Intro.html Brahnam, S., Chuang, C. F., Shih, F. Y., & Slack. (2006). Machine recognition and representation of neonatal facial displays of acute pain. Artificial Intelligence in Medicine, 36(3), 211-222.
- Branco, A., Fekete, S. M., Rugolo, L. M., & Rehder, M. I. (2007). The newborn pain cry: descriptive acoustic spectrographic analysis. International Journal of Pediatric Otorhinolaryngology, 71(4), 539-546.
- Cano, S., Suaste, I., Escobedo, D., Reyes-Garcia, C. A., & Ekkel, T. (2006). A combined classifier of cry units with new acoustic attributes. Advances in Pattern Recognition, 4225, 416-425.
- Cano-Ortiz, S. D., Reyes-Garcia, C. A., Reyes-Galaviz, O. F., Escobedo- Beceiro, D. I., & Cano-Otero, J. D. (2013). Emergence of a New Alternative on Cry Analysis: The Fuzzy Approach. 5TH LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING (CLAIB 2011): SUSTAINABLE TECHNOLOGIES FOR THE HEALTH OF ALL, PTS 1 AND 2, 33(1-2), 846-849.
- Chollet, G., Esposito, A., Faundez-Zanuy, M., & Marinaro, M. (Eds.). (2005). Berlin and Heidelberg: Springer-Verlag.
- Cohen, R., & Lavner, Y. (2012). Infant cry analysis and detection. In Electrical Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of (pp. 1-5).
- Corwin, M. J., Lester, B. M., Sepkoski, C., McLaughlin, S., Kayne, H., & Golub, H. L. (1992). Effects of in utero cocaine exposure on newborn acoustical cry characteristics. Pediatrics, 89(6 Pt 2), 1199-1203.
- DBLP. (2014). Digital Bibliography & Library Project. Retrieved from http://www.dblp.org/ Deutsche Zentralbibliothek für Medizin. (2014). MEDPILOT. Retrieved from http://www.medpilot.de/ DIMDI. (2014). DIMDI Medizinwissen. Retrieved from http://www.dimdi.de/static/de/index.html Esposito, G., Nakazawa, J., Venuti, P., & Bornstein, M. H. (2013). Componential deconstruction of infant distress vocalizations via tree-based models: A study of cry in autism spectrum disorder and typical development. Research in Developmental Disabilities, 34(9), 2717-2724.
- Etz, T., Reetz, H., & Wegener, C. (2012). A classification model for infant cries with hearing impairment and unilateral cleft lip and palate. Folia Phoniatrica et Logopaedica, 64(5), 254-261.
- Fisichelli, V. R., & Karelitz, S. (1966). Frequency spectra of the cries of normal infants and those with Down’s syndrome. Psychonomic Science, 6, 195-196.
- Fort, A., & Manfredi, C. (1998). Acoustic analysis of newborn infant cry signals. Medical Engineering & Physics, 20(6), 432-442.
- Fuller, B. F. (1991). Acoustic discrimination of three types of infant cries. Nursing Research, 40(3), 156-160.
- Galaviz, Orion Fausto Reyes, & García, Carlos Alberto Reyes (2005). Infant cry classification to identify hypo acoustics and asphyxia comparing an evolutionary-neural system with a neural network system. In: MICAI’05, Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence (pp. 949-958). Springer-Verlag.
- Garcia, J., & Reyes Garcia, C. (2003). Mel-frequency cepstrum coefficients extraction from infant cry for classification of normal and pathological cry with feed-forward neural networks. In Neural Networks, 2003. Proceedings of the International Joint Conference on (Vol. 4, pp. 3140-3145 vol. 4).
- Garcia, J. O., & Reyes Garcia, Carlos A. (2003). Medical Applications - Acoustic Features Analysis for Recognition of Normal and Hipoacustic Infant Cry Based on Neural Networks. Lecture Notes in Computer Science, 2687, 615-622.
- GBV. (2014). Online Contents - SSG Mathematik und Informatik. Retrieved from http://gso.gbv.de/DB=2.77/LNG=DU/ Goberman, A. M., & Robb, M. P. (2005). Acoustic characteristics of crying in infantile laryngomalacia. Logopedics, Phoniatrics, Vocology, 30(2), 79-84.
- Golub, H. L., & Corwin, M. J. (1982). Infant cry: a clue to diagnosis. Pediatrics, 69(2), 197-201.
- Hariharan, M., Saraswathy, J., Sindhu, R., Khairunizam, W., & Yaacob, S. (2012). Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks. Expert Systems with Applications, 39(10), 9515-9523.
- Hariharan, M., Saraswathy, J., Sindhu, R., Khairunizam, W., & Yaacob, S. (2012). Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks. Expert Systems with Applications, 39(10), 9515-9523.
- Hariharan, M., Sindhu, R., & Yaacob, S. (2012). Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network. Computer Methods and Programs in Biomedicine, 108(2), 559-569.
- Hariharan, M., Yaacob, S., & Awang, S. A. (2011). Pathological infant cry analysis using wavelet packet transform and probabilistic neural network. Expert Systems with Applications, 38(12), 15377-15382.
- Honda, K., Kitahara, K., Matsunaga, S., Yamashita, M., & Shinohara, K. (2012). Emotion classification of infant cries with consideration for local and global features. In Signal Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific (pp. 1-4).
- IBM. (2013). SPSS Modeler. Version 15.
- IBM. (2013). SPSS Statistics.
- IEEE. (2014). IEEE Xplore Digital Library. Retrieved from http://ieeexplore.ieee.org/ Karelitz, S., & Fisichelli, V. R. (1962). The cry thresholds of normal infants and those with brain damage. Disability and Rehabilitation, 61(5), 679-684.
- Kheddache, Y., & Tadj, C. (2012). Newborn’s pathological cry identification system. In Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on (pp. 1024-1029).
- Kia, M., Kia, S., Davoudi, N., & Biniazan, R. (2012). A detection system of infant cry using fuzzy classification including dialing alarm calls function. In Innovative Computing Technology (INTECH), 2012 Second International Conference on (pp. 224-229).
- Lederman, D., Cohen, A., Zmora, E., Wermke, K., Hauschildt, S., & Stellzig- Eisenhauer, A. (2002). On the use of hidden Markov models in infants’ cry classification. 22ND CONVENTION OF ELECTRICAL AND ELECTRONICS ENGINEERS IN ISRAEL, PROCEEDINGS, 350-352.
- Lederman, D., Zmora, E., Hauschildt, S., Stellzig‐Eisenhauer, A., & Wermke, K. (2008). Classification of cries of infants with cleft-palate using parallel hidden Markov models. Medical & Biological Engineering & Computing, 46(10), 965-975.
- Lester, B. M., Tronick, E. Z., LaGasse, L. L., Seifer, R., Bauer, C. R., Shankaran, S., . . . Maza, P. L. (2002). The maternal lifestyle study: effects of substance exposure during pregnancy on neurodevelopmental outcome in 1-monthold infants. Pediatrics, 110(6), 1182-1192.
- Lind, J., Vuorenkoski, V., & Rosberg, G. (1970). Spectrographic analysis of vocal response to pain stimuli in infants with Down’s syndrome. Developmental Medicine and Child Neurology, 12(4), 478-486.
- Lind, J., Wasz-Höckert, O., Rosberg, G., Theorell, K., Valanne, E. H., Partanen, T. J., & Vuorenkoski, V. (1967). Sound spectrography in pediatric diagnosis. Acta Paediatrica Scandinavica, 177(Suppl. s177), 113-119.
- Lu Guanming, Li Xiaonan, & Li Haibo. (2008). Research on Recognition for Facial Expression of Pain in Neonates. Acta Optica Sinica, 28(11), 2109-2114.
- Michelsson, K., Eklund, K., Leppänen, P., & Lyytinen, H. (2002). Cry Characteristics of 172 Healthy 1- to 7-Day-Old Infants. Folia Phoniatrica et Logopaedica, 54(4), 190-200.
- Michelsson, K., Sirvio, P., & Wasz-Hockert, O. (1977). Sound spectrographic cry analysis of infants with bacterial meningitis. Developmental Medicine and Child Neurology, 19(3), 309-315.
- Mohd Ali, M., Mansor, W., Lee, Y. K., & Zabidi, A. (2012). Asphyxiated infant cry classification using Simulink model. In Signal Processing and its Applications (CSPA), 2012 IEEE 8th International Colloquium on (pp. 491-494).
- Möller, S., & Schönweiler, R. (1999). Analysis of infant cries for the early detection of hearing impairment. Speech Communication, 28(3), 175-193.
- Nugent, J. K., Lester, B. M., Greene, S. M., Wieczorek-Deering, D., & O’Mahony, P. (1996). The effects of maternal alcohol consumption and cigarette smoking during pregnancy on acoustic cry analysis. Child Development, 67(4), 1806-1815.
- Orozco, J., & Reyes-Garcia, C. A. (2003). Implementation and analysis of training algorithms for the classification of infant cry with feed-forward neural networks. 2003 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING, PROCEEDINGS: FROM CLASSICAL MEASUREMENT TO COMPUTING WITH PERCEPTIONS, 271-276.
- Orozco-Garcia, J., Reyes-Garcia, C. A., & Reyes-Garcia, C. (2003). A Study on the Recognition of Patterns of Infant Cry for the Identification of Deafness in Just Born Babies with Neural Networks. Lecture Notes in Computer Science, 2905, 342-349.
- Ortiz, S. D., Beceiro, D. I., & Ekkel, T. (2004). A radial basis function network oriented for infant cry classification. Advances in Pattern Recognition, 3287, 374-380.
- Ortiz, Sergio D. Cano, Escobedo Beceiro, Daniel L., Ekkel, T., & Ortiz, S. D. (2004). A Radial Basis Function Network Oriented for Infant Cry Classification. Lecture Notes in Computer Science, 3287, 374-380.
- Own, H. S., & Abraham, A. (2012). A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice. Appl. Soft Comput., 12(3), 999-1005.
- Petroni, M., Malowany, M., Johnston, C. C., & Stevens, B. J. (1995). A comparison of neural network architectures for the classification of three types of infant cry vocalizations. In Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference (Vol. 1, pp. 821-822 vol. 1).
- Petroni, M., Malowany, M., Johnston, C. C., & Stevens, B. J. (1995). On the use of artificial neural networks (ANNs) for the classification of three types of infant cries. In Communications, Computers, and Signal Processing, 1995. Proceedings., IEEE Pacific Rim Conference on (pp. 501-504).
- Poel, M., & Ekkel, T. (2006). Analyzing infant cries using a committee of neural networks in order to detect hypoxia related disorder. International Journal on Artificial Intelligence Tools, 15(3), 397-410.
- Press, W. H., Flannery, B. P., Teukolsky, S. A., & Vetterling, W. T. (2002). Numerical recipes in C: The art of scientific computing (2nd ed.). Cambridge: Cambridge University Press.
- Rapid-I. (2014). RapidMiner Studio 6. Retrieved from http://rapidminer.com/products-2/rapidminer-studio/ Rautava, L., Lempinen, A., Ojala, S., Parkkola, R., Rikalainen, H., Lapinleimu, H., . . . Lehtonen, L. (2007). Acoustic quality of cry in very-low-birth-weight infants at the age of 1 1/2 years. Early Human Development, 83(1), 5-12.
- Reyes Galaviz, Orion Fausto, & Reyes Garcia, Carlos Alberto. (2004). Intelligent Interfaces and Speech Processing - Infant Cry Classification to Identify Hypoacoustics and Asphyxia with Neural Networks. Lecture Notes in Computer Science, 2972, 69-78.
- Reyes Galaviz, Orion Fausto, & Reyes Garcia, Carlos Alberto. (2005). Bioinformatics and Medical Applications - Infant Cry Classification to Identify Hypo Acoustics and Asphyxia Comparing an Evolutionary-Neural System with a Neural Network System. Lecture Notes in Computer Science, 3789, 949-958.
- Reyes-Galaviz, O. F., Arch Tirado, E., Reyes-Garcia, C. A., Reyes-Galaviz, O., & Reyes-Garcia, C. (2004). Elderly and Disabled People: Therapy and Care - Classification of Infant Crying to Identify Pathologies in Recently Born Babies with ANFIS. Lecture Notes in Computer Science, 3118, 408-415.
- Reyes-Galaviz, O., Cano-Ortiz, S., & Reyes-Garcia, C. (2008). Validation of the Cry Unit as Primary Element for Cry Analysis Using an Evolutionary-Neural Approach. In Computer Science, 2008. ENC ’08. Mexican International Conference on (pp. 261-267).
- Reyes-Galaviz, O. F., Verduzco, A., Arch-Tirado, E., & Reyes-García, C. A. (2005). Analysis of an infant cry recognizer for the early identification of pathologies: Nonlinear Speech Modeling and Applications. In G. Chollet, A. Esposito, M. Faundez-Zanuy, & M. Marinaro (Eds.) (pp. 404-409). Berlin and Heidelberg: Springer-Verlag.
- Reyes-Garcia, C. A., Reyes-Galaviz, O. F., Cano-Ortiz, S. D., Escobedo- Becerro, D. I., Zatarain, R., & Barron-Estrada, L. (2010). Soft Computing Approaches to the Problem of Infant Cry Classification with Diagnostic Purposes. Soft Computing for Recognition Based on Biometrics, 312, 3-18.
- Robb, M. P., Crowell, D. H., & Dunn-Rankin, P. (2007). Cry analysis in infants resuscitated for apnea of infancy. International Journal of Pediatric Otorhinolaryngology, 71(7), 1117-1123.
- Rosales-Pérez, A., Reyes-García, C. A., & Gómez-Gil, P. (2011). Genetic fuzzy relational neural network for infant cry classification. In : MCPR’11, Proceedings of the Third Mexican Conference on Pattern Recognition (pp. 288-296). Springer-Verlag.
- Sahak, R., Lee, Y., Mansor, W., Yassin, A. I. M., & Zabidi, A. (2010). Optimized Support Vector Machine for classifying infant cries with asphyxia using Orthogonal Least Square. In Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on (pp. 692-696).
- Sahak, R., Lee, Y., Mansor, W., Zabidi, A., & Yassin, A. I. M. (2011). Detection of asphyxia from infant cry by linear kernel support vector machine enhanced with features from orthogonal least square. In Computer Applications and Industrial Electronics (ICCAIE), 2011 IEEE International Conference on (pp. 341-345).
- Sahak, R., Mansor, W., Lee, Y. K., Yassin, A. I. M., & Zabidi, A. (2010). Performance of Combined Support Vector Machine and Principal Component Analysis in recognizing infant cry with asphyxia. In 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 6292-6295). IEEE.
- Sahak, R., Mansor, W., Khuan, L., Zabidi, A., & Yassin, A. I. M. (2012). Detection of asphyxia from infant cry using support vector machine and multilayer perceptron integrated with Orthogonal Least Square. In Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on (pp. 906-909).
- Santiago-Sanchez, K., Reyes-Garcia, C. A., & Gomez-Gil, P. (2009). Type-2 Fuzzy Sets Applied to Pattern Matching for the Classification of Cries of Infants under Neurological Risk. Advances in Pattern Recognition, 5754, 201-210.
- Saraswathy, J., Hariharan, M., Vijean, V., Yaacob, S., & Khairunizam, W. (2012). Performance comparison of Daubechies wavelet family in infant cry classification. In Signal Processing and its Applications (CSPA), 2012 IEEE 8th International Colloquium on (pp. 451-455).
- Schonweiler, R., Kaese, S., Moller, S., Rinscheid, A., & Ptok, M. (1996). Neuronal networks and self-organizing maps: New computer techniques in the acoustic evaluation of the infant cry. International Journal of Pediatric Otorhinolaryngology, 38(1), 1-11.
- Schönweiler, R., Kaese, S., Möller, S., Rinscheid, A., & Ptok, M. (1996). Neuronal networks and self-organizing maps: new computer techniques in the acoustic evaluation of the infant cry. International Journal of Pediatric Otorhinolaryngology, 38(1), 1-11.
- Sheinkopf, S. J., Iverson, J. M., Rinaldi, M. L., & Lester, B. M. (2012). Atypical cry acoustics in 6-month-old infants at risk for autism spectrum disorder. Autism Research, 5(5), 331-339.
- Singh, A. K., Mukhopadhyay, J., & Rao, K. (2013). Classification of infant cries using epoch and spectral features. In Communications (NCC), 2013 National Conference on (pp. 1-5).
- Sirviö, P., & Michelsson, K. (1976). Sound-spectrographic cry analysis of normal and abnormal newborn infants: A review and a recommendation for standardization of the cry characteristics. Folia Phoniatrica, 28(3), 161-173.
- Suaste-Rivas, I., Diaz-Méndez, A., Reyes-Garcia, C. A., Reyes-Galaviz, O. F., Reyes-Garcia, C., & Reyes-Galaviz, O. (2006). IV Dialogue - Hybrid Neural Network Design and Implementation on FPGA for Infant Cry Recognition. Lecture Notes in Computer Science, 4188, 703-710.
- Suaste-Rivas, I., Reyes-Galaviz, O. F., Diaz-Mendez, A., & Reyes-Garcia, C. A. (2004). A fuzzy relational neural network for pattern classification. Advances in Pattern Recognition, 3287, 358-365.
- Suaste-Rivas, I., Reyes-Galviz, O. F., Diaz-Mendez, A., & Reyes-Garcia, C. A. (2004). Implementation of a linguistic fuzzy relational neural network for detecting pathologies by infant cry recognition. Advances in Pattern Recognition, 3315, 953-962.
- The R Foundation for Statistical Computing. (2014). The R Project for Statistical Computing. Retrieved from http://www.r-project.org/
- Thoden, C. J., & Michelsson, K. (1979). Sound spectrographic cry analysis in Krabbe’s Disease. Developmental Medicine and Child Neurology, 21(3), 400-401.
- Thomson Reuters. (2014). Web of Science. Retrieved from http://www.isiknowledge.com/WOS
- Várallyay, György Jr. (2007). The melody of crying. International Journal of Pediatric Otorhinolaryngology, 71(11), 1699-1708.
- Verduzco-Mendoza, A., Arch-Tirado, E., Reyes-Garcia, C. A., Leybon-Ibarra, J., & Licona-Bonilla, J. (2012). Spectrographic cry analysis in newborns with profound hearing loss and perinatal high-risk newborns. Cirugia y Cirujanos, 80(1), 3-10.
- Vuorenkoski, V., Lind, J., & Partanen, T. J. (1966). Spectrographic analysis of cries from children with maladie du cri du chat. Annales Paediatriae Fenniae, 12(3), 174-180.
- Wasz-Höckert, O., Lind, J., Vuorenkoski, V., Partanen, T. J., & Valanne, E. H. (1968). The infant cry: A spectrographic and auditory analysis (1st ed.). Clinics in developmental medicine: Vol. 29: Cambridge University Press.
- Zabidi, A., Khuan, L. Y., Mansor, W., Yassin, I. M., & Sahak, R. (2010). Classification of Infant Cries with Asphyxia Using Multilayer Perceptron Neural Network. 2010 SECOND INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND APPLICATIONS: ICCEA 2010, PROCEEDINGS, VOL. 1, 204-208.
- Zabidi, A., Khuan, L., Mansor, W., Yassin, I. M., & Sahak, R. (2011). Binary particle swarm optimization for feature selection in detection of infants with hypothyroidism. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE (pp. 2772-2775).
- Zabidi, A., Mansor, W., Lee Yoot Khuan, Yassin, I., & Sahak, R. (2010). Discrete Mutative Particle Swarm Optimisation of MFCC computation for classifying hypothyroidal infant cry. In Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on (pp. 588-592).
- Zabidi, A., Mansor, W., Yoot Khuan Lee, Yassin, I., & Sahak, R. (2011). Binary Particle Swarm Optimization for selection of features in the recognition of infants cries with asphyxia. In Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on (pp. 272-276).
- Zabidi, A., Mansor, W., Lee Yoot Khuan, Yassin, I., & Sahak, R. (2011). Threedimensional particle swam optimisation of Mel Frequency Cepstrum Coefficient computation and Multilayer Perceptron neural network for classifying asphyxiated infant cry. In Computer Applications and Industrial Electronics (ICCAIE), 2011 IEEE International Conference on (pp. 290-293).