{"id":50797,"key":"Global_Health_Medical_Device_Compendium/Newborn_Cry-Based_Diagnosis_System","title":"Global Health Medical Device Compendium/Newborn Cry-Based Diagnosis System","latest":{"id":1267847,"timestamp":"2026-09-10T14:51:26Z"},"content_model":"wikitext","license":{"url":"https://www.appropedia.org/Appropedia:Copyrights","title":"CC-BY-SA-4.0"},"source":"{{GHMDC device data\n| health-topic = Child mortality,\n| classification = Diagnosis\n| made = No\n| replicated = No\n| manufacturer-location = Quebec, Canada\n}}\n\nNewborn cries can be influenced by the physiological and neurological state of the child. Information about the source of the newborn’s discomfort, which could be benign or indicative of a serious health problem, can be collected from the newborn’s cries. Diseases, infections, or deformities can change an infant’s cry by affecting the central nervous system, respiratory organs, or oral cavities. It has been shown that infants with particular diseases produce cries with certain consistent attributes (Alaie, 2012). Identifying health issues in infants in low-resource settings is difficult due to a lack of diagnostic equipment. It is also especially important because the infant is less likely to have regular access to medical care and screenings during childhood, so health problems are likely to go untreated for long periods of time.\n\n== Detailed description of the solution ==\n\nThe non-invasive cry diagnosis system will use computer acoustical analysis of newborn cries to detect serious medical conditions. The cries of 120 healthy and sick newborns were analyzed to identify diagnostically relevant acoustic characteristics. The next step of the development of the cry diagnosis system is to analyze a larger pool of infants in order to expand the scope of this device and the conditions it can detect. The device will also incorporate a software-based diagnostic tool that can interpret recorded cries to help neonatologists detect specific pathologies affecting newborns. This device will be especially useful in low-resource settings because it will allow healthcare workers to identify the detect health problems in newborns noninvasively immediately after birth so that treatment can be given or further investigation can be done, if necessary.\n\n== Designed by ==\n\n* Designed by: Chakib Tadj, Professor, Department of Electrical Engineering, Ecole de Technologie Superieure, Montreal, Quebec, CA\n* Manufacturer (if different):\n* Manufacturer location:\n\n== When and where it was tested/implemented ==\n\n== Funding Source ==\n\nRecipient of a Grand Challenges in Global Health grant.\n\n== References ==\n\n=== Peer-reviewed publication ===\n\nKheddache, Y. and Tadj, C. (2013) Acoustic measures of the cry characteristics of healthy newborns and newborns with pathologies. Journal of Biomedical Science and Engineering, 6, 796-804. doi: 10.4236/jbise.2013.68097.\n\nHesam Farsaie Alaie and Chakib Tadj. Cry-Based Classification of Healthy and Sick Infants Using Adapted Boosting Mixture Learning Method for Gaussian Mixture Models. Modelling and Simulation in Engineering. 2012. doi:10.1155/2012/983147\n\n=== Other internally generated reports ===\n\n=== Externally generated reports ===\n\n\"A Newborn Cry-Based Diagnosis System.\" Grand Challenges Explorations Grants. Grand Challenges in Global Health, n.d. Retrieved December 6, 2013 from [http://www.grandchallenges.org/Explorations/Pages/GrantsAwarded.aspx?Topic=Mothers%20and%20newborns&Round=all&Phase=1 here.]\n\n=== IP and copyright ===\n\n=== Approval by regulatory bodies or standards boards ===\n\n{{Page data\n| sdg = SDG03 Good health and well-being, SDG09 Industry innovation and infrastructure\n| license = CC-BY-SA-3.0\n| language = en\n}}"}