000			01972caa a2200229 4500
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022			_a2456-7132
100			_aAkshay M Mendhakar
245		0	_a Infant Screening System Based on Cry Analysis
260			_c2019
270			_aAll India Institute of Speech & Hearing
300			_a1-7
490			_vVolume 6 Issue 1
520			_aAcoustical investigation of infant cries has been a clinical and research focus in the recent years. Findings of several studies reveal the importance of cry as a useful window for early detection of several diseases and communication difficulties such as hearing impairment, intellectual disabilities, cerebral palsy etc. This motivates us to use a minimal interface system that can automatically classify infant cries into normal and pathological with the help of state-of-the-art machine learning strategies. In this paper, we propose a software program for screening infants based on their cries. The proposed system is able to detect & classify infant cries into normal and pathological based on the acoustic input. To build and train the system, infant cries of normal and Low Birth Weight (LBW) newborn within 7 days of birth were considered. A pain induced cry elicited using the routine intramuscular immunization was recorded using a standard Olympus LS-100 recorder which was held about 10 centimetres away from the infant’s mouth. The acoustic correlates of these cries were used to build the software tool. Artificial Neural Network was employed to improve its functionality. Therefore, we propose a screening tool for further accessibility and large-scale implementation.
653			_aAcoustic, Analysis, Cry, Early intervention, Infant, Screening
700			_aArunraj, K
700			_aJayashree C Shanbal
700			_aSreedevi, N
773			_aInternational Annals of Science
856			_uhttps://doi.org/10.21467/ias.6.1.1-7
942			_cFJAS _yFJAS
999			_c17825 _d17825