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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19445
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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Published Paper Details
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| Paper Title: | A Survey on Infant Cry Classification and Pain level Prediction |
| Authors Name: | Harshitha P , Ananth S , Akshay S , Namratha U K , Ankith Kumar M S |
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IJRTI_188901
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| Published Paper Id: | IJRTI2401058 |
| Published In: | Volume 9 Issue 1, January-2024 |
| DOI: | |
| Abstract: | This project addresses the critical challenges in infant care by introducing a comprehensive framework for "Infant Cry Classification and Pain Level Detection." Leveraging advanced machine learning techniques, including Support Vector Machines (SVM), k-Nearest Neighbors (KNN), and deep learning architectures, the project aims to revolutionize the understanding of infant cries. The methodology encompasses a series of preprocessing steps to extract meaningful features from cry signals. With a focus on predicting four distinct levels of pain and classifying cries into six types, the proposed system incorporates SVM and KNN for cry classification and deep learning architectures for pain level prediction. This multifaceted approach enables a nuanced analysis of infant distress signals, providing a more accurate and granular understanding of the baby's needs. The innovation lies in the real-world applicability of the system, enabling the monitoring of infants in real-time. By swiftly identifying the reason behind a baby's cry and predicting the corresponding pain level, caregivers can respond promptly and accurately, facilitating faster and more targeted care. This project thus marks a significant advancement in infant healthcare, offering a practical and efficient solution for attending to the needs of infants based on the nuances of their cries. |
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| Cite Article: | "A Survey on Infant Cry Classification and Pain level Prediction", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 1, page no.343 - 347, January-2024, Available :http://www.ijrti.org/papers/IJRTI2401058.pdf |
| Downloads: | 000205096 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2401058
Registration ID:188901
Published In: Volume 9 Issue 1, January-2024
DOI (Digital Object Identifier):
Page No: 343 - 347 Country: Bengaluru, Karnataka, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2401058 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2401058 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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