Nearly 20 million USD per year is invested to operationalize 1151 Nutrition Rehabilitation Centers (NRCs) under National Health Mission to treat children with Severe Acute Malnutrition (SAM). Inefficiency in detection of SAM, and poor referral and lack of tracking system leads to underutilization of services. A mobile application that will facilitate and track referrals of children with SAM to NRCs and provide real-time bed availability status is required.
Fetal distress before and during childbirth indicating that the fetus has been receiving inadequate oxygen. Cardiotocography monitors two vital parameters, i.e Fetal heart rate (FHR) and uterine contractions (UC). These time series data and can be used to detect fetal distress.
Goal: a system that takes these two time series data as inputs and classifies them as "Distress" and "Normal" Source data: https://physionet.org/physiobank/database/ctu-uhb-ctgdb/
Methods of processing could include Support Vector Machines/ Principal Component Analysis or any other method of choice that discriminates the best.
Babies born very premature or those with cerebral palsy often have additional needs, for example, a gastric tube. Parents and family members are generally unfamiliar and need a lot of help and assistance. Information about usage and ongoing care is not readily available. There is a need for helping parents navigate the maze of information. Goal: An multilingual educational app (android/iOS) with editable content for parents of children with long-term disability.
Diagnosing neonatal and pediatric skin conditions does not require face-to-face communication and can be done remotely. There is a need for an App based system which receives images from a phone, allows the "physician" to 1) receive an image 2) tag the diagnosis, 3) automatically store the image for research use and 3) respond to the sender. There is no need to make an automated diagnosis.
Problem Statement Type
5th November , 2018
5th November , 2018
Healthcare & Biomedical Devices
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