‘AIM4SafeBaby®’ (Artificial Intelligence monitoring for Safe baby birth)
Lead Participant:
5GORECONN LIMITED
Abstract
The MBRRACE-UK report highlights 2292 stillbirths in 2020 and RCOG (Royal College of Obstetricians and Gynecologists)'s Each Baby Counts report; 2022 reiterates that, in 2018 alone, amongst 1145 babies, 11 % of babies died during labour, 75% of babies suffered from severe brain injury and whilst 14% died in 1st month of their life. The world's live birth rate is 701,277,931 per year \[1\] and 3% of these births (21,038,337 births/year) will have complicated and delayed caesarean sections. CDC (Centers for Disease Control and Prevention.) reports, in the USA, 50,000 mothers are severely injured & 700 die annually. 60% of these deaths and half the injuries could be avoided with proper care\[Vital Signs The report (CDC), May 2019\].
There is clearly a need for better monitoring of the labour data. The Healthcare Safety Investigation Branch (HSIB) recommends that the Department of Health and Social Care commission a review to improve the reliability of existing assessment tools for fetal growth and fetal heart rate to minimise the risk for babies \[Safety recommendation R/2021/148\].
The AIM4SafeBaby project addresses this need and will create an innovative clinical decision support system that converts labour data into knowledge-based guidelines for safer baby delivery. This innovative monitoring device will monitor the birth process and help clinicians, labouring women, and their birth partners choose the safest birth option and the benefits versus risks of all the available options. This will help timely and accurate management of the birth and will reduce the birth trauma to the mother and the baby.
'AIM4SafeBaby' solution offers a game-changing solution to clinicians. Currently, there is no technology or integrated solution able to offer a complete picture of the labour process and highlight the risks for taking educated decisions towards a safe and smooth birth process for both mother and baby. Existing labour monitoring devices like EFM(Electronic Foetal Monitoring) and CTG(cardiotocography) offer findings that cannot be relied upon as the sole source to make decisions in real-time during ongoing labour. Even highly trained health professionals sometimes struggle to interpret electronic monitor readings accurately and reliably. An off-site senior obstetrician may be called upon to help, often losing critical time for the baby's health. Hence there is an enormous scope to minimise human errors with our AI-based CTG monitoring and prediction tool.
\[1\]Ref: United Nations, Department of Economic and Social Affairs, Population Division, 2019
There is clearly a need for better monitoring of the labour data. The Healthcare Safety Investigation Branch (HSIB) recommends that the Department of Health and Social Care commission a review to improve the reliability of existing assessment tools for fetal growth and fetal heart rate to minimise the risk for babies \[Safety recommendation R/2021/148\].
The AIM4SafeBaby project addresses this need and will create an innovative clinical decision support system that converts labour data into knowledge-based guidelines for safer baby delivery. This innovative monitoring device will monitor the birth process and help clinicians, labouring women, and their birth partners choose the safest birth option and the benefits versus risks of all the available options. This will help timely and accurate management of the birth and will reduce the birth trauma to the mother and the baby.
'AIM4SafeBaby' solution offers a game-changing solution to clinicians. Currently, there is no technology or integrated solution able to offer a complete picture of the labour process and highlight the risks for taking educated decisions towards a safe and smooth birth process for both mother and baby. Existing labour monitoring devices like EFM(Electronic Foetal Monitoring) and CTG(cardiotocography) offer findings that cannot be relied upon as the sole source to make decisions in real-time during ongoing labour. Even highly trained health professionals sometimes struggle to interpret electronic monitor readings accurately and reliably. An off-site senior obstetrician may be called upon to help, often losing critical time for the baby's health. Hence there is an enormous scope to minimise human errors with our AI-based CTG monitoring and prediction tool.
\[1\]Ref: United Nations, Department of Economic and Social Affairs, Population Division, 2019
Lead Participant | Project Cost | Grant Offer |
---|---|---|
5GORECONN LIMITED | £365,691 | £ 255,984 |
  | ||
Participant |
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UNIVERSITY OF EAST ANGLIA | £249,779 | £ 199,823 |
UNIVERSITY OF EAST ANGLIA |
People |
ORCID iD |
Pallavi Gore (Project Manager) |