A baby in Flinders Medical Centre’s intensive care neonatal unit, one of seven infants whose vital signs were remotely monitored in the study.
University of South Australia researchers have designed a computer vision system that can automatically detect a tiny baby’s face in a hospital bed and remotely monitor its vital signs from a digital camera with the same accuracy as an electrocardiogram machine.
Using artificial intelligence-based software to detect human faces is now common with adults, but this is the first time that researchers have developed software to reliably detect a premature baby’s face and skin when covered in tubes, clothing, and undergoing phototherapy.
Engineering researchers and a neonatal critical care specialist from UniSA remotely monitored heart and respiratory rates of seven infants in the Neonatal Intensive Care Unit (NICU) at Flinders Medical Centre in Adelaide, using a digital camera.
“Babies in neonatal intensive care can be extra difficult for computers to recognise because their faces and bodies are obscured by tubes and other medical equipment,” says UniSA Professor Javaan Chahl, one of the lead researchers.
“Many premature babies are being treated with phototherapy for jaundice, so they are under bright blue lights, which also makes it challenging for computer vision systems.”
The ‘baby detector’ was developed using a dataset of videos of babies in NICU to reliably detect their skin tone and faces.
Vital sign readings matched those of an electrocardiogram (ECG) and in some cases appeared to outperform the conventional electrodes, endorsing the value of non-contact monitoring of pre-term babies in intensive care.
The study is part of an ongoing UniSA project to replace contact-based electrical sensors with non-contact video cameras, avoiding skin tearing and potential infections that adhesive pads can cause to babies’ fragile skin.
Infants were filmed with high-resolution cameras at close range and vital physiological data extracted using advanced signal processing techniques that can detect subtle colour changes from heartbeats and body movements not visible to the human eye.
UniSA neonatal critical care specialist Kim Gibson says using neural networks to detect the faces of babies is a significant breakthrough for non-contact monitoring.
“In the NICU setting it is very challenging to record clear videos of premature babies. There are many obstructions, and the lighting can also vary, so getting accurate results can be difficult. However, the detection model has performed beyond our expectations.
“Worldwide, more than 10 per cent of babies are born prematurely and due to their vulnerability, their vital signs need to be monitored continuously. Traditionally, this has been done with adhesive electrodes placed on the skin that can be problematic, and we believe non-contact monitoring is the way forward,” Gibson says.
Professor Chahl says the results are particularly relevant given the COVID-19 pandemic and need for physical distancing.
In 2020, the UniSA team developed world-first technology, now used in commercial products sold by North American company Draganfly, that measures adults’ vital signs to screen for symptoms of COVID-19.
Original Article: Baby detector software embedded in digital camera rivals ECG
More from: University of South Australia
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
Baby detector software
- Two-headed baby turtle thrives at animal refuge
A rare two-headed diamondback terrapin turtle is alive and kicking – with all six of its legs – at a wildlife centre in Massachusetts after hatching two weeks ago.
- 2-headed baby turtle thrives at Massachusetts animal refuge
A rare two-headed diamondback terrapin turtle is alive and kicking — with all six of its legs — at the Birdsey Cape Wildlife Center in Massachusetts after hatching two ...
- Patient Safety Concerns Grow Over Medical Gear Security
The expanded recall of insulin pump devices due to vulnerabilities that pose the risk of injury or death to patients and a recent malpractice lawsuit alleging that ...
- Mom blames infant daughter's death on hospital attacked by ransomware
An Alabama woman whose 9-month-old daughter died has filed a suit against the hospital where she was born claiming it did not disclose that its computer systems had been crippled by a cyberattack, ...
- Lawsuit blames baby’s death on ransomware attack at Alabama hospital
A lawsuit filed by an Alabama woman attributes her baby’s death to a ransomware attack at Springhill Medical Center, which resulted in diminished care.
Go deeper with Google Headlines on:
Baby detector software
Go deeper with Bing News on:
Computer vision system
- Computer Vision in Artificial Intelligence (AI) Market 2021 Report Forecast by Global Industry Trends, Future Growth, Regional Overview
A research assessment conducted to provide a thorough analysis of the Computer Vision in Artificial Intelligence (AI) market and various aspects of the market mainly ...
- Autonomous Machine Vision Improves Injection Molding Quality
A Bosch plant that produces plastic molded connectors for automotive manufacturers implements Inspekto’s S70 machine vision system, resulting in immediate savings and an improvement in connector ...
- Affordable 4K spatial AI computer vision kit raises over $700,000 via Kickstarter
Developers searching for an affordable 4K computer vision spatial AI kit may be interested in the affordable Oak D Lite OpenCV kit now ...
- Celona and Megh Computing Collaborate to Validate the Value of Computer Vision Applications Running Over New 5G LAN Technology
Tight integration of Celona’s 5G LAN technology with Megh Computing’s intelligent video analytics at the edge lets enterprises to easily enable a new era of innovative use casesCUPERTINO, Calif., Oct.
- Computer Vision Market to Reach $41B By End of Decade
Allied Market Research has a new report that suggests that the computer vision market will grow at a steady rate for the rest of the decade ...