A team of Finnish researchers has developed a “smart jumpsuit” that can track a baby’s movements and use this to predict its brain development.
The Motor Assessment of Infants with a Jumpsuit (MAIJU) is a wearable device equipped with movement sensors.
The researchers, who have published their findings in Communications Medicine, have used the smart jumpsuit to monitor the movements of 59 infants, all aged between five and 19 months old, during playtime.
They then used MAIJU’s sensor data, along with some recorded video, to feed a machine-learning program. This yielded an algorithm that can recognise a baby’s postures and movements with ease, and uses this to assess the baby’s neurological development.
“The development of the MAIJU wearable required a technical breakthrough in the development of machine-learning algorithms for this purpose,” says lead author Dr Manu Airaksinen, a researcher at Helsinki University Hospital, Finland.
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“This was achieved by combining a new kind of motility description with state-of-the-art deep learning solutions.”
Motor development is strongly linked to neurological development in infants, but it can be difficult to assess babies’ motor skills objectively. Plus, children are typically assessed in clinics and hospitals, where they might behave differently to their home environments.
“Our research shows that it is very possible to assess the motor development of an infant outside of a hospital or special laboratory setting,” says co-author Professor Sampsa Vanhatalo, a researcher in physiology at Helsinki University Hospital.
“A particular advantage of the MAIJU methodology is the fact that it allows us to carry out developmental assessments in the natural environment of the child, such as a home or daycare.”
Most of the infants assessed wore the jumpsuit during spontaneous play at home, while some came with their caregivers to a “home-like environment” at the hospital for logistical reasons.
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Professor Leena Haataja, a researcher in child neurology at the University of Helsinki and Helsinki University Hospital says: “Methods of this kind are urgently needed to support the research and novel therapeutic innovations of early neurological development.”
Beyond checking babies’ progress, the researchers think their algorithm and sensors could be used by other people.
“Our methods can be automatised and scaled up for very wide use,” says Vanhatalo.
“It is also possible that our technology could be adapted for developing wearable solutions to help other patient groups, such as older children or even elderly people.”