Wearable technology is finding its way into all nooks and crannies of life from fitness to pets. Now a spin-off from MIT has developed technology that can help parents keep track of their child’s vital signs and alert them if anything is amiss.
The start-up called Rest Devices has developed the connected baby-grow Mimo, which captures respiration data, sleeping position, activity level, and body temperature. It takes the traditional baby-monitor which only transmits the sound of a baby crying downstairs to a completely new level. Welcome to Nursery 2.0!
embedded in clothes
Machine-washable sensors are embedded directly in the baby-grow – or kimono – which measure the baby’s respiration. They do this by calculating the contractions and expansions of the baby’s chest as it breathes. The kimono has a slot on it that takes a module called a “turtle”, which captures the respiration data along with information on sleeping position, activity level and body position.
All of this data is beamed using Bluetooth to a base station called a “lilypad”. This also acts as the charging station for the turtle and incorporates a microphone to pick up any sound in the room. The lilypad takes all of this data and sends it in real-time to a web and mobile app that parents can monitor.
The company initially developed its respiration technology to help diagnose sleep apnea at home, because people normally have to go into a sleep lab to see if they suffer from the condition. As the company refined its early prototypes, it discovered that there was a massive latent demand for similar technology from parents.
peace of mind
“The aim is to provide peace of mind,” says Rest Devices co-founder Carson Darling. “Parents have a lot to worry about, and anything we can do to help mitigate that concern is the target.” In addition to peace of mind, collecting all this data allows parents to view trends over time, such as how sleep patterns are developing.
To improve accuracy in detecting changes in breathing and movement, the company refined its technology and algorithms over several years. “With greater accuracy, we avoid causing extra worry with false alarms,” Darling says. It achieved this by testing the solution with data from children to detect trends, errors and patterns.
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