Slip a soft sensor under your bedsheet to find out in the morning how your night went. Joonas Paalasmaa, doctoral candidate in computer science, has developed a device which can help poor sleepers sleep better.
A third of the population struggles at night – they have trouble falling asleep, or they wake up at night, sleep badly or experience breathing problems during sleep. Many just yawn and curse in frustration or take a sleeping pill.
Joonas Paalasmaa chose another solution. He began to develop a tool that people could use to monitor their sleep – comfortably at home, in their own beds. The monitoring data could then be used as a basis for sleep coaching. So far, this solution has produced an invention called Beddit along with a respectable amount of research data.
The measuring systems and algorithm used in the Beddit sleep monitoring device will be closely examined this week when Paalasmaa defends his computer science doctoral dissertation on sleep monitoring on 7 February.
Snoring, resting heart rate and sleep quantity
Beddit is used by slipping the soft sensor under the bedsheet in the evening. The sensor monitors breathing, movements and heart rate, and evaluates the quality and quantity of sleep based on these metrics.
“I’ve noticed that the results correlate with how you feel the following day. An upcoming examination or other cause of stress shows in the data,” boasts Paalasmaa.
Beddit displays the information it gathers through a web service or mobile device, and gives instructions on improving sleep. These hints depend on the measuring results and on the information entered into the user profile.
“Providing personalised sleep instructions is a challenge. We have to generate hundreds of tips to fit the individual needs of our users, and to make the users feel like the app is intelligent and useful,” Paalasmaa explains.
Boosted by crowd funding
In any case, the public is excited. Beddit managed to accrue nearly half a million dollars in a few months during its US-based crowd funding campaign.
Its closest competitors are intended primarily for making medical diagnoses, not for home use.
The supervisor of Paalasmaa’s dissertation was Professor Hannu Toivonen, a specialist in data mining and a world-renowned expert in computational creativity.
One of the topics of interest for Toivonen and his research group is the expression of information to different senses. Based on the Kumpula campus, the group creates machine compositions which explore the possibilities of transforming data into music. If information can be visualised, why not auditised?