Sleep Pose Estimation to Improve Sleep Apnea Condition
Globally, more than 1 billion people suffer from sleep apnea which makes the disease a global challenge. In this high-impact 8-week challenge, 50 AI engineers developed an AI algorithm for sleep pose estimation.
The problem
Sleep apnea is a disorder characterized by repeated interruptions in breathing during sleep. The most common cause of these pauses in respiration is the relaxation of throat muscles, provoking a blockage of the airways (Obstructive Sleep Apnea; OSA). Sleep position has been shown to influence the frequency and severity of OSA [1], and treatment strategies exist specializing in patients with positional sleep apnea.
Sleepiz AG has developed a contactless medical device to monitor a person’s sleep throughout the night. The sensing technology, based on continuous wave radar, measures the person’s movements with sub-millimeter resolution.
The project outcomes
The team built several machine learning algorithms to detect Periodic Limb Movements from complex Electromyography (EMG) and I/Q radar-based time series data.
First Omdena Project?
Join the Omdena community to make a real-world impact and develop your career
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Your benefits
Address a significant real-world problem with your skills
Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)
Access paid projects, speaking gigs, and writing opportunities
Requirements
Good English
A very good grasp in computer science and/or mathematics
Student, (aspiring) data scientist, (senior) ML engineer, data engineer, or domain expert (no need for AI expertise)
Programming experience with Python
Understanding of Data Analysis and Machine Learning.
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