Home / Challenges / Completed Projects / 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.
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 team built several machine learning algorithms to detect Periodic Limb Movements from complex Electromyography (EMG) and I/Q radar-based time series data.
Sleepiz AG (Ltd.) is a Zürich based startup with a mission to provide patient-centric disease management through seamless integration of contactless monitoring into people’s homes.
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