AI, Wearables and the Future of Sleep Medicine​

Traditional sleep monitoring

Since the 1960s, Polysomnography has been used to monitor sleep through complementary sensors. These sensors allow the measurement of body positions, oxygen levels, the electrical activity of muscles, heart rate, etc. to name a few.

Ambulatory PSG is an alternative that uses a smaller number of sensors and allows at-home monitoring. It promotes monitoring of patients with sleep disorders that may not be possible to evaluate in the laboratory although it is a solution to man issues it persists to be burdensome and expensive.

Modern sleep sensing technology

EEG is used in neuropsychiatric tests. Conventional ECG is not portable hence, can be burdensome, Wireless ECGs have gained popularity in recent years. Similarly, several ECGs such as in-ear sensors have proved to be more promising. Smartwatches and mobile sensors are also used to monitor sleep, Smartphone’s microphone detects body movements, coughing etc. by processing acoustic signals. Ultrasound sensors are used for tracking body moments with 88% recall and less than 10% errors. In recent years, WIFI and Radio signals have been able to detect body movements without coming in contact with the patient, It gives accurate information on breathing activities and other body functions during sleep which can help to detect insomnia.

AI sleep modelling

AI is growing rapidly and is being used in multiple fields, use of AI in sleep science is well rounded. As it is used to mimic several cognitive functions, it is used to translate collected data to predefined knowledge. Machine learning provides a more flexible alternative method to collect data. 

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