The first step is to streamline preliminary information gathering. Instead traditionally spending up to 90% of the time asking patients questions, the preliminary questionnaires can be automated using an interactive chatbot program on a web- or mobile-based app.
In the second phase, the chatbot can gather data on voice quality and cognitive function. As a snorer himself, Dr. Liu felt hoarse after a poor night’s sleep, and he also saw many patients with persistent cough and hoarseness caused by snoring which led to the idea that voice could be as an indicator of sleep disturbance. The patient’s voice can be recorded using a cellphone app, and the AI system can determine neurocognitive function at the same time.
Voice and neurocognitive data combined with other parameters can be recorded using wearables and home-based IoT devices that gather physiological and environmental data to account for factors that affect sleep quality like physical activity, air quality, noise, light, and temperature. In the third phase, all the information is integrated and analyzed using AI tools to help create cognitive behavior therapy programs and sleep environment interventions.
In designing his model Dr. Liu is taking advantage of its access to data from over 10 000 patients in northern Taiwan. He has already successfully uncovered links between physical profiles, environmental pollution, and sleep disorders. As his AI model takes shape, a comprehensive sleep disorder prediction model is on the horizon.
Dr. Liu says that as sensing technology and data processing tools improve, doctors will be freed up to spend more time on patients, whether they have complicated clinical problems or would benefit from minor lifestyle changes. “When we developed some system or machine to take over the ‘low level’ task … we can find how to improve patients’ and peoples’ health. In 200 years of medical science, we just have the resources to focus on the severe problems.”
Besides providing patients with longitudinal follow-up, the smart devices used to monitor severe sleep apnea can also be useful for people with subclinical issues. Dr. Liu is also working with business to build a personalized care program for anyone to upload their own data for analysis by his AI model.
A large proportion of sleep disturbances can be addressed through lifestyle changes, but whether a patient’s condition can be improved by sleep hygiene or a sleep apnea ventilator, sleep data gathered in Dr. Liu’s program will be a valuable resource for research and precision treatment, and will help move sleep studies to where sleep actually happens – out of the hospital and into the bedroom.