Chair: Clete Kushida (United States)
Chair: Daewoo Kim (Republic of Korea)
Summary:
This session will feature a presentation on Asleep's sound-based sleep tracking technology, exploring its applications, limitations, and future developments. During the session, participants will discuss collaborative research, cooperation, and the potential of data-driven AI, while also exploring unexpected opportunities in the field.
Part 1. Sleep X AI Introduction
Our aim is to present evidence demonstrating the effectiveness and thorough validation of sound-based AI models for sleep monitoring.
Enhancing Sleep Medicine: Leveraging AI for Advanced Diagnosis and Treatment
Clete Kushida (United States)
12:45 - 12:55 (10 min)
Summary: "Sleep Meets AI in Medicine: Leveraging existing and untapped data, this union has the potential to advance sleep diagnosis and even improve sleep quality through innovative technologies.”
AI and Sleep: The Power of Sound-based Analysis for Accurate Sleep Insights
Daewoo Kim (Republic of Korea)
Seulki Park (Republic of Korea)
12:55 - 13:20 (25 min)
Summary: “We explain the connection between sleep and sound, showing AI-driven sleep analysis and our innovative sleep tracker, "SleepRoutine." We discuss efforts to overcome noise challenges, validate our tracker, and provide comparisons with other sleep trackers and performance metrics.”
Part 2. Collaborate and Innovate
We hope to explore potential collaborations for data-driven research and expand the application of our AI model to sleep medicine.
Integration of clinical and Airable data by AI to optimize treatment in sleep medicine
Claudia Pinter (Austria)
13:20 - 13:30 (10 min)
Summary: “Sleep analysis using AI to diagnose breathing disorders, including OSA , has promise for enhanced accessible and accuracy. In this session the current capabilities and limitation of using AI in sleep medicine will be explored, while proposing directions to further harness this technology for optimized treatment outcomes.”
Data Analysis from SleepRoutine: Exploring Korean Sleep Patterns
Ki-Young Jung (Republic of Korea)
13:30 - 13:40 (10 min)
Summary: ”We reveal the analysis of Korean users' sleep patterns using SleepRoutine data, focusing on weekday vs. weekend variations. SleepRoutine's sleep tracker allows for diverse data analysis, and we propose collaborative research opportunities.”
Collaborate and Innovate: Leveraging AI in Sleep Research and Business Ventures
Dongheon Lee (Republic of Korea)
13:40 - 14:50 (10 min)
Summary: ”This session focuses on research and business opportunities. We discuss leveraging AI for data analysis, quantifying sleep data's value, and proposing API integration in sectors like sleep tech, smart appliances, healthcare, and insurance. We also explore collaborations under the theme "Sleep and X" for enhanced user experiences and business growth.”