Collaborative research integrates mobile sensing data to revolutionize early Alzheimer’s diagnosis.
A Groundbreaking Study in Alzheimer’s Detection
Sleep Cycle, a pioneer in sleep technology, has partnered with the University of Cambridge and University College London (UCL) to explore innovative methods for identifying Alzheimer’s disease. The collaboration focuses on leveraging mobile-based data to detect cognitive decline before dementia symptoms emerge.
Key study components include:
- Sleep and navigation patterns: Early indicators of Alzheimer’s disease.
- Mobile monitoring: Collecting real-world, at-home data for less invasive and scalable analysis.
- Machine learning: Combining sleep and navigation data to identify early cognitive changes.
The Importance of Sleep and Navigation
“Navigation ability and sleep are affected in the earliest stages of Alzheimer’s,” said Dr. Abhirup Ghosh, a lead researcher. “Traditional tests often miss these changes, but phone apps offer a scalable way to detect them in real-life settings.”
Sleep Cycle’s Role in Advancing the Study
Sleep Cycle’s app plays a critical role, providing:
- Comprehensive metrics: Monitoring sleep duration, efficiency, and snoring patterns.
- Privacy-focused solutions: Ensuring secure data collection.
- Real-world applicability: Capturing accurate in-home behaviors.
Data from Sleep Cycle’s app is combined with navigation metrics from a custom app developed by the research team. Together, these insights create a holistic picture of participant behaviors.
“This partnership supports our mission to improve health through sleep,” said Mikael Kågebäck, Sleep Cycle CTO.
Study Goals and Early Progress
The study began in August 2024, focusing on a cohort of 50–60 participants with mild cognitive impairment. Researchers are analyzing:
- Sleep patterns: Using Sleep Cycle’s app to track efficiency and disruptions.
- Navigation data: Monitoring spatial orientation as an early Alzheimer’s indicator.
- Biomarkers: Correlating amyloid and tau levels with behavioral changes.
Transforming Alzheimer’s Detection
With Alzheimer’s affecting nearly 1 in 9 Americans aged 65+, early detection is critical. This research highlights how mobile technology can enable timely intervention and expand access to care.
“This study could revolutionize early detection by offering a scalable, real-world approach,” Dr. Ghosh noted.
Follow MEDWIRE.AI for insights into health tech innovations shaping the future of Alzheimer’s care.
