Fullpower®-AI Launches Sleeptracker-AI®, Empowering Healthcare with the World's Largest Sleep Dataset

SANTA CRUZ, Calif., May 29, 2024 /PRNewswire/ -- Fullpower^®-AI, a leader in sleep technology and wellness solutions, is proud to announce the launch of the Sleeptracker.ai platform with the World's Largest Sleep Dataset.

"At Fullpower^®-AI, we are dedicated to advancing sleep science through innovative technology and comprehensive data. The launch of our Sleeptracker.ai platform, equipped with the industry's most extensive dataset, marks a significant milestone in our mission to improve health worldwide. We are excited to see the profound impact this platform will have on individual well-being and the broader field of clinical research," said Philippe Kahn, CEO of Fullpower^®-AI.

The Sleeptracker-AI^® real-time platform, with over 250 million nights of high-fidelity sleep data recorded, can be a very valuable complement for healthcare systems focused on development and monitoring for several reasons:

1. Massive dataset: With such a vast amount of sleep data collected over millions of nights and five years, developers and practitioners can access an unprecedented dataset for studying sleep patterns and disorders and their impact on health outcomes. This large-scale continually growing dataset can provide insights that may not be possible with smaller datasets or clinical studies alone.
   
   
2. Real-world data: The data collected by Sleeptracker-AI^® comes from real-world settings, capturing the natural sleep patterns and behaviors of individuals in their home environments with 5 years of longitudinal data, including the correlations between two sleepers in the same bed. This real-world dataset can be more representative of the general population compared to controlled clinical studies, allowing for more generalizable findings.
   
   
3. Continuous monitoring: The Sleeptracker-AI^® platform enables real-time continuous monitoring of sleep, respiration, heart rate, and other vital signs throughout the night. This longitudinal data can help researchers understand sleep dynamics over time and identify patterns or changes associated with various health conditions or interventions.
   
   
4. Noninvasive and contactless: The Sleeptracker-AI^® system is noninvasive and contactless, continuing to monitor without needing anything after initial setup. This can facilitate long-term data collection and improve participant compliance, providing more comprehensive and accurate data.
   
   
5. Integration with healthcare systems via Real-time API: The Sleeptracker-AI^® platform and its real-time API integrate with existing healthcare systems, allowing researchers to correlate sleep data with electronic health records, clinical assessments, and other relevant data sources. This integration can enable more comprehensive analysis and facilitate exploring relationships between sleep, health conditions, and treatment outcomes.
   
   
6. Scalability and accessibility: With a cloud-based infrastructure, the Sleeptracker-AI^® platform can scale to accommodate large-scale research projects and provide secure, remote access to data for researchers across different locations. This accessibility can foster collaboration and accelerate the pace of sleep research.
   
   
7. Validation and accuracy: The accuracy of the Sleeptracker-AI^® system has been validated in collaboration with Stanford Sleep Medicine, ensuring that the data collected is reliable and comparable to gold-standard polysomnography measurements. This validation enhances the credibility of research findings based on the platform's data.
   
   
8. Synthetic Data Generation: The Sleeptracker-AI^® platform and large data set allow Fullpower^®-AI to generate synthetic data as a digital twin for clinical trials, thereby improving outcomes, speeding up, and reducing the cost of clinical trials.

Summary: By leveraging the vast, high-fidelity, and real-world sleep data provided by the Sleeptracker-AI^® platform, healthcare systems can gain valuable insights into sleep patterns and disorders and their relationships with various health conditions. This data can inform clinical practice, treatment strategies, and public health initiatives, ultimately improving patient outcomes and population health management.

For more information contact [email protected]

SOURCE Fullpower