Market Context — Why This Technology, Why Now

The global shift towards preventative health and personalized medicine is fueling unprecedented growth in the sleep technology market, projected to reach ~$45B–$50B globally by 2027 (AI est.). Regulatory bodies are increasingly emphasizing data-driven health outcomes, while competitive pressures demand innovative, user-friendly solutions. This technology's non-invasive, high-accuracy approach aligns perfectly with these trends, offering a critical advantage for companies seeking to capture market share in digital therapeutics, remote patient monitoring, and consumer wellness.

Key Competitive Advantages
01

Integrates respiratory rate variability and heart rate data to estimate NREM and REM sleep stages with higher accuracy than conventional methods.

02

Utilizes respiratory, heart rate, and body movement data obtainable from wearable devices, significantly reducing user burden and promoting daily use.

03

Overcame nine prior art rejections to achieve registration, indicating strong validity and a high competitive advantage.

Market Opportunity
Medical & Healthcare
$1B–$1.5B annually (AI est.)
Expanding demand for sleep data utilization in sleep disorder screening, telemedicine, and chronic disease management.
Digital health platform providers Telemedicine solution developers Medical device manufacturers for diagnostics Healthcare AI analytics firms
Consumer Wellness
$0.5B–$1B annually (AI est.)
Increasing consumer interest in daily health management through non-invasive devices like smartwatches and smart rings.
Wearable technology companies Smart home device manufacturers Fitness and wellness app developers Consumer electronics brands
Corporate Health Management
$300M–$350M annually (AI est.)
Growing trend among companies to implement sleep improvement programs to boost employee productivity and address mental health concerns.
Corporate wellness program providers HR technology solution developers Occupational health service companies Employee benefits platforms
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent successfully overcame nine prior art rejections, demonstrating strong validity and robust defense against competitive challenges. The six claims comprehensively protect the technical features of NREM sleep determination using respiratory data variability and REM sleep determination combined with heart rate data, providing a solid foundation for licensees.

Competitive White Space

This patent primarily covers the algorithm for sleep stage determination from basic physiological data. White space exists in developing integrated hardware solutions, advanced predictive analytics for sleep disorder onset, or therapeutic interventions based on these insights, allowing for complementary IP development.

Economic Impact
~$150K/year estimated diagnostic and analysis cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Estimates expert analysis labor for polysomnography (PSG) in medical and research institutions. Assuming 20,000 analyses per year at 1 hour/case and a labor cost of ~$33/hour (AI est.), this technology could reduce analysis effort by 25%, leading to an annual cost reduction of ~$150K (AI est.).

Speed to Market
5× faster than in-house development
This technology's core sleep stage determination algorithm is established and patented. It leverages existing respiratory, heart rate, and body movement data from current wearable devices and smart sensors, eliminating the need for new hardware development. This significantly shortens proof-of-concept (PoC) and basic research phases, enabling rapid market entry through software integration into existing systems and services.
Competitive Positioning

X: Sleep Stage Determination Accuracy
Y: User Convenience

Business Models & Applications
☁️ Sleep Analysis SaaS Provision
Offer subscription services for individuals and businesses, providing detailed sleep reports and improvement advice by analyzing acquired sleep data on a cloud platform.
💡 Licensing to Device Manufacturers
Provide this technology's algorithm to hardware manufacturers of smartwatches, smart rings, and non-contact sensors to enhance product value.
🌐 Telemedicine & Monitoring System Integration
Integrate this technology into remote monitoring systems offered by medical institutions and care facilities to continuously track the sleep status of patients and the elderly.
Adjacent Application Opportunities
👶 Infant & Child Care
Infant Sleep Monitoring
Estimate sleep stages from infant breathing patterns to help reduce SIDS risk and support parents in understanding their child's sleep rhythms. Combining with non-contact sensors enables safe, non-intrusive monitoring, potentially reducing false alarms by ~30%.
🏋️ Sports & Fitness
Athlete Recovery Analysis
Analyze athlete sleep data in detail to optimize training load and recovery balance. Visualize fatigue levels and condition to support personalized coaching services for performance enhancement and injury prevention, potentially improving recovery efficiency by 15-20%.
🚗 Transportation & Logistics
Driver Fatigue Detection System
Analyze sleep patterns during driver breaks to estimate alertness and fatigue accumulation. Integrate into vehicles as a warning system to reduce drowsy driving risks and suggest optimal break timings, potentially cutting fatigue-related incidents by ~25%.
Integration Roadmap — Estimated 12-Month Deployment
Technology Evaluation & Requirements Definition
Duration: 3 months
Evaluate the technology's compatibility with existing systems and define functional/performance requirements for the adopting company. Develop a PoC plan.
Prototype Development & Validation
Duration: 6 months
Adjust the algorithm using existing or simulated data, then implement and conduct validation experiments for the prototype system.
Production System Integration & Deployment
Duration: 3 months
Based on prototype validation results, integrate the system into the production environment, establish operational frameworks, and deploy to users.
Technical Feasibility
This technology is an algorithm patent utilizing generic physiological data: respiratory, heart rate, and body movement data. These are easily obtainable from existing wearable devices and non-contact sensors, eliminating the need for new dedicated hardware development. Integration as a software module into existing data collection infrastructure and applications is technically feasible, requiring no large-scale capital investment and enabling rapid system integration.
Success Scenario
Implementing this technology could enable companies to offer more detailed and highly accurate sleep stage analysis services using respiratory and heart rate data from existing healthcare devices. This could enhance customer satisfaction with sleep quality, differentiate from competitors, and potentially reduce service delivery costs by approximately 25% annually by cutting manual analysis effort from specialists.
Patent Record
APPLICATION NO.
特願2020-019990
REGISTRATION NO.
6925057
FILING DATE
2020/02/07
GRANT DATE
2021/08/05
EXPIRATION DATE
2040/02/07
PATENT HOLDER
国立大学法人電気通信大学
Examination History
2020年02月07日
出願審査請求書
2021年01月19日
拒絶理由通知書
2021年05月20日
手続補正書（自発・内容）
2021年05月20日
意見書
2021年07月13日
特許査定