Global AI in Detecting Sleep Disorders Market - 2025-2033

The global AI in detecting sleep disorders market reached US$ 486.22 million in 2024 and is expected to reach US$ 983.26 million by 2033, growing at a CAGR of 8.2% during the forecast period 2025-2033.

AI in detecting sleep disorders refers to the use of artificial intelligence (AI) technologies, such as machine learning (ML), deep learning (DL) and data analytics, to monitor, diagnose and treat various sleep disorders. These technologies help in the automated analysis of large volumes of sleep-related data collected through wearables, sensors, medical devices or environmental factors, providing accurate and timely insights for healthcare professionals and individuals alike. AI systems can monitor sleep patterns through wearables, apps or non-contact sensors, offering a non-invasive way to track sleep health.

Market Dynamics: Drivers & Restraints

Shift Towards Home-Based Sleep Monitoring

The shift towards home-based sleep monitoring is significantly driving the growth of the AI in detecting sleep disorders market and is expected to drive the market over the forecast period. This transition from traditional in-lab sleep studies to more accessible, non-invasive, and AI-powered home monitoring solutions has paved the way for massive market growth. Home-based sleep monitoring allows individuals to track and diagnose sleep disorders without the need for a hospital visit or overnight stay. This is particularly appealing for people who find traditional sleep studies cumbersome, expensive or inconvenient.

For instance, in September 2023, Honeynaps announced that its SOMNUM artificial intelligence (AI) sleep disease analysis algorithm received FDA approval. The software leverages deep learning-based AI to perform real-time analysis of vast volumes of biosignals. SOMNUM is software intended to aid in the diagnosis of sleep and respiratory-related sleep disorders. It analyses previously recorded physiological data obtained during sleep studies. The software automates recognition of sleep stage, respiratory, arousal and leg movement events.

The shift towards home-based sleep monitoring is a key driver for the growth of the AI in detecting sleep disorders market. With a focus on convenience, affordability and continuous monitoring, consumers are embracing AI-powered devices that allow for real-time data tracking, early detection and remote consultations. This transformation is leading to faster market adoption and driving future growth, as evidenced by increasing sales of wearables and home devices and the growing telemedicine market.

Limited Awareness and Adoption in Developing Regions

The limited awareness and adoption in developing regions is a significant barrier to the growth of AI in detecting sleep disorders market. Despite the widespread availability of advanced AI tools and technologies in developed countries, developing regions face several challenges that hinder the adoption of these solutions. These challenges include a lack of education about sleep health, limited access to healthcare infrastructure and financial constraints.

In many developing regions, sleep disorders are still not widely recognized or understood as serious health conditions. This results in limited demand for sleep disorder detection tools, particularly AI-based solutions, as individuals may not be aware of their own sleep issues or the importance of early diagnosis. For instance, in regions like Sub-Saharan Africa and Southeast Asia, many people still consider sleep disorders as a natural consequence of lifestyle or aging, rather than a health condition that requires medical intervention.

Segment Analysis

The global AI in detecting sleep disorders market is segmented based on device type, technology, application, end-user and region.

Application:

The insomnia from application segment is expected to dominate the AI in detecting sleep disorders market with the highest market share

Many people with insomnia seek non-drug-based treatments due to concerns about the side effects of sleeping pills. AI-driven solutions like Cognitive Behavioral Therapy for Insomnia (CBT-I), which has proven highly effective, are gaining popularity. These treatments, when supported by AI, provide personalized, scalable and easily accessible interventions.

For instance, Sleepio, an AI-powered digital platform, offers CBT-I therapy that is accessible from home. The app analyzes sleep data and provides personalized cognitive and behavioral strategies to help users overcome insomnia. The success of this solution has spurred the development of more AI-based insomnia treatment platforms.

Additionally, AI has the ability to provide personalized sleep insights by analyzing individual sleep patterns, lifestyle data, and other factors that affect sleep. This level of customization is especially beneficial for insomnia patients, as AI tools can recommend tailored sleep schedules, relaxation techniques and environmental adjustments that are specific to each person's needs.

For instance, Oura Ring, a wearable that uses AI to track various physiological metrics, provides users with detailed insights into their sleep stages, including REM sleep and deep sleep. It also offers personalized recommendations for improving sleep quality based on individual data, making it a popular choice for people dealing with insomnia.

Geographical Analysis

North America is expected to hold a significant position in the AI in detecting sleep disorders market with the highest market share

Sleep disorders, especially insomnia and sleep apnea, are highly prevalent in North America, leading to a strong demand for innovative AI solutions that can help diagnose and manage these conditions. The increasing awareness about the consequences of poor sleep on overall health has prompted both consumers and healthcare providers to adopt AI-based solutions. For instance, according to the Psychiatry Organization, an estimated 34 percent of Americans report their sleep quality as "poor" or "only fair." More than 50 million Americans have chronic sleep disorders.

AI allows for personalized sleep treatments that are customized to an individual's sleep patterns and health needs. North American consumers have a growing preference for tailored health solutions, and AI in sleep disorder detection is well-suited to meet this demand by offering personalized feedback, sleep management techniques, and even adjustments to environmental factors like room temperature, lighting, and noise levels.

For instance, Endel, a company offering AI-generated soundscapes, provides personalized audio tracks to improve sleep quality, reduce anxiety and enhance relaxation. These AI-driven solutions contribute to the growing trend of personalized sleep management.

Competitive Landscape

The major global players in the AI in detecting sleep disorders market include Fullpower Technologies, Inc., Apple Inc., Endel, BigHealth, dbbeats, Dr.BreathE, Neybox Digital Ltd., SleepUp Limited, Calm.com, Inc., Sleep Cycle AB and among others.

Why Purchase the Report?

• Pipeline & Innovations: Reviews ongoing clinical trials, product pipelines, and forecasts upcoming advancements in medical devices and pharmaceuticals.
• Product Performance & Market Positioning: Analyzes product performance, market positioning, and growth potential to optimize strategies.
• Real-World Evidence: Integrates patient feedback and data into product development for improved outcomes.
• Physician Preferences & Health System Impact: Examines healthcare provider behaviors and the impact of health system mergers on adoption strategies.
• Market Updates & Industry Changes: Covers recent regulatory changes, new policies, and emerging technologies.
• Competitive Strategies: Analyzes competitor strategies, market share, and emerging players.
• Pricing & Market Access: Reviews pricing models, reimbursement trends, and market access strategies.
• Market Entry & Expansion: Identifies optimal strategies for entering new markets and partnerships.
• Regional Growth & Investment: Highlights high-growth regions and investment opportunities.
• Supply Chain Optimization: Assesses supply chain risks and distribution strategies for efficient product delivery.
• Sustainability & Regulatory Impact: Focuses on eco-friendly practices and evolving regulations in healthcare.
• Post-market Surveillance: Uses post-market data to enhance product safety and access.
• Pharmacoeconomics & Value-Based Pricing: Analyzes the shift to value-based pricing and data-driven decision-making in R&D.

The global AI in detecting sleep disorders market report delivers a detailed analysis with 70 key tables, more than 65 visually impactful figures and 159 pages of expert insights, providing a complete view of the market landscape.

Target Audience 2024

• Manufacturers: Pharmaceutical, Medical Device, Biotech Companies, Contract Manufacturers, Distributors, Hospitals.
• Regulatory & Policy: Compliance Officers, Government, Health Economists, Market Access Specialists.
• Technology & Innovation: AI/Robotics Providers, R&D Professionals, Clinical Trial Managers, Pharmacovigilance Experts.
• Investors: Healthcare Investors, Venture Fund Investors, Pharma Marketing & Sales.
• Consulting & Advisory: Healthcare Consultants, Industry Associations, Analysts.
• Supply Chain: Distribution and Supply Chain Managers.
• Consumers & Advocacy: Patients, Advocacy Groups, Insurance Companies.
• Academic & Research: Academic Institutions.