세계의 혈압 모니터링용 AI 시장 규모, 점유율, 동향 분석 보고서 : 기기 종류별, 기술별, 제공 방식별, 용도별, 최종 용도별, 지역별, 부문별 예측(2025-2030년)

AI In Blood Pressure Monitoring Market Summary

The global AI in blood pressure monitoring market size was estimated at USD 932.52 million in 2024 and is projected to reach USD 4.38 billion by 2030, growing at a CAGR of 29.98% from 2025 to 2030. Rising prevalence of hypertension and cardiovascular diseases, increasing demand for continuous and non-invasive monitoring, and growing consumer adoption of smart health devices are significant factors contributing to market growth.

In addition, advancements in AI and sensor technologies and integration with telehealth & remote patient monitoring platforms are some other factors fueling market growth further. The increasing prevalence of hypertension and cardiovascular disorders (CVDs) globally significantly contributes to the AI in blood pressure monitoring market growth. For instance, according to the World Health Organization, an estimated 1.28 billion adults (aged 30-79 years) are currently living with hypertension. In addition, CVDs are the leading cause of death globally, causing an estimated 17.9 million deaths each year. This case surge pressures healthcare systems to adopt technologies that offer early detection, real-time monitoring, and proactive intervention. AI-powered blood pressure monitors help early detection of irregularities, supporting proactive disease management.

Machine learning and AI algorithms have made significant advancements in signal processing, data interpretation, and pattern recognition. With advanced biosensors and IoT connectivity, AI analyzes blood pressure data alongside other health metrics such as heart rate, activity levels, oxygen concentration, and sleep quality. These advancements have enhanced the accuracy, predictive capabilities, and personalization of blood pressure monitoring systems. In addition, edge AI allows faster processing and real-time feedback directly on the device, reducing the dependence on cloud infrastructure.

Furthermore, advancements in AI & sensor technologies fuel market growth. Innovations in machine learning, edge computing, and biosensor miniaturization have significantly enhanced the accuracy and reliability of blood pressure estimation. AI can identify patterns and anomalies across vast data sets, allowing for personalized insights and predictive alerts, which improve user engagement and clinical decision-making. AI-powered monitoring systems use photoplethysmography (PPG) sensors to measure blood pressure, oxygen saturation, etc. For instance, in August 2024, Bisam Pharmaceuticals launched Quick Vitals, an AI and deep learning-powered health monitoring app in Hyderabad, India. This app uses Photoplethysmography (PPG) technology for rapid, accurate vital sign assessments such as heart rate, blood pressure, SPO2, etc., via smartphones or tablets in seconds.

In addition, the healthcare industry's adoption of AI-powered wearables is expanding rapidly. AI enhances its utility by analyzing large volumes of physiological data to detect anomalies, predict health risks, and enable timely interventions. This improves patient outcomes and reduces the burden on healthcare systems by minimizing hospital visits and enabling telehealth services. For instance, in June 2024, Sky Labs launched CART BP, a smart ring for continuous blood pressure monitoring. The ring provides real-time, non-invasive blood pressure tracking using advanced sensors and AI algorithms.

Global AI In Blood Pressure Monitoring Market Report Segmentation

This report forecasts, revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented global AI in blood pressure monitoring market report based on device type, technology, delivery mode, application, end use, and region.

• Device Type Outlook (Revenue, USD Million, 2018 - 2030)
• Wearable Devices
  • Smartwatches
  • Fitness Bands
  • Patch Sensors
  • Smart Rings
• Cuff-based Device
• Cuffless Solutions
• Technology Outlook (Revenue, USD Million, 2018 - 2030)
• Machine Learning Algorithms
  • Deep learning
  • Supervised
  • Unsupervised
  • Others
• Natural Language Processing (NLP)
• Computer Vision Techniques
• Delivery Mode Outlook (Revenue, USD Million, 2018 - 2030)
• On-Device AI
• Cloud-based AI
• Hybrid AI
• Application Outlook (Revenue, USD Million, 2018 - 2030)
• Hypertension Management
• Cardiovascular Disease Prediction
• Remote Patient Monitoring
• Fitness and Wellness
• Others
• End Use Outlook (Revenue, USD Million, 2018 - 2030)
• Hospitals & Acute Care
• Home Care Settings/Patient (Consumers)
• Clinics & Ambulatory Care
• Others
• Regional Outlook (Revenue, USD Million, 2018 - 2030)
• North America
  • U.S.
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Denmark
  • Sweden
  • Norway
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Thailand
• Latin America
  • Brazil
  • Argentina
• MEA
  • South Africa
  • Saudi Arabia
  • UAE
  • Kuwait

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
• 1.2. Market Definitions
  • 1.2.1. Device Type Segment
  • 1.2.2. Technology Segment
  • 1.2.3. Delivery Mode Segment
  • 1.2.4. Application Segment
  • 1.2.5. End Use
• 1.3. Information analysis
  • 1.3.1. Market formulation & data visualization
• 1.4. Data validation & publishing
• 1.5. Information Procurement
  • 1.5.1. Primary Research
• 1.6. Information or Data Analysis
• 1.7. Market Formulation & Validation
• 1.8. Market Model
• 1.9. Total Market: CAGR Calculation
• 1.10. Objectives
  • 1.10.1. Objective 1
  • 1.10.2. Objective 2

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Snapshot
• 2.3. Competitive Insights Landscape

Chapter 3. AI in Blood Pressure Monitoring Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook.
• 3.2. Market Dynamics
  • 3.2.1. Market driver analysis
    • 3.2.1.1. Rising prevalence of hypertension and cardiovascular diseases
    • 3.2.1.2. Increasing demand for continuous and non-invasive monitoring
    • 3.2.1.3. Advancements in AI and sensor technologies and growing consumer adoption of smart health devices
  • 3.2.2. Market restraint analysis
    • 3.2.2.1. Data security and privacy concerns
    • 3.2.2.2. High costs of advanced devices
  • 3.2.3. Market opportunity analysis
  • 3.2.4. Market challenges analysis
• 3.3. Case Studies
• 3.4. AI in Blood Pressure Monitoring Market Analysis Tools
  • 3.4.1. Industry Analysis - Porter's
    • 3.4.1.1. Supplier power
    • 3.4.1.2. Buyer power
    • 3.4.1.3. Substitution threat
    • 3.4.1.4. Threat of new entrant
    • 3.4.1.5. Competitive rivalry
  • 3.4.2. PESTEL Analysis
    • 3.4.2.1. Political landscape
    • 3.4.2.2. Technological landscape
    • 3.4.2.3. Economic landscape
    • 3.4.2.4. Environmental Landscape
    • 3.4.2.5. Legal Landscape
    • 3.4.2.6. Social Landscape

Chapter 4. AI in Blood Pressure Monitoring Market: Device Type Estimates & Trend Analysis

• 4.1. Segment Dashboard
• 4.2. Global AI in Blood Pressure Monitoring Market Device Type Movement Analysis
• 4.3. Global AI in Blood Pressure Monitoring Market Size & Trend Analysis, by Device Type, 2018 to 2030 (USD Million)
• 4.4. Wearable Devices
  • 4.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 4.4.2. Smartwatches
    • 4.4.2.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 4.4.3. Fitness Bands
    • 4.4.3.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 4.4.4. Patch Sensors
    • 4.4.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 4.4.5. Smart Rings
    • 4.4.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 4.5. Cuff-based Device
  • 4.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 4.6. Cuffless Solutions
  • 4.6.1. Market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 5. AI in Blood Pressure Monitoring Market: Technology Estimates & Trend Analysis

• 5.1. Segment Dashboard
• 5.2. Global AI in Blood Pressure Monitoring Market Technology Movement Analysis
• 5.3. Global AI in Blood Pressure Monitoring Market Size & Trend Analysis, by Technology, 2018 to 2030 (USD Million)
• 5.4. Machine Learning Algorithms
  • 5.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 5.4.2. Deep learning
    • 5.4.2.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 5.4.3. Supervised
    • 5.4.3.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 5.4.4. Unsupervised
    • 5.4.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
  • 5.4.5. Others
    • 5.4.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 5.5. Natural Language Processing (NLP)
  • 5.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 5.6. Computer Vision Techniques
  • 5.6.1. Market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 6. AI in Blood Pressure Monitoring Market: Delivery Mode Estimates & Trend Analysis

• 6.1. Segment Dashboard
• 6.2. Global AI in Blood Pressure Monitoring Market Delivery Mode Movement Analysis
• 6.3. Global AI in Blood Pressure Monitoring Market Size & Trend Analysis, by Delivery Mode, 2018 to 2030 (USD Million)
• 6.4. On-Device AI
  • 6.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 6.5. Cloud-based AI
  • 6.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 6.6. Hybrid AI
  • 6.6.1. Market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 7. AI in Blood Pressure Monitoring Market: Application Estimates & Trend Analysis

• 7.1. Segment Dashboard
• 7.2. Global AI in Blood Pressure Monitoring Market Application Movement Analysis
• 7.3. Global AI in Blood Pressure Monitoring Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
• 7.4. Hypertension Management
  • 7.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 7.5. Cardiovascular Disease Prediction
  • 7.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 7.6. Remote Patient Monitoring
  • 7.6.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 7.7. Fitness and Wellness
  • 7.7.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 7.8. Others
  • 7.8.1. Market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 8. AI in Blood Pressure Monitoring Market: End Use Estimates & Trend Analysis

• 8.1. Segment Dashboard
• 8.2. Global AI in Blood Pressure Monitoring Market End Use Movement Analysis
• 8.3. Global AI in Blood Pressure Monitoring Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
• 8.4. Hospitals & Acute Care
  • 8.4.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 8.5. Home Care Settings/Patient (Consumers)
  • 8.5.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 8.6. Clinics & Ambulatory Care
  • 8.6.1. Market estimates and forecasts, 2018 to 2030 (USD Million)
• 8.7. Others
  • 8.7.1. Market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 9. AI in Blood Pressure Monitoring Market: Regional Estimates & Trend Analysis

• 9.1. Regional Market Share Analysis, 2024 & 2030
• 9.2. Regional Market Dashboard
• 9.3. Market Size & Forecasts Trend Analysis, 2018 to 2030:
• 9.4. North America
  • 9.4.1. U.S.
    • 9.4.1.1. Key country dynamics
    • 9.4.1.2. Regulatory framework
    • 9.4.1.3. Competitive scenario
    • 9.4.1.4. U.S. market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.4.2. Canada
    • 9.4.2.1. Key country dynamics
    • 9.4.2.2. Regulatory framework
    • 9.4.2.3. Competitive scenario
    • 9.4.2.4. Canada market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.4.3. Mexico
    • 9.4.3.1. Key country dynamics
    • 9.4.3.2. Regulatory framework
    • 9.4.3.3. Competitive scenario
    • 9.4.3.4. Mexico market estimates and forecasts, 2018 to 2030 (USD Million)
• 9.5. Europe
  • 9.5.1. UK
    • 9.5.1.1. Key country dynamics
    • 9.5.1.2. Regulatory framework
    • 9.5.1.3. Competitive scenario
    • 9.5.1.4. UK market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.2. Germany
    • 9.5.2.1. Key country dynamics
    • 9.5.2.2. Regulatory framework
    • 9.5.2.3. Competitive scenario
    • 9.5.2.4. Germany market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.3. France
    • 9.5.3.1. Key country dynamics
    • 9.5.3.2. Regulatory framework
    • 9.5.3.3. Competitive scenario
    • 9.5.3.4. France market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.4. Italy
    • 9.5.4.1. Key country dynamics
    • 9.5.4.2. Regulatory framework
    • 9.5.4.3. Competitive scenario
    • 9.5.4.4. Italy market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.5. Spain
    • 9.5.5.1. Key country dynamics
    • 9.5.5.2. Regulatory framework
    • 9.5.5.3. Competitive scenario
    • 9.5.5.4. Spain market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.6. Norway
    • 9.5.6.1. Key country dynamics
    • 9.5.6.2. Regulatory framework
    • 9.5.6.3. Competitive scenario
    • 9.5.6.4. Norway market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.7. Sweden
    • 9.5.7.1. Key country dynamics
    • 9.5.7.2. Regulatory framework
    • 9.5.7.3. Competitive scenario
    • 9.5.7.4. Sweden market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.5.8. Denmark
    • 9.5.8.1. Key country dynamics
    • 9.5.8.2. Regulatory framework
    • 9.5.8.3. Competitive scenario
    • 9.5.8.4. Denmark market estimates and forecasts, 2018 to 2030 (USD Million)
• 9.6. Asia Pacific
  • 9.6.1. Japan
    • 9.6.1.1. Key country dynamics
    • 9.6.1.2. Regulatory framework
    • 9.6.1.3. Competitive scenario
    • 9.6.1.4. Japan market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.6.2. China
    • 9.6.2.1. Key country dynamics
    • 9.6.2.2. Regulatory framework
    • 9.6.2.3. Competitive scenario
    • 9.6.2.4. China market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.6.3. India
    • 9.6.3.1. Key country dynamics
    • 9.6.3.2. Regulatory framework
    • 9.6.3.3. Competitive scenario
    • 9.6.3.4. India market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.6.4. Australia
    • 9.6.4.1. Key country dynamics
    • 9.6.4.2. Regulatory framework
    • 9.6.4.3. Competitive scenario
    • 9.6.4.4. Australia market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.6.5. South Korea
    • 9.6.5.1. Key country dynamics
    • 9.6.5.2. Regulatory framework
    • 9.6.5.3. Competitive scenario
    • 9.6.5.4. South Korea market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.6.6. Thailand
    • 9.6.6.1. Key country dynamics
    • 9.6.6.2. Regulatory framework
    • 9.6.6.3. Competitive scenario
    • 9.6.6.4. Thailand market estimates and forecasts, 2018 to 2030 (USD Million)
• 9.7. Latin America
  • 9.7.1. Brazil
    • 9.7.1.1. Key country dynamics
    • 9.7.1.2. Regulatory framework
    • 9.7.1.3. Competitive scenario
    • 9.7.1.4. Brazil market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.7.2. Argentina
    • 9.7.2.1. Key country dynamics
    • 9.7.2.2. Regulatory framework
    • 9.7.2.3. Competitive scenario
    • 9.7.2.4. Argentina market estimates and forecasts, 2018 to 2030 (USD Million)
• 9.8. MEA
  • 9.8.1. South Africa
    • 9.8.1.1. Key country dynamics
    • 9.8.1.2. Regulatory framework
    • 9.8.1.3. Competitive scenario
    • 9.8.1.4. South Africa market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.8.2. Saudi Arabia
    • 9.8.2.1. Key country dynamics
    • 9.8.2.2. Regulatory framework
    • 9.8.2.3. Competitive scenario
    • 9.8.2.4. Saudi Arabia market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.8.3. UAE
    • 9.8.3.1. Key country dynamics
    • 9.8.3.2. Regulatory framework
    • 9.8.3.3. Competitive scenario
    • 9.8.3.4. UAE market estimates and forecasts, 2018 to 2030 (USD Million)
  • 9.8.4. Kuwait
    • 9.8.4.1. Key country dynamics
    • 9.8.4.2. Regulatory framework
    • 9.8.4.3. Competitive scenario
    • 9.8.4.4. Kuwait market estimates and forecasts, 2018 to 2030 (USD Million)

Chapter 10. Competitive Landscape

• 10.1. Company/Competition Categorization
• 10.2. Strategy Mapping
• 10.3. Company Market Position Analysis, 2024
• 10.4. Company Profiles/Listing
  • 10.4.1. Withings
    • 10.4.1.1. Company overview
    • 10.4.1.2. Financial performance
    • 10.4.1.3. Product benchmarking
    • 10.4.1.4. Strategic initiatives
  • 10.4.2. Aktiia SA
    • 10.4.2.1. Company overview
    • 10.4.2.2. Financial performance
    • 10.4.2.3. Product benchmarking
    • 10.4.2.4. Strategic initiatives
  • 10.4.3. Biospectal SA
    • 10.4.3.1. Company overview
    • 10.4.3.2. Financial performance
    • 10.4.3.3. Product benchmarking
    • 10.4.3.4. Strategic initiatives
  • 10.4.4. Valencell, INC.
    • 10.4.4.1. Company overview
    • 10.4.4.2. Financial performance
    • 10.4.4.3. Product benchmarking
    • 10.4.4.4. Strategic initiatives
  • 10.4.5. Biofourmis
    • 10.4.5.1. Company overview
    • 10.4.5.2. Financial performance
    • 10.4.5.3. Product benchmarking
    • 10.4.5.4. Strategic initiatives
  • 10.4.6. Edwards Lifesciences Corporation (now BD)
    • 10.4.6.1. Company overview
    • 10.4.6.2. Financial performance
    • 10.4.6.3. Product benchmarking
    • 10.4.6.4. Strategic initiatives
  • 10.4.7. Hello Heart
    • 10.4.7.1. Company overview
    • 10.4.7.2. Financial performance
    • 10.4.7.3. Product benchmarking
    • 10.4.7.4. Strategic initiatives
  • 10.4.8. FaceHeart Corporation
    • 10.4.8.1. Company overview
    • 10.4.8.2. Financial performance
    • 10.4.8.3. Product benchmarking
    • 10.4.8.4. Strategic initiatives
  • 10.4.9. Shen AI
    • 10.4.9.1. Company overview
    • 10.4.9.2. Financial performance
    • 10.4.9.3. Product benchmarking
    • 10.4.9.4. Strategic initiatives
  • 10.4.10. Huawei Technologies Co., Ltd.
    • 10.4.10.1. Company overview
    • 10.4.10.2. Financial performance
    • 10.4.10.3. Product benchmarking
    • 10.4.10.4. Strategic initiatives