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AI In Blood Pressure Monitoring Market Size, Share & Trends Analysis Report By Device Type (Wearable Devices), By Technology (Machine Learning Algorithms), By Delivery Mode, By Application, By End Use, By Region, And Segment Forecasts, 2025 - 2030
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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.

Table of Contents

Chapter 1. Methodology and Scope

Chapter 2. Executive Summary

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

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

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

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

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

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

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

Chapter 10. Competitive Landscape

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