AI in Remote Patient Monitoring Market Size is valued at USD 1,221.35 Mn in 2022 and is predicted to reach USD 6,896.41 Mn by the year 2031 at a 21.3% CAGR during the forecast period for 2023-2031.
AI in Remote Patient Monitoring (RPM) utilizes technology to remotely gather and analyze patient health data, offering continuous monitoring, early warning capabilities, personalized care, and cost reduction. This approach integrates with telehealth, tailors care plans, ensures data security, and aids clinical decision-making. It empowers patients, reduces healthcare expenses, and has the potential for population health management. Successful implementation requires robust data infrastructure, secure communication, and adherence to regulations, ultimately improving patient care and healthcare efficiency.
Large data quantities, growing issues connected to healthcare expenditures, and precise patient outcomes contribute to the healthcare sector's rapid evolution.
The need for real-time data is growing as the prevalence of chronic diseases, including diabetes, cardiovascular disease, and chronic respiratory diseases, rises, which in turn is driving demand for AI technology in remote patient monitoring. Approximately 9.3% of the world's population, or 463 Mn people, have diabetes, according to Diabetes Research and Clinical Practices, with the highest prevalence in low- and middle-income nations.
The AI in the Remote Patient Monitoring market has been segmented based on product, solution, technology, and application. The market is broadly divided into special and vital monitors based on the product. The solution segment includes hardware, services, and software. The technology segment includes machine learning, natural language processing, querying methods, and speech recognition. The application segments include cancer, cardiovascular diseases, dehydration, diabetes, infections, respiratory issues, sleep disorders, viral infection, and weight management & fitness monitoring.
The market for AI in remote patient monitoring is dominated by the machine learning segment in terms of revenue. Machine learning, a kind of AI, uses specialized algorithms to assist clinicians in swiftly comprehending complex data. In order to aid in the early detection of health status deterioration, they can assist with patient evaluations and even classify the patient's varied movements and activities. Large datasets can be processed by these AI systems to find and comprehend complicated patterns for decision-making.
The market for artificial intelligence (AI) in remote patient monitoring had the greatest revenue share in the world. Doctors can get asset information via remote monitoring using AI software even when assets are dispersed across several physical sites. It can, therefore, be used to monitor and assess the performance and condition of assets located away from the workplace, such as while patients are travelling.
The market had its greatest revenue share in North America. In 2022, the market is dominated by North America as a result of the presence of significant companies. Additionally, it is projected that the expansion will be aided by North America's more straightforward payback regulations and a rise in the occurrence of uncommon diseases. The market has also been considerably impacted by the general public's increased awareness of diseases, their treatments, and related preventative actions. The adoption of smartphones, network advancements, and internet and social media use drives the industry. The growth of mHealth apps and intensive R&D in health wearables are driving the demand for AI-based remote patient monitoring solutions in the North American region.
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Report Attribute |
Specifications |
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Market Size Value In 2022 |
USD 1,221.35 Mn |
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Revenue Forecast In 2031 |
USD 6,896.41 Mn |
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Growth Rate CAGR |
CAGR of 21.3% from 2023 to 2031 |
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Quantitative Units |
Representation of revenue in US$ Mn and CAGR from 2023 to 2031 |
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Historic Year |
2019 to 2022 |
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Forecast Year |
2023-2031 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Product, Solution, Technology, Application |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia |
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Competitive Landscape |
Aicurev, Binah.Ai, Biofourmis, Care.Ai Inc., Connect America LLC, Cardiomo Care, Inc., ChroniSense Medical, Ltd., CU-BX Automotive Technologies Ltd., Current Health, Healthsaas Inc., Implicity, Maya Md, Somatix Inc., Ejenta, Inc., Feebris Ltd., Gyant.com, Inc., Huma Therapeutics Limited, Neteera Technologies Ltd., iBeat, Inc., iHealth Labs, Inc., Others |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Remote Patient Monitoring Market Snapshot
Chapter 4. Global AI in Remote Patient Monitoring Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Product Estimates & Trend Analysis
5.1. By Product, & Market Share, 2020 & 2031
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Product:
5.2.1. Special Monitors
5.2.1.1. Anaesthesia Monitors
5.2.1.2. Blood Glucose Monitor
5.2.1.3. Cardiac Rhythm Monitor
5.2.1.4. Fetal Heart Rate Monitor
5.2.1.5. Multi-Parameter monitors
5.2.1.6. Prothrombin Monitors
5.2.1.7. Respiratory Monitor
5.2.2. Vital Monitors
5.2.2.1. Blood Pressure Monitor
5.2.2.2. Brain Monitor
5.2.2.3. Heart Rate Monitor
5.2.2.4. Pulse Oximeter
5.2.2.5. Respiratory Monitor
5.2.2.6. Temperature Monitor
Chapter 6. Market Segmentation 2: By Solution Estimates & Trend Analysis
6.1. By Solution & Market Share, 2020 & 2031
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Solution:
6.2.1. Hardware
6.2.2. Services
6.2.3. Software
Chapter 7. Market Segmentation 3: By Technology Estimates & Trend Analysis
7.1. By Technology & Market Share, 2020 & 2031
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Technology:
7.2.1. Machine Learning
7.2.2. Natural Language Processing
7.2.3. Querying Method
7.2.4. Speech Recognition
Chapter 8. Market Segmentation 4: By Application Estimates & Trend Analysis
8.1. By Application & Market Share, 2020 & 2031
8.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Application:
8.2.1. Cancer
8.2.2. Cardiovascular Diseases
8.2.3. Dehydration
8.2.4. Diabetes
8.2.5. Infections
8.2.6. Respiratory Issues
8.2.7. Sleep Disorder
8.2.8. Viral Infection
8.2.9. Weight Management & Fitness Monitoring
Chapter 9. AI in Remote Patient Monitoring Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America AI in Remote Patient Monitoring Market revenue (US$ Million) estimates and forecasts By Product, 2019-2031
9.1.2. North America AI in Remote Patient Monitoring Market revenue (US$ Million) estimates and forecasts By Solution, 2019-2031
9.1.3. North America AI in Remote Patient Monitoring Market revenue (US$ Million) estimates and forecasts By Technology, 2019-2031
9.1.4. North America AI in Remote Patient Monitoring Market revenue (US$ Million) estimates and forecasts By Application, 2019-2031
9.1.5. North America AI in Remote Patient Monitoring Market revenue (US$ Million) estimates and forecasts by country, 2019-2031
9.2. Europe
9.2.1. Europe AI in Remote Patient Monitoring Market revenue (US$ Million) By Product, 2019-2031
9.2.2. Europe AI in Remote Patient Monitoring Market revenue (US$ Million) By Solution, 2019-2031
9.2.3. Europe AI in Remote Patient Monitoring Market revenue (US$ Million) By Technology, 2019-2031
9.2.4. Europe AI in Remote Patient Monitoring Market revenue (US$ Million) By Application, 2019-2031
9.2.5. Europe AI in Remote Patient Monitoring Market revenue (US$ Million) by country, 2019-2031
9.3. Asia Pacific
9.3.1. Asia Pacific AI in Remote Patient Monitoring Market revenue (US$ Million) By Product, 2019-2031
9.3.2. Asia Pacific AI in Remote Patient Monitoring Market revenue (US$ Million) By Solution, 2019-2031
9.3.3. Asia Pacific AI in Remote Patient Monitoring Market revenue (US$ Million) By Technology, 2019-2031
9.3.4. Asia Pacific AI in Remote Patient Monitoring Market revenue (US$ Million) By Application, 2019-2031
9.3.5. Asia Pacific AI in Remote Patient Monitoring Market revenue (US$ Million) by country, 2019-2031
9.4. Latin America
9.4.1. Latin America AI in Remote Patient Monitoring Market revenue (US$ Million) By Product, (US$ Million) 2019-2031
9.4.2. Latin America AI in Remote Patient Monitoring Market revenue (US$ Million) By Solution, (US$ Million) 2019-2031
9.4.3. Latin America AI in Remote Patient Monitoring Market revenue (US$ Million) By Technology, (US$ Million) 2019-2031
9.4.4. Latin America AI in Remote Patient Monitoring Market revenue (US$ Million) By Application, (US$ Million) 2019-2031
9.4.5. Latin America AI in Remote Patient Monitoring Market revenue (US$ Million) by country, 2019-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa AI in Remote Patient Monitoring Market revenue (US$ Million) By Product, (US$ Million) 2019-2031
9.5.2. Middle East & Africa AI in Remote Patient Monitoring Market revenue (US$ Million) By Solution, (US$ Million) 2019-2031
9.5.3. Middle East & Africa AI in Remote Patient Monitoring Market revenue (US$ Million) By Technology, (US$ Million) 2019-2031
9.5.4. Middle East & Africa AI in Remote Patient Monitoring Market revenue (US$ Million) By Application, (US$ Million) 2019-2031
9.5.5. Middle East & Africa AI in Remote Patient Monitoring Market revenue (US$ Million) by country, 2019-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. AiCure LLC
10.2.2. Binah.ai
10.2.3. Biofourmis Inc.
10.2.4. Cardiomo Care Inc.
10.2.5. ChroniSense Medical Ltd
10.2.6. Current Health Limited
10.2.7. Ejenta Inc.
10.2.8. Feebris Ltd
AI in Remote Patient Monitoring Market By Product-
AI in Remote Patient Monitoring Market By Solution-
AI in Remote Patient Monitoring Market By Technology-
AI in Remote Patient Monitoring Market By Application-
AI in Remote Patient Monitoring Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
