Next Generation Surgical Robotics Market Size
Market Outlook:
Base Year Value (2023)
USD 3.23 Billion
CAGR (2024-2032)
34.9%
Forecast Year Value (2032)
USD 47.79 Billion
Historical Data Period
2019-2023
Largest Region
North America
Forecast Period
2024-2032
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Market Dynamics:
Growth Drivers & Opportunity:The Next Generation Surgical Robotics Market is expected to be driven by technological advancements in robotic surgery systems, which allow for more precise and minimally invasive procedures. These systems are also equipped with features such as image guidance and haptic feedback, which enhance the surgeon's control and accuracy during surgery. Additionally, the increasing adoption of surgical robots in various medical specialties, including urology, gynecology, and orthopedics, is expected to drive market growth.
Industry
Report Scope
| Report Coverage | Details |
|---|---|
| Segments Covered | Component, Technology, Surgery Type, End User |
| Regions Covered | • North America (United States, Canada, Mexico) • Europe (Germany, United Kingdom, France, Italy, Spain, Rest of Europe) • Asia Pacific (China, Japan, South Korea, Singapore, India, Australia, Rest of APAC) • Latin America (Argentina, Brazil, Rest of South America) • Middle East & Africa (GCC, South Africa, Rest of MEA) |
| Company Profiled | Medrobotics, Renishaw plc., TransEnterix Surgical,, Intuitive Surgical, Medtronic plc, THINK Surgical , Zimmer Biomet Holdings, Smith & Nephew Plc. , Auris Next generation surgical robotics,, Intuitive Surgical,, KUKA AG, Stryker, Mazor Robotics |
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However, the high cost of procurement and maintenance of surgical robotic systems remains a major restraint for market growth. The initial investment required for purchasing these systems, along with the additional costs for training and maintenance, can be significant barriers for healthcare facilities. Furthermore, the limited availability of skilled professionals who are trained to operate surgical robots is another major restraint for the market. Training healthcare professionals to use these advanced systems can be time-consuming and resource-intensive, thereby hindering their widespread adoption.
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