Intelligent Surgical Systems with Real-time Haptic Feedback and Autonomous Tool Movement

Publication ID: 24-11857201_0005_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Surgical Systems with Real-time Haptic Feedback and Autonomous Tool Movement,” Published Technical Disclosure No. 24-11857201_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857201_0005_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,201.

Summary of the Inventive Concept

A next-generation surgical system that integrates artificial intelligence, haptic feedback, and autonomous tool movement to revolutionize the field of computer-assisted surgeries, enhancing precision, speed, and safety.

Background and Problem Solved

The original patent, 'Surgical system with automated alignment,' introduced a system that relied on pre-operative planning and automated alignment. However, this system had limitations in terms of real-time adaptability, tactile feedback, and autonomous decision-making. The new inventive concept addresses these limitations by incorporating machine learning, haptic feedback, and swarm robotics to create a more dynamic, responsive, and efficient surgical system.

Detailed Description of the Inventive Concept

The new surgical system comprises a neural network-based prediction module, a haptic device, and a robotic device. The prediction module forecasts optimal surgical trajectories, while the haptic device provides real-time tactile feedback to the surgeon based on these predictions. The robotic device automatically adjusts surgical tool movement in response to the predicted trajectories. Additionally, the system may include a swarm of micro-robots for autonomous tissue dissection, a virtual reality module for simulation-based training, and a machine learning-based evaluation module for real-time surgical skill assessment.

Novelty and Inventive Step

The new claims introduce a paradigm shift in surgical systems by integrating artificial intelligence, haptic feedback, and autonomous tool movement. The use of neural networks for prediction, swarm robotics for tissue dissection, and machine learning-based evaluation for surgical skill assessment are all novel and non-obvious advancements over the original patent.

Alternative Embodiments and Variations

Alternative embodiments may include the use of different machine learning algorithms, varying haptic feedback modalities, or incorporating additional sensors for real-time data acquisition. Variations may also involve adapting the system for different surgical specialties, such as orthopedic, neurosurgical, or ophthalmological procedures.

Potential Commercial Applications and Market

The intelligent surgical system has vast commercial potential in the healthcare industry, particularly in the fields of computer-assisted surgeries, surgical training, and medical robotics. The system's enhanced precision, speed, and safety features can lead to improved patient outcomes, reduced recovery times, and increased adoption rates among surgeons.

CPC Classifications

SectionClassGroup
A A61 A61B17/15
A A61 A61B17/142
A A61 A61B17/1615
A A61 A61B17/1703
A A61 A61B34/20
A A61 A61B34/30
A A61 A61B34/76
A A61 A61B17/157
A A61 A61B34/25
A A61 A61B90/03
A A61 A61B2017/00128
A A61 A61B2034/105
A A61 A61B2034/2055

Field of Art

Surgical robotics and computer-assisted medical systems, specifically focusing on haptic feedback, robotic tool control, and surgical navigation technologies. Requires advanced understanding of robotics, machine learning, sensor integration, and surgical procedural workflows

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or robotics specialist with expertise in surgical systems, machine learning algorithms, sensor design, and human-machine interaction. Possesses advanced degrees in biomedical engineering, computer science, or related fields with practical experience in developing medical robotics

Obviousness Rationale

A PHOSITA would recognize that the PTD's variations represent predictable technological extensions of the source patent's foundational surgical robotics framework. The integration of neural networks, machine learning, and autonomous movement are natural progressions in surgical system design, leveraging known computational techniques to enhance existing robotic surgical platforms. The disclosed variations demonstrate incremental improvements that would be obvious to a skilled practitioner seeking to optimize surgical precision and automation.

Obvious Combinations & Variations

Source Patent Element
Robotic device configured to be coupled to a surgical tool with controllable movement
PTD Variation
Neural network-based prediction module for generating optimal surgical trajectories
Obviousness Reasoning
Predictable application of machine learning to existing robotic control systems, representing a known technique for improving automated tool guidance
Source Patent Element
Haptic feedback system providing tactile sensations during surgical procedures
PTD Variation
Real-time tactile feedback integrated with AI-predicted surgical trajectories
Obviousness Reasoning
Logical extension of existing haptic feedback technologies, combining known sensor integration techniques with predictive computational methods
Source Patent Element
Sensor for detecting user presence and enabling automatic movement
PTD Variation
Machine learning-based surgical skill assessment module tracking surgeon movements
Obviousness Reasoning
Natural progression of sensor-based interaction, applying advanced computational analysis to existing user interaction monitoring techniques
Source Patent Element
Surgical system with configurable virtual planes and resection parameters
PTD Variation
Swarm micro-robot system for autonomous tissue dissection with dynamic movement adjustment
Obviousness Reasoning
Predictable technological evolution applying distributed robotics principles to existing surgical navigation concepts
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857201 and the published technical disclosure, a person having ordinary skill in the art would find the claimed surgical system variations obvious and anticipated. The disclosed innovations represent foreseeable technological improvements utilizing known computational techniques, sensor integration methods, and robotic control strategies that would be readily apparent to a skilled practitioner in surgical robotics and machine learning technologies.

Original Patent Information

Patent NumberUS 11,857,201
TitleSurgical system with automated alignment
Assignee(s)MAKO Surgical Corp.