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Innovative Haptic System Enhances Robotic Surgery Training

In an article recently submitted to the arXiv* server, researchers introduced an innovative, cost-effective system to improve robotic surgery training by addressing the lack of haptic feedback in existing systems. Their goal was to enhance surgical training fidelity and the precision of robotic-assisted surgeries, promoting broader adoption and safer practices.

Innovative Haptic System Enhances Robotic Surgery Training
Study: Innovative Haptic System Enhances Robotic Surgery Training. Image Credit: Gorodenkoff/


Robotic-assisted surgery has transformed minimally invasive procedures by offering surgeons enhanced dexterity, precision, reliability, and stability compared to traditional methods.

These systems allow operations through small incisions using specialized instruments and an endoscopic camera. Benefits for patients include less pain, fewer complications, quicker recovery, and minimal scarring.

However, current systems rely mainly on visual feedback from three-dimensional (3D) cameras, which is helpful by lacking the sense of touch and force (haptic feedback). This feedback is important for surgeons to feel the forces and textures during surgery for performing delicate operations safely and effectively.

Haptic feedback encompasses kinesthetic (force) and tactile (grip and texture) sensations, providing real-time, detailed feedback that enhances control and sensitivity in complex procedures. Kinesthetic feedback allows surgeons to feel the forces on the surgical tool, while tactile feedback conveys information about gripping forces and tissue textures.

About the Research

In this paper, the authors presented a novel robotic endotrainer that integrates kinesthetic and tactile feedback to address the importance of haptic feedback in robotic surgery. This development aims to overcome the limitations of existing surgical robots by providing surgeons with a more realistic and immersive training experience.

The robotic endotrainer mimics the design and function of the widely used da Vinci Si surgical robot. It features two master arms on the surgeon’s side, each with seven degrees of freedom (DOF) to replicate the range of motion of the human arm.

The slave side consists of two manipulators and a camera arm, each equipped with precise control mechanisms to mimic the movements dictated by the master arms. This architecture ensures real-time feedback and control, with the surgeon's actions being precisely recorded and mirrored by the slave manipulators.

The system includes a force/torque (F/T) sensor developed using optoelectronic technology. This sensor, designed with three springs and three photo sensors, measures the deflections of the springs, which correlate directly with the forces and moments applied to surgical tools, achieving 95% accuracy. This setup delivers kinesthetic feedback, allowing surgeons to feel the forces acting on their instruments.

Additionally, a tactile feedback mechanism informs the surgeon about the gripping forces between the tool's tip and the tissue. This system employs a commercially available force sensor at the tooltip to measure these forces, which are then converted into vibrations.

These vibrations, transmitted through motors integrated into the master arm's finger clutch, vary in intensity with the gripping force, providing clear feedback to the surgeon.

Research Findings

The integrated haptic feedback system demonstrated remarkable effectiveness and potential in improving robotic surgery training. A key component, the F/T sensor, achieved high accuracy by measuring forces along three axes and torques around two axes, offering comprehensive feedback to surgeons. Additionally, its compact and innovative design also facilitated easy integration with various surgical tools.

The tactile feedback system provided crucial information during procedures to minimize the risk of tissue damage. This feedback is essential for maintaining the integrity of delicate tissues and preventing the application of excessive force.

Additionally, the combination of these feedback systems significantly enhanced the realism and effectiveness of surgical simulations. Surgeons reported a marked improvement in their ability to perceive and control forces during these simulations, which translates into better precision and safety in real-world surgeries.

Furthermore, the system's cost-effectiveness makes it accessible to a wide range of training programs. This affordability could democratize access to high-quality robotic surgery training, expanding opportunities for surgeons to refine their skills using advanced technology.


The novel haptic system has significant implications for robotic surgery and surgical training. It enhances training programs by offering more realistic and effective simulations, which is particularly beneficial for teaching complex procedures where tactile feedback is crucial for safety and precision.

In clinical practice, the system improves control of surgical tools, reduces error risks, and increases patient safety by providing surgeons with real-time force and tactile feedback.

Additionally, the developed F/T sensor has potential applications beyond surgery. With minor design modifications, this sensor can be adapted for industrial robots, paving the way for its use in fields that require precise force measurement and feedback.


In summary, the novel haptic system proved valuable for revolutionizing the field of robotic surgery. This technology could enable more effective training for surgeons, preparing them to perform complex procedures with greater precision.

Moving forward, researchers recommended refining the feedback mechanisms and exploring the system's applications across various surgeries.

Journal Reference

Nair, B, R., et, al. Advancing Robotic Surgery: Affordable Kinesthetic and Tactile Feedback Solutions for Endotrainers. arXiv, 2024, 2406.18229. doi: 10.48550/arXiv.2406.18229,

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.


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