Challenges in laparoscopic surgery can impact cost, utilization, effectiveness, and outcomes of the procedure. For instance, the inability of the surgeon to control vision can create efficiency and safety challenges. Quick movement or unsteady control of the camera can cause fogging, which requires a pause in the procedure for cleaning. Moreover, the limitations of traditional laparoscopy impact clinical intelligence, which is defined as point-of-care knowledge that allows a surgeon to make more informed decisions that may drive improved outcomes and procedural efficiency. Now, a first of its kind digital laparoscopic platform aims to eliminate the challenges and limitations of traditional laparoscopy by leveraging augmented intelligence to provide unmatched performance and patient outcomes through machine learning.

The Senhance Surgical System from Asensus Surgical, Inc. (Durham, NC, USA) is the first and only digital laparoscopic platform designed to support hospitals and surgeons by providing greater control in laparoscopy, reduce variability and increase OR efficiency. With the addition of machine vision, augmented intelligence, and deep learning capabilities throughout the surgical experience, Senhance aims to holistically address the current clinical, cognitive and economic shortcomings that drive surgical outcomes and value-based healthcare.

Senhance goes beyond the typical surgical robotic systems, providing surgical assurance through haptic feedback, eye-tracking camera control, and 3D visualization, and is the first platform to offer 3mm instruments (the smallest instrument available in the world on a robotic surgical platform). The Senhance Surgical System is powered by the Intelligent Surgical Unit (ISU). The ISU enables machine vision-driven tools to gather data related to anatomical structures and control of the camera for a surgeon by responding to commands and recognizing certain objects and locations in the surgical field and allows a surgeon to change the visualized field of view using the movement of their instruments.

Asensus intends to unlock clinical intelligence and capabilities to reduce surgical variability and the complications associated with it by adding machine vision, augmented intelligence, and deep learning capabilities that will be built upon the digital library of data collected from surgeries performed using Senhance. The insights gained from these cases will help deliver on the promise of consistently superior surgery regardless of a surgeon’s experience or skill level by guiding improved decision making, enriching collaboration, and enhancing predictability. 

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