Dynamic Haptic Feedback for Robotic Surgery Nerve Protection
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Solution Overview
Problem
Current surgical systems face challenges in accurately preventing damage to nervous tissue during bone drilling or resection procedures, as they may inaccurately define haptic boundaries or improperly register patient anatomy, leading to potential injury from spinal cord or nerve interactions.
Innovation Solution
A computer-implemented method and system that uses a neural monitor to detect the distance between a surgical tool and nervous tissue, dynamically altering the robotic arm's resistance to movement based on received signals, providing haptic feedback to prevent unwanted interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed haptic boundaries are used to constrain surgical tool movement, then surgeon safety is improved, but accuracy is worsened due to improper boundary definition or registration errors
Solution Approach 1:
The haptic boundary is transformed from a fixed static constraint to a dynamic adaptive constraint that adjusts in real-time based on neural monitor feedback. The robotic arm's haptic resistance changes dynamically according to the detected proximity of nervous tissue, allowing the boundary to adapt to actual anatomical conditions rather than relying on pre-defined virtual boundaries that may be inaccurate due to registration errors.
Solution Approach 2:
A closed-loop feedback system is implemented where the neural monitor continuously detects EMG signals indicating proximity to nervous tissue, and this information feeds back to dynamically adjust the haptic boundary constraints. The system uses real-time neural monitoring feedback to modify haptic resistance, creating an adaptive safety mechanism that responds to actual physiological conditions rather than static pre-planned boundaries.
2Object-affected harmful factors
If power to cutting tool is disabled based on distance threshold, then nerve damage is prevented, but surgical quality deteriorates due to continuous toggling between enabled and disabled states
Solution Approach 1:
Instead of a binary on/off power control based on fixed distance thresholds, the system implements dynamic haptic resistance that continuously adjusts based on real-time neural monitor feedback. The robotic arm provides variable resistance that increases as the tool approaches nervous tissue, creating a gradual protective effect rather than abrupt power disconnection that disrupts surgical flow and quality.
Solution Approach 2:
The haptic feedback system acts as an intermediary between the neural monitor detection and the cutting tool power control. Rather than directly disabling power when a threshold is reached, the system uses haptic resistance as a mediating mechanism that provides progressive warning and constraint, allowing the surgeon to maintain control and surgical quality while still preventing nerve damage through tactile feedback.
3Reliability
If haptic boundaries are expanded to ensure safety margin, then nerve protection is improved, but surgical precision is worsened due to overly restrictive constraints
Solution Approach 1:
The haptic boundary constraint is made dynamic rather than static, adjusting in real-time based on actual neural proximity detection. This allows the system to provide strong protective constraints when needed (when nervous tissue is detected) while maintaining full surgical maneuverability when the tool is in safe zones, eliminating the need for permanently expanded safety margins that would restrict all movements.
Solution Approach 2:
The haptic resistance is applied locally and selectively based on real-time neural monitoring rather than globally across all movements. The system provides increased resistance only in specific directions or positions where nervous tissue proximity is detected, while allowing free movement in safe zones, thus maintaining surgical precision and maneuverability without compromising nerve protection.
Data Source
AI summary
A computer-assisted surgery system may have a robotic arm including a surgical tool and a processor communicatively connected to the robotic arm. The processor may be configured to receive, from a neural monitor, a signal indicative of a distance between the surgical tool and a portion of a patient's anatomy including nervous tissue. The processor may be further configured to generate a command for altering a degree to which the robotic arm resists movement based on the signal received from the neural monitor; and send the command to the robotic arm.