Laser Speckle Signal Processing for Real-Time Surgical Motion Filtering
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Solution Overview
Problem
Conventional laser speckle imaging systems are computationally intensive and struggle with accurately distinguishing between biological and external movements, leading to false positives and negatives, and fail to detect critical structures in real-time surgical scenarios.
Innovation Solution
The method processes laser speckle signals over an infinite number of frames, using function spaces and reference signals to differentiate between biological and external movements, and generates output signals to aid surgical procedures by determining tool-tissue contact and force exertion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems analyze laser speckle signals over a finite number of frames, then computational overhead is reduced, but measurement precision and accuracy deteriorate due to inability to distinguish biological from external movements
Solution Approach 1:
The system performs preliminary classification of movement types by comparing laser speckle signals against reference signals corresponding to known biological movements (heartbeat, respiration) before full analysis. This preliminary action filters out false positives from external movements, improving measurement precision without requiring exhaustive analysis of all frames.
Solution Approach 2:
The invention extracts and separates biological movement signals from external movement signals by comparing laser speckle patterns against reference signals. By taking out only the relevant biological movement components and filtering out external disturbances, the system achieves high measurement precision with reduced computational overhead compared to analyzing all signals equally.
2Measurement precision
If laser speckle imaging processes signals to detect critical structures, then measurement precision improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system introduces reference signals as intermediaries that represent known biological movement patterns (heartbeat, respiration). These reference signals mediate between the raw laser speckle data and the detection of critical structures, enabling enhanced measurement precision through comparison and correlation analysis without requiring complex processing architectures.
Solution Approach 2:
The laser speckle imaging system performs multiple functions using the same processing pipeline: it distinguishes biological from external movements, detects critical structures, and provides real-time feedback for surgical guidance. This multi-functionality achieves high measurement precision without proportionally increasing device complexity, as a single processing framework handles multiple detection tasks.
3Reliability
If the system filters false positives by comparing signals to reference signals, then reliability improves, but device complexity increases due to additional comparison mechanisms
Solution Approach 1:
The system uses feedback mechanisms where reference signals representing known biological movements are continuously compared against incoming laser speckle signals. The comparison results feed back into the processing pipeline to confirm or reject detected movements, improving reliability by reducing false positives. This feedback-based verification adds minimal complexity compared to exhaustive analysis methods.
Solution Approach 2:
Reference signals serve as intermediaries that mediate between raw laser speckle data and final movement detection. By introducing these reference signals as a intermediate comparison layer, the system reliably filters false positives from external movements while maintaining manageable device complexity through straightforward correlation and comparison operations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces computational overhead and enhances the accuracy of laser speckle imaging by filtering false positives, detecting critical structures, and providing real-time data for surgical tools and tissue interaction.
Implementation Method 1
at least one laser light source that is directed towards a tissue region of a subject
Implementation Method 2
laser light to illuminate a diffuse surface to produce a visual effect known as a speckle pattern
Data Source
AI summary
The present disclosure provides systems and methods for processing laser speckle signals. The method may comprise obtaining a laser speckle signal from a laser speckle pattern generated using at least one laser light source that is directed towards a tissue region of a subject and a reference signal corresponding to a movement of a biological material of or within the subject's body. The method may comprise computing one or more measurements using a first function corresponding to at least the laser speckle signal and a second function corresponding to the reference signal. The method may comprise generating an output signal in part based on the one or more measurements for the function space and using the output signal to aid a surgical procedure on or near the tissue region of the subject.