Autonomous ICSI Platform Using AI Imaging and Robotic Egg Handling
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Solution Overview
Problem
Traditional in vitro fertilization (IVF) technologies rely heavily on human clinical embryologists and andrologists, leading to high costs, geographic limitations, and inconsistencies due to human performance, limiting access and efficiency.
Innovation Solution
An intelligent, automated IVF system using robotic modules, imaging, and AI/ML for tasks such as zona pellucida detection, sperm injection, and semen preparation, reducing human intervention and enhancing precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human clinical embryologists and andrologists perform IVF procedures manually, then the procedures can be performed with human judgment and adaptability, but the costs are high, access is limited, and there are inconsistencies due to human performance variability
Solution Approach 1:
The system enables autonomous ICSI procedures where the robotic platform independently performs zona pellucida detection, needle positioning, membrane piercing, and sperm injection without continuous human intervention. The AI algorithms automatically analyze imaging data, make decisions about procedural steps, and control robotic actuators to complete the entire ICSI process autonomously, eliminating human performance variability while maintaining high reliability through consistent automated execution
Solution Approach 2:
The patent replaces manual mechanical operations by human embryologists with an automated robotic system that uses computer vision for detection, AI algorithms for decision-making, and robotic actuators for precise physical manipulation. The robotic platform substitutes human hands and eyes with automated imaging systems and controlled mechanical arms, achieving consistent results through programmable precision rather than human skill variation
2Productivity
If automated robotic systems are used for ICSI procedures, then costs are reduced and access is improved, but the device complexity increases significantly
Solution Approach 1:
The robotic platform integrates multiple functions into a single unified system: the same robotic arm performs both egg manipulation and sperm injection, the imaging system serves both for zona detection and membrane visualization, and the AI algorithms handle both navigation and procedural control. This multi-functionality reduces the need for separate specialized devices while maintaining high productivity through coordinated automated operations
Solution Approach 2:
The patent introduces AI algorithms as an intermediary layer between the robotic hardware and the procedural tasks. The AI serves as a mediator that processes imaging data, makes autonomous decisions about procedural steps, and translates high-level instructions into precise robotic movements. This intermediary simplifies the control architecture by centralizing intelligence in the software layer rather than requiring complex hardwired control circuits
3Manufacturing precision
If manual ICSI procedures are performed by human operators, then the equipment required is simpler, but human error and variability affect the precision and outcomes
Solution Approach 1:
The system creates a digital copy of the egg and surrounding structures through high-resolution imaging and AI-based 3D reconstruction. This virtual model allows the system to plan the injection path, determine optimal piercing points, and simulate procedural outcomes before executing the actual ICSI. The digital twin enables precise positioning and navigation without requiring complex real-time sensing and adjustment mechanisms during the procedure
4Ease of operation
If traditional manual IVF methods are used, then the system is easier to operate, but geographic and economic limitations restrict access to IVF treatment
Solution Approach 1:
The robotic system performs all complex ICSI operations autonomously without requiring skilled human operators to be physically present during the procedure. The platform independently executes zona detection, needle positioning, membrane piercing, and sperm injection based on AI-driven decision-making. This autonomy makes the system easy to operate from a remote location while delivering precision comparable to or exceeding manual expert performance
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
The system minimizes costs, improves access, and ensures consistent, efficient IVF processes by automating complex tasks like ICSI and semen preparation, reducing human error and variability.
Implementation Method 1
The AI/ML system and imaging system may be used to assess a thickness of the zona and determine an ablation action, may generate a laser to ablate a pre-designated section and depth of the zona pellucida
Implementation Method 2
breaking the egg membrane (oolemma) using a piezoelectric pulse
Data Source
AI summary
A method for automated ICSI includes receiving at least one droplet containing an egg in a dish placed on a stage. The method includes using an artificial intelligence/machine learning system (AI/ML system) and an imaging system to detect a zona pellucida. The imaging system includes a microscopy system, a camera system, and a lighting system. The method includes holding the egg using a robotic microtool and lowering a robotic pipettor into the droplet. The method includes using the AI/ML system and imaging system to determine an area at which to hold the egg and positioning the robotic microtool to that area. The method includes using the AI/ML system and imaging system to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor. The method includes using the AI/ML system and imaging system to determine a target location where zona ablation should be performed.