Motion Error Characterization in Flow Cytometry Streams

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

In flow cytometry, high-accuracy and high-speed systems face significant uncertainties in predicting the arrival times and locations of micro-entities due to unaccounted higher-order motion characteristics, limiting their operational speed, accuracy, and performance.

Innovation Solution

A method and apparatus for characterizing motion-related errors in flow cytometers by measuring deviations in arrival times and locations of micro-entities, using periodic energy sources and optical probing to create a model that compensates for these errors, thereby improving measurement accuracy and system performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If average stream velocity is used to predict arrival time or location of micro-entities, then the prediction method is simple and fast, but the prediction accuracy deteriorates due to unaccounted higher-order motion characteristics

Engineering Contradiction:

Improveprediction speedVSAvoidarrival time prediction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs preliminary characterization of motion-related errors by measuring deviations in arrival times and locations of micro-entities before using this information for compensation. A model of the error characteristics is built in advance based on measured data, allowing the system to account for higher-order motion characteristics without performing complex real-time calculations during prediction.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system measures actual arrival times and locations of micro-entities, compares them with predicted values based on average velocity, and uses the measured deviations to build an error compensation model. This feedback loop allows the system to continuously improve prediction accuracy by incorporating real motion characteristics into the prediction algorithm.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If higher-order motion characteristics are accounted for to improve prediction accuracy, then measurement precision improves, but device complexity and computational requirements increase

Engineering Contradiction:

Improvearrival time prediction accuracyVSAvoiderror characterization system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

Instead of directly implementing complex physical models of higher-order motion characteristics, the system creates a simplified computational model that copies the essential error patterns from measured data. The error characteristics are characterized through measurement and represented in a simplified form that can be easily applied for compensation without requiring complex real-time calculations.

Inventive Principle:

Principle #26Copying

3Measurement precision

If higher-order motion characteristics are accounted for to improve prediction accuracy, then measurement precision improves, but loss of time increases due to additional measurement and characterization steps

Engineering Contradiction:

Improvearrival time prediction accuracyVSAvoiderror characterization time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The error characterization and model building are performed as preliminary actions before the actual measurement and prediction tasks. By characterizing motion-related errors in advance and storing the error model, the system avoids time-consuming error analysis during critical measurement operations, thus minimizing time loss while maintaining high prediction accuracy.

Inventive Principle:

Principle #10Preliminary action

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 characterization and compensation of motion-related errors enhance the precision of micro-entity tracking and sorting in flow cytometers, leading to improved throughput and purity of cell sorting, even at higher speeds.

Implementation Method 1

a source of periodic energy configured to couple the periodic energy to the stream of moving micro-entities

Methodology Applied

Scientific EffectPeriodic energy coupling:

Implementation Method 2

using periodic energy sources and optical probing to create a model that compensates for these errors

Methodology Applied

Scientific EffectOptical detection:

Data Source

PatentEP2724144B1Characterization of motion-related error in a stream of moving micro-entities

Publication Date: 2018.04.11 SONY GROUP CORP

Figure 1
Figure 2
Figure 3A~3G

AI summary

Apparatus and methods for detecting and characterizing motion-related error of moving micro-entities are described. Motion-related error may occur in streams of moving micro-entities, and may represent a deviation in and expected arrival time or an uncertainty in position of a micro-entity. Motion-related error of micro-entities is observed in a flow cytometer, e.g., as pulse jitter, and is found to have a functional dependence on a parameter related to a system clock. The motion-related error may be characterized by correlating measurements of micro-entities moving within a fluid stream.