Gaussian Fitting for Real-Time TOF Mass Spectrometry Signals
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Solution Overview
Problem
Conventional methods for processing signals in time-of-flight (TOF) mass spectrometry are costly, cumbersome, and inefficient, often producing imprecise and unreliable results due to complexity and slow processing speeds.
Innovation Solution
A system and method for real-time processing of digitized signals using Gaussian fitting, which involves curve fitting to construct a Gaussian function that accurately fits the data points from ions detection in TOF mass spectrometry, enabling precise measurement of ions' time of arrival and signal intensity, and allowing for efficient processing of significant ion rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used for processing TOF mass spectrometry signals, then implementation is possible with existing systems, but processing speed is slow and results are imprecise
Solution Approach 1:
The patent applies Gaussian fitting as a mathematical transformation to change the processing parameters of the signal data. By fitting the detected ion signals to a Gaussian function model, the system extracts precise parameters (amplitude, mean, standard deviation) that directly correspond to ion characteristics, achieving both high precision measurement and efficient real-time processing
Solution Approach 2:
The patent replaces complex conventional signal processing algorithms with a streamlined Gaussian fitting approach. This substitution simplifies the processing mechanism while maintaining or improving measurement precision, enabling real-time analysis of high ion rates without the computational burden of traditional methods
2Productivity
If conventional processing methods are used, then system complexity is manageable, but processing efficiency and reliability are poor
Solution Approach 1:
The patent transforms the signal processing task into a parameter estimation problem by fitting Gaussian function parameters (amplitude, mean, standard deviation) to the detected signals. This parameter-based approach simplifies the processing pipeline and enables real-time computation while maintaining measurement accuracy
Solution Approach 2:
The Gaussian fitting algorithm automatically processes each detected signal independently, extracting all necessary information (ion arrival time, intensity, duration) in a single operation. This self-contained processing approach eliminates the need for multiple sequential processing steps, improving efficiency while keeping the system relatively simple
3Reliability
If conventional methods are used, then implementation is straightforward, but results are unreliable and imprecise
Solution Approach 1:
The patent uses Gaussian fitting to transform raw signal data into reliable parameter estimates (amplitude, mean, standard deviation). This mathematical transformation provides a robust framework for extracting accurate ion measurement data, significantly improving result reliability compared to conventional processing methods
Solution Approach 2:
The Gaussian fitting process provides built-in validation through parameter consistency checks. The fitted parameters must satisfy mathematical constraints and physical expectations, providing automatic feedback that ensures measurement reliability and allows for quality control of the processed data
Data Source
AI summary
Systems and methods are provided for processing in real-time and using Gaussian fitting digitized signals from ions detection in time-of-flight (TOP) mass spectrometry. Acquisition/analog-to-digital conversion may be applied in the course of Ion detection during time-of-flight (TOP) mass spectrometry, with the acquisition/analog-to-digital conversion including generating, in response to detection of ions, one or more time-of-flight (TOP) based signals, and digitizing, using analog-to-digital conversion, the one or more TOP based signals, to generate corresponding digitized data. The digitized data may then be processed, in real-time and based on use of Gaussian fitting, to generate result data corresponding to the time-of-flight (TOP) mass spectrometry. The Gaussian fitting may comprise applying second (2nd) degree polynomial fit, such as by least squares via QR factorization.