Medical ventilator capable of early detecting and recognizing types of pneumonia, gas recognition chip, and method for recognizing gas thereof
First Claim
1. A gas recognition chip, comprising:
- a sensor array, including a plurality of sensors and a plurality of sensing films applied on the sensors correspondingly, and each of the sensing films being provided with selectivity to adsorb plural types of gases, and each of the sensors being provided to produce an odor signal corresponding to each of the respective gases adsorbed by the sensing film;
a sensor interface circuit, for reading and analyzing the odor signal of each of the gases to generate a gas pattern signal corresponding to each of the respective gases;
a stochastic neural network chip, for amplifying the difference between the gas pattern signals and reducing the dimensions of each gas pattern signal to produce an analysis result;
a memory, for storing gas training data; and
a microcontroller, for receiving the analysis result, and executing a mixed gas recognizing algorithm according to the analysis result to recognize the type of the gas, and classify an unknown gas not existed in the gas training data, and producing a recognition result according to the gas training data,wherein the microcontroller transmits data of the unknown gas to the stochastic neural network chip and the memory when the microcontroller detects the unknown gas, so that the gas recognition chip has a self learning ability,wherein the mixed gas recognizing algorithm includes a K nearest neighbor (KNN) algorithm, a linear least squares regression algorithm and a median-threshold K nearest neighbor (MTKNN) classification algorithm, and the median-threshold K nearest neighbor classification algorithm is used to find a distance between every two data in the gas training data first, and then find a median of the distances to determine whether the gas is the unknown gas.
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Accused Products
Abstract
A medical ventilator capable of early detecting and recognizing types of pneumonia, a gas recognition chip, and a method for recognizing gas thereof are disclosed. The gas recognition chip of the medical ventilator comprises a sensor array, a sensor interface circuit, a stochastic neural network chip, a memory and a microcontroller. The sensor array receives a plurality of multiple types of gases to produce odor signals corresponding to each type of gas. The sensor interface circuit analyzes the odor signals to produce gas pattern signals corresponding to each type of gas. The stochastic neural network chip amplifies the differences between the gas pattern signals and performs dimensional reduction on the gas pattern signals to aid the analysis. The memory stores training data. The microcontroller performs a mixed gas recognizing algorithm to early detect and recognize the type of the pneumonia according to the gas training data.
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Citations
14 Claims
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1. A gas recognition chip, comprising:
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a sensor array, including a plurality of sensors and a plurality of sensing films applied on the sensors correspondingly, and each of the sensing films being provided with selectivity to adsorb plural types of gases, and each of the sensors being provided to produce an odor signal corresponding to each of the respective gases adsorbed by the sensing film; a sensor interface circuit, for reading and analyzing the odor signal of each of the gases to generate a gas pattern signal corresponding to each of the respective gases; a stochastic neural network chip, for amplifying the difference between the gas pattern signals and reducing the dimensions of each gas pattern signal to produce an analysis result; a memory, for storing gas training data; and a microcontroller, for receiving the analysis result, and executing a mixed gas recognizing algorithm according to the analysis result to recognize the type of the gas, and classify an unknown gas not existed in the gas training data, and producing a recognition result according to the gas training data, wherein the microcontroller transmits data of the unknown gas to the stochastic neural network chip and the memory when the microcontroller detects the unknown gas, so that the gas recognition chip has a self learning ability, wherein the mixed gas recognizing algorithm includes a K nearest neighbor (KNN) algorithm, a linear least squares regression algorithm and a median-threshold K nearest neighbor (MTKNN) classification algorithm, and the median-threshold K nearest neighbor classification algorithm is used to find a distance between every two data in the gas training data first, and then find a median of the distances to determine whether the gas is the unknown gas. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for recognizing gas, comprising the steps of:
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providing a sensor array, including a plurality of sensors and a plurality of sensing films applied on the sensors correspondingly; using each of the sensing films with selectivity to adsorb plural types of gases, and using each of the sensors to generate an odor signal corresponding to each of the respective gases adsorbed by the sensing film; using a sensor interface circuit to read and analyze the odor signal of each of the gases to generate a gas pattern signal corresponding to each of the respective gases; using a stochastic neural network chip to amplify the difference between the gas pattern signals and reduce the dimensions of each of the gas pattern signals to produce an analysis result; storing gas training data in a memory; and using a microcontroller to receive the analysis result, and execute a mixed gas recognizing algorithm to identify the type of the gas according to the analysis result, and classify an unknown gas not existing in the gas training data, and then produce a recognition result according to the gas training data, wherein when the unknown gas is detected, the data of the unknown gas is transmitted to the stochastic neural network chip and the memory by the microcontroller, so that the gas recognition chip has a self-learning ability, wherein the mixed gas recognizing algorithm includes a K nearest neighbor algorithm, a linear least squares regression algorithm and a median-threshold K nearest neighbor classification algorithm, wherein the median-threshold K nearest neighbor classification algorithm is used to find a distance between every two data in the gas training data, and then find a median of the distances, and the median is used to determine whether the gas is the unknown gas. - View Dependent Claims (10, 11, 12, 13, 14)
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Specification