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Real-time acquisition and analysis method based on parallel fractional physiological signals

A technology of physiological signals and analysis methods, applied in the field of real-time acquisition and analysis of physiological signals based on parallel fractional orders, can solve problems such as unsupported airborne capabilities and precision problems, and achieve easy software and hardware implementation, high precision, and simple logical structure Effect

Active Publication Date: 2018-12-07
NANJING LONGYUAN MICROELECTRONICS TECH CO LTD +3
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide a method based on parallel fractional-order physiological signal real-time acquisition and analysis to solve the problem of the accuracy of traditional physiological signal analysis methods and the problem that the airborne capabilities of mobile intelligent terminal equipment cannot support real-time signal analysis constraints

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  • Real-time acquisition and analysis method based on parallel fractional physiological signals
  • Real-time acquisition and analysis method based on parallel fractional physiological signals
  • Real-time acquisition and analysis method based on parallel fractional physiological signals

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Embodiment 1

[0052] Such as figure 2 As shown, the processing steps based on the parallel fractional-order physiological signal real-time acquisition and analysis method are divided into the following four processes: data acquisition, data transmission, parallel fractional-order physiological signal analysis, and data presentation.

[0053] Step 1: If image 3 As shown, the physiological signal is collected from the sensor,

[0054] Step 1a: After the mobile terminal is started, register its supported sensors and communication protocols into the virtual table, which includes device type, communication protocol, communication parameters, communication method, and format information.

[0055] Step 1b: Determine whether the sensor data is readable. If readable, identify the communication protocol and sensor type based on the connection information and call the virtual table registration method to obtain physiological signal data. If not, continue to judge whether the sensor is readable afte...

Embodiment 2

[0083] This embodiment provides a real-time collection and analysis of ECG signals based on fractional order parallel distribution. ECG signal is an important physiological signal, which can be used as an important indicator to reflect people's physiological and psychological state. It is often used in heart disease diagnosis, stress test, dehydration state and sleep state assessment. In this embodiment, the mobile terminal adopts a customized terminal device based on the Android platform, and uses the Apache Flink big data computing framework to build a Map / Reduce cluster. The parallel distributed fractional-order ECG analysis process is as follows:

[0084] Step 1: The Android smart terminal reads the ECG signal and stores the data in the local database SQLite3.

[0085] Step 2: Realize the remote call through Java and Resting technology, and submit the ECG data to the remote server from the HTTP protocol.

[0086] Step 3: The remote server is composed of elastic computing...

Embodiment 3

[0091] The present embodiment provides a real-time acquisition and analysis of skin electrical signals based on fractional order parallel distribution. Electrodermal signal, also known as "skin galvanic response" and "skin galvanic properties", represents changes in skin conduction when the body is stimulated, and can be used as an indirect indicator of brain arousal, alertness, and tension.

[0092] In this embodiment, a foot skin electrosensory sensor is configured in the car, and a vehicle-mounted tablet computer is used to collect data. The tablet computer is equipped with a 4G network card to communicate with a remote server, and is connected to the skin electrosensory sensor via Bluetooth.

[0093] The tablet is based on the Android platform and uses the Apache Flink big data computing framework to build a Map / Reduce cluster. The parallel distributed fractional-order skin electrophoresis analysis process is as follows:

[0094] Step 1: The tablet connects the skin elect...

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Abstract

The invention relates to a real-time acquisition and analysis method based on parallel fractional physiological signals and belongs to application of artificial intelligence and the information technology in the medical field. The method is characterized in that physiological sensor data is read through an abstraction layer; the physiological signal data is transmitted to a server through a remoteinterface; the physiological signal is analyzed through a fractional index, firstly, the uploaded physiological signal and historical data are synthesized into a physiological signal data sequence, the sequence and different fractional orders are used as input parameters and transmitted to N Map terminals, stability and variance of the corresponding order differential sequence are calculated by each Map end, the result is transmitted to a Reduce end, and the fractional physiological signal index is calculated by the Reduce end and returned to a client; if the index is not within the normal range, the alarm information is emitted by the client to a user. The method is advantaged in that the method is simple, safe and efficient and can be widely applied to the intelligent health service, intelligent nursing and man-machine interaction fields.

Description

technical field [0001] The invention relates to the application of the field of artificial intelligence in intelligent health monitoring, in particular to a method for real-time collection and analysis of physiological signals based on parallel fractional orders. Background technique [0002] With the development of a new generation of information technology, smart terminal devices and wearable medical sensing devices are becoming more and more popular. Through this kind of equipment, it is possible to read people's physiological signals conveniently and analyze them in time. Real-time analysis of people's physiological signals is an important basis for applications in the fields of smart health, smart elderly care, and smart driving, and has great application value and a wide range of applications. [0003] Traditional physiological signal analysis mainly adopts time-domain analysis, frequency-domain analysis, and the combination of time-domain and frequency-domain analysi...

Claims

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Application Information

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IPC IPC(8): G16H50/70G16H40/67G16H40/60A61B5/0488A61B5/0402
CPCG16H40/60G16H40/67G16H50/70A61B5/318A61B5/389Y02D30/70
Inventor 吕太之陈勇张军冯茂岩徐钊毛宇鹏
Owner NANJING LONGYUAN MICROELECTRONICS TECH CO LTD
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