WO2017063598A1 - 采集光信息的云端处理方法 - Google Patents

采集光信息的云端处理方法 Download PDF

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Publication number
WO2017063598A1
WO2017063598A1 PCT/CN2016/102229 CN2016102229W WO2017063598A1 WO 2017063598 A1 WO2017063598 A1 WO 2017063598A1 CN 2016102229 W CN2016102229 W CN 2016102229W WO 2017063598 A1 WO2017063598 A1 WO 2017063598A1
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value
sensor
data
information
batch
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PCT/CN2016/102229
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English (en)
French (fr)
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吴凡
叶欢
吴湜溪
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吴凡
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

Definitions

  • the present invention relates to the field of medical treatment and health, and in particular to a cloud processing method for collecting optical information.
  • the current health tests are mainly divided into two types, one is directly checked by a doctor; the other is analyzed by equipment inspection, and there are two ways to analyze, one is for doctors to analyze, and the other is for intelligent device analysis; For the last method, there are the following problems: 1. The information collected by the user at any time and place has a large error; 2. The error caused by the sensor error is large; these errors will affect the detection.
  • the present invention is implemented as follows: a cloud processing method for collecting optical information, comprising the following steps:
  • the sensor response information before and after the user received by the terminal is placed into the test object is divided into calibration data and test data, and the sensor information is used for identification;
  • the calibration data is compared with the laboratory data of the batch of sensors stored in the server, and a correction coefficient is obtained;
  • the laboratory data of the batch sensor in the server is compared with the color correction value or the grayscale correction value, and the final test result is obtained and archived and sent to the client.
  • a further technical solution of the present invention is: for the sensor response information is greatly affected by temperature,
  • the information received by the terminal should also include the temperature value used by the user;
  • step F the color correction value or the grayscale correction value and the laboratory data of the batch sensor in the server corresponding to the temperature range. The comparison is made and the final test results are archived and sent to the client.
  • the invention has the beneficial effects that: by adopting the above technical solution, the cloud processing for collecting optical information is more accurate through sensor error processing and multiple test error processing.
  • the test data of the optical information is directly compared with the theoretical value, and since the conditions of many conditions and theoretical values are different when the test data is used, the error is large, and the innovation of the present invention is The first is to use the cloud test value as a comparison object.
  • the cloud processing method for collecting optical information is characterized in that: the following steps are included:
  • the sensor response information before and after the user received by the terminal is placed into the test object is divided into calibration data and test data, and the sensor information is used for identification.
  • the calibration data is used for calibration of sensor errors; the sensor information is used to identify information such as the specific model, manufacturer, batch number, expiration date, etc., in order to interface and compare with the laboratory data described in step A.
  • the average value calculation may be calculated by using the patient's information processing device and then sent to the terminal, or the patient directly sends the collected information to the terminal, and the terminal calculates the average value.
  • the average RBG value refers to the average value of each color pixel point in the test data
  • the mixed color value refers to the value obtained by performing a weighted average algorithm for each color.
  • the calibration data is compared with the laboratory data of the batch of sensors stored in the server, and the correction coefficient is obtained.
  • the laboratory data of the batch sensor in the server is compared with the color correction value or the grayscale correction value, and the final test result is obtained and archived and sent to the customer. Account.
  • step B the information received by the terminal should also include the temperature value when the user uses it; in step F, the color correction value or the grayscale correction value and the batch in the server.
  • step F the color correction value or the grayscale correction value and the batch in the server.
  • the cloud processing of collecting optical information is more accurate.

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

一种采集光信息的云端处理方法，通过缜密的运算方式和步骤，对检测设备、即传感器进行误差处理，对采集的光信息进行误差处理，使得对采集光信息的云端处理更为准确。

Description

采集光信息的云端处理方法 【技术领域】
本发明涉及医疗、健康领域，尤其涉及一种采集光信息的云端处理方法。
【背景技术】
目前的健康检测主要分为两种，一种靠医生直接检查；另一种是靠设备检查后分析，分析又有两种方式，一种是交给医生分析，另一种是智能设备分析；对于最后一种方法存在如下问题：1、用户随时随地采集的信息存在误差较大；2、传感器误差形成的误差较大；这些误差将对检测造成影响。
【发明内容】
本发明的目的在于提供一种减小误差的针对采集光信息的云端处理方法，旨在解决光信息误差问题。
本发明是这样实现的：一种采集光信息的云端处理方法，包含如下步骤：
A、将生产的每批次传感器取样拿到实验室进行试验，得出标准的实验室数据储存在服务器中；
B、将终端收到的用户放入检测物前后的传感器反应信息分为校准数据和测试数据，连同传感器信息进行识别；
C、计算出测试数据的平均RBG值或者平均灰度值，对平均RBG值用加权平均算法进行计算，得到一个混色值；
D、校准数据与储存在服务器的该批次传感器的实验室数据进行比对，得到校正系数；
E、将混色值或者平均灰度值与校正系数相乘得到混色修正值或者灰度修正值；
F、按传感器信息查找到该批次传感器在服务器中的实验室数据与混色修正值或者灰度修正值进行比对，得到最终测试结果进行存档并发送到客户端。
本发明的进一步技术方案是：对于传感器反应信息受温度影响较大的， 步骤B中，终端收到的信息中，还应包含有用户使用时的温度值；步骤F中，混色修正值或者灰度修正值与服务器中该批次传感器在对应温度段下的实验室数据进行比对，得到最终测试结果进行存档并发送到客户端。
本发明的有益效果是：由于采用上述技术方案，通过传感器误差处理、多次测试误差处理，使得对采集光信息的云端处理更为准确。
【具体实施方式】
现有技术中，光信息的测试数据都是直接与理论值进行比对得出结果，由于测试数据时很多条件和理论值的条件是不一样的，所以误差就很大，本发明的创新之一就是利用云端试验值作为对比对象。具体为，一种采集光信息的云端处理方法，其特征在于：包含如下步骤：
A、将生产的每批次传感器取样拿到实验室进行试验，得出标准的实验室数据储存在服务器中；不同批次的传感器做的试验数据不同，避免了现有技术中直接拿用户端发来的传感器信息与理论值进行对比，存在的传感器批次误差。
B、将终端收到的用户放入检测物前后的传感器反应信息分为校准数据和测试数据，连同传感器信息进行识别。所述校准数据用于传感器误差的校正；所述传感器信息用于识别传感器具体型号、生产厂家、批号、有效期等信息，以便于和步骤A所述的实验室数据进行对接和比对。
C、计算出测试数据的平均RBG值或者平均灰度值，对平均RBG值用加权平均算法进行计算，得到一个混色值；用户端与服务器端的数据传输可以在提取平均值前或之后，也就是说平均值计算可以是利用患者的信息处理设备计算出来后再发送给终端，或者患者直接将采集到的信息发送给终端、由终端来计算平均值。平均RBG值指的是测试数据中各色像素点的平均值，混色值指的是对各色进行加权平均算法后得出的值。
D、校准数据与储存在服务器的该批次传感器的实验室数据进行比对，得到校正系数，校正系数的具体算法为：1-(实验室数据-校准数据)/校正数据＝校正系数，也可以是其他公知的校正算法，其目的就是缩小误差。
E、按传感器信息查找到该批次传感器在服务器中的实验室数据与混色修正值或者灰度修正值进行比对，得到最终测试结果进行存档并发送到客 户端。
对于传感器反应信息受温度影响较大的，步骤B中，终端收到的信息中，还应包含有用户使用时的温度值；步骤F中，混色修正值或者灰度修正值与服务器中该批次传感器在对应温度段下的实验室数据进行比对，得到最终测试结果进行存档并发送到客户端。
通过传感器误差处理、多次测试误差处理，使得对采集光信息的云端处理更为准确。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。

Claims (2)

  1. 一种采集光信息的云端处理方法，其特征在于：包含如下步骤：
    A、将生产的每批次传感器取样拿到实验室进行试验，得出标准的实验室数据储存在服务器中；
    B、将终端收到的用户放入检测物前后的传感器反应信息分为校准数据和测试数据，连同传感器信息进行识别；
    C、计算出测试数据的平均RBG值或者平均灰度值，对平均RBG值用加权平均算法进行计算，得到一个混色值；
    D、校准数据与储存在服务器的该批次传感器的实验室数据进行比对，得到校正系数；
    E、将混色值或者平均灰度值与校正系数相乘得到混色修正值或者灰度修正值；
    F、按传感器信息查找到该批次传感器在服务器中的实验室数据与混色修正值或者灰度修正值进行比对，得到最终测试结果进行存档并发送到客户端。
  2. 根据权力要求1所述的采集光信息的云端处理方法，其特征在于：对于传感器反应信息受温度影响较大的，步骤B中，终端收到的信息中，还应包含有用户使用时的温度值；步骤F中，混色修正值或者灰度修正值与服务器中该批次传感器在对应温度段下的实验室数据进行比对，得到最终测试结果进行存档并发送到客户端。
PCT/CN2016/102229 2015-10-16 2016-10-14 采集光信息的云端处理方法 WO2017063598A1 (zh)

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Publication number Priority date Publication date Assignee Title
CN105389459A (zh) * 2015-10-16 2016-03-09 吴凡 采集光信息的云端处理方法
CN106124748A (zh) * 2016-07-27 2016-11-16 柳州康云互联科技有限公司 用于移动端的尿常规检测传感器

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5712966A (en) * 1994-03-22 1998-01-27 Kabushiki Kaisha Topcon Medical image processing apparatus
US20020003893A1 (en) * 1998-03-31 2002-01-10 Eiji Ogawa Medical network system
CN103414810A (zh) * 2013-07-29 2013-11-27 王曙光 基于移动终端检测反应图像的方法、移动终端及检测载体
CN104280390A (zh) * 2014-09-30 2015-01-14 王钧 一个基于网络的比色检测系统
CN104964973A (zh) * 2015-07-08 2015-10-07 邓双胜 一种基于移动终端摄像头的试纸读取与分析方法与系统
CN105260606A (zh) * 2015-10-16 2016-01-20 吴凡 移动式医疗光学信息采集系统
CN105389459A (zh) * 2015-10-16 2016-03-09 吴凡 采集光信息的云端处理方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5712966A (en) * 1994-03-22 1998-01-27 Kabushiki Kaisha Topcon Medical image processing apparatus
US20020003893A1 (en) * 1998-03-31 2002-01-10 Eiji Ogawa Medical network system
CN103414810A (zh) * 2013-07-29 2013-11-27 王曙光 基于移动终端检测反应图像的方法、移动终端及检测载体
CN104280390A (zh) * 2014-09-30 2015-01-14 王钧 一个基于网络的比色检测系统
CN104964973A (zh) * 2015-07-08 2015-10-07 邓双胜 一种基于移动终端摄像头的试纸读取与分析方法与系统
CN105260606A (zh) * 2015-10-16 2016-01-20 吴凡 移动式医疗光学信息采集系统
CN105389459A (zh) * 2015-10-16 2016-03-09 吴凡 采集光信息的云端处理方法

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