Application for diagnosing Alzheimer's disease and device for diagnosing Alzheimer's disease

A technology for Alzheimer's disease and diagnosis, which is applied in the direction of diagnosis, application, diagnosis record/measurement, etc. It can solve the problems of AD patients such as difficulty in persisting, labor-intensive, and long test time. The method is simple, flexible, interesting, The effect of short time consumption and small manpower requirement

Active Publication Date: 2022-04-29
BEIJING MUSICAL INSTR RES INST
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the process of the scale diagnosis method is boring and the test time is long, and it is difficult for AD patients to persist in completing it. Moreover, the scale diagnosis method needs to be tested one-to-one, which is labor-intensive and not suitable for large-scale adoption.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Application for diagnosing Alzheimer's disease and device for diagnosing Alzheimer's disease
  • Application for diagnosing Alzheimer's disease and device for diagnosing Alzheimer's disease
  • Application for diagnosing Alzheimer's disease and device for diagnosing Alzheimer's disease

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0241] Embodiment 1 establishes diagnostic model A

[0242] according to figure 2 , 4 The method or device establishes the diagnosis model A and performs the diagnosis.

[0243] Randomly select 15 participants with Alzheimer's disease (MMSE scale score 15-20 points, 8 males, 7 females) and 15 healthy participants (MMSE scale score above 26 points, males 8 people, 7 women) as a training set, record each person's education level (1 means elementary school, 2 means junior high school, 3 means high school) and actual age.

[0244] (1) pitch test

[0245] According to the actual physical and mental state of the 30 participants, choose Angloon, thumb piano (Kalimba kalimba) or piano instrument respectively. Before the test, show the selected musical instruments to the participants, and perform a demonstration of playing the tones, and ask the participants to try until they can play the tones proficiently.

[0246] Intonation test 1: The staff will play the three tones called...

Embodiment 2

[0283] Embodiment 2 establishes diagnostic model B

[0284]According to the education level of all people in embodiment 1, intonation test 1 (YZ1), rhythm test 1 (DJ1) data and MMSE diagnosis result, carry out parameter training by logistic regression algorithm, obtain diagnosis model B as follows:

[0285] Y=27.663+(-2.180)×R 1 +(-1.989)×R 2 +(-2.701)×R 5

[0286] Among them, Y represents the diagnosis result, R 1 Indicates education level, R 2 Indicates pitch test 1 score, R 5 Indicates the score of rhythm test 1; and the threshold value is 0, that is, Y>0, the diagnosis result is diseased, otherwise the diagnosis result is not diseased.

Embodiment 3

[0287] Embodiment 3 establishes diagnostic model C

[0288] According to the education level of all people in embodiment 1, pitch test 1 (YZ1), pitch test 2 (YZ2), rhythm test 1 (DJ1), rhythm test 2 (DJ2) data and MMSE diagnosis result, carry out by logistic regression algorithm Parameter training, the diagnosis model C is obtained as follows:

[0289] Y=15.4818+0.8629×R 1 +(-0.7602)×R 2 +(-0.5532)×R 3 +0.3974×R 5 +(-2.9928)×R 6

[0290] Among them, Y represents the diagnosis result, R 1 Indicates education level, R 2 Indicates pitch test 1 score, R 3 Indicates pitch test 2 score, R 5 Indicates the rhythm test 1 score, R 6 Indicates the score of rhythm test 2; and the threshold value is 0.667, that is, Y>0.667, the diagnosis result is diseased, otherwise the diagnosis result is not diseased.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical field of diagnostic devices, and specifically relates to the use of keyboard instruments and percussion instruments in the manufacture of a device for diagnosing Alzheimer's disease. Among them, the use of keyboard instruments is used to test the pitch of the person to be diagnosed to obtain pitch scores, and the use of percussion instruments is used to test the pitch of the person to be diagnosed. The patient conducts a rhythm test to obtain a rhythm score, and the intonation score and rhythm score are substituted into a pre-established diagnostic model through machine learning methods for calculation to obtain a diagnosis result. The invention also relates to a device for diagnosing Alzheimer's disease. The method of the invention can diagnose Alzheimer's disease simply, accurately and quickly, and is suitable for large-scale use.

Description

technical field [0001] The invention belongs to the technical field of diagnostic devices, and in particular relates to the use of keyboard instruments and percussion instruments in manufacturing a device for diagnosing Alzheimer's disease, and also relates to a device for diagnosing Alzheimer's disease. Background technique [0002] Alzheimer's disease (AD) is an age-related chronic progressive central nervous system degenerative disease. Among the elderly over 65 years old, the prevalence of AD is about 5%, and the risk of AD will double for every 5 years of age thereafter. In 2015, the number of AD patients in the world was about 46.8 million. According to the latest statistics in 2017, the prevalence of AD among people aged 65 and over in my country is 5.56%. At present, the disease cannot be cured, and drug intervention is mainly used to relieve symptoms and delay the development of the disease. Therefore, early prediction, early detection, early diagnosis and early ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/00G06N20/00G16H20/00
CPCA61B5/4088A61B5/7282G16H20/00G06N20/00
Inventor 张小川陈显扬赵春婷高彤
Owner BEIJING MUSICAL INSTR RES INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap