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Design of medical equipment system based on neural network algorithm and network feature
- Source :
- Journal of Intelligent & Fuzzy Systems. 40:6815-6825
- Publication Year :
- 2021
- Publisher :
- IOS Press, 2021.
-
Abstract
- Nowadays, science and technology are developing, more and more things need to be detected by science and technology, and the content that people need to understand is becoming more and more complex. Not only need to know its size, but also need to know some of the relevant comprehensive information or internal information. At present, people’s demands can no longer be met only by existing medical systems, so data fusion technology has emerged. This technology can simultaneously obtain a variety of information, express various information, seek the internal relationship between various information, and comprehensively process and improve this relationship. In view of the existing medical equipment, this paper puts forward the design method of multi-sensor data fusion technology. The original whole system is decomposed into several small particles and extracted from the original system. The extracted particles are arranged independently and the neural network system is formed. On the basis of neural network computing and implementing network feature service, this paper introduces how to establish a new medical equipment system based on network registration, discovery and various management and fault-tolerant conditions. This article is a community-oriented, long-distance service intelligent system based on family health care, designed on network processors and Android systems. By combining various technologies, collecting various body information parameters of patients, under the guidance of network protocol and existing remote technology, the gateway of intelligent home can talk to the community to a certain extent. In this way, the data collected in smart homes can be uploaded to other communities through the community network.
- Subjects :
- Statistics and Probability
Artificial neural network
Computer science
business.industry
05 social sciences
General Engineering
050301 education
Medical equipment
050801 communication & media studies
Pattern recognition
0508 media and communications
Artificial Intelligence
Feature (computer vision)
Artificial intelligence
business
0503 education
Subjects
Details
- ISSN :
- 18758967 and 10641246
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Accession number :
- edsair.doi...........0b01e6607f688b57b8e162218333659c