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Disease Prediction By Articulatory Analysis Using Deep Learning.

In today's technology, there is a lot of development involved in the field of medical. At the same time, the continuous monitoring of the patient's health condition also takes a vital role in the medical field. For example, the heart rate is to be simultaneously monitored. In this project, the conti...

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Published in:Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 2247 - 2252
Main Authors: RAMYA, S., NANDHANA, S., BHARKAVI, S. S. SHRI, SUGANYA, A., THARANI, D.
Format: pictorial review tables/charts Journal Article
Published: Turkish Journal of Physiotherapy & Rehabilitation 2021
Online Access:View this record in EBSCOhost
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      dt: 2021
      vid: 32
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      pub: Turkish Journal of Physiotherapy & Rehabilitation
      place: Kizilay/ Ankara, <Blank>
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        atl: Disease Prediction By Articulatory Analysis Using Deep Learning.
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        au:
          RAMYA, S.
          NANDHANA, S.
          BHARKAVI, S. S. SHRI
          SUGANYA, A.
          THARANI, D.
        affil: Assistant Professor, Department of Information Technology M.Kumarasamy College of Engineering, Karur, Tamilnadu
      sug:
        subj:
          Deep Learning
          Monitoring, Physiologic
          Computers and Computerization Equipment and Supplies
          Heart Rate
          Body Temperature
          Mobile Applications
          Physicians
          Extended Family
          Communication
          Internet of Things
          Computer Hardware
      ab: In today's technology, there is a lot of development involved in the field of medical. At the same time, the continuous monitoring of the patient's health condition also takes a vital role in the medical field. For example, the heart rate is to be simultaneously monitored. In this project, the continuous analysis of the heart beat is done by using the arduino microcontroller. In addition to this, the temperature is also monitored by using the LM35.The normal and abnormal heart rates are measured by connecting the pulse sensor to the patient. The overall process is continuously updated to required authority using GSM module and also updated in mobile application by using Bluetooth module. The emergency message to the doctor or relatives when the abnormal activity of pulse rate or temperature is detected. For that, the arduino IDE platform is employed. Hence an efficient health monitoring system can be designed.
      pubtype: Academic Journal
      doctype:
        pictorial
        review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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