Earticle

초록

영어

The Intensive Care Unit (ICU) bedside monitors present the medical staff with large amounts of continuous data which can create a number of challenges. If the data is transmitted as part of a telemedicine system then the large volume of data can put pressure on bandwidth and affect the quality of service of the network. Another challenge is that the large volume of data has to be interpreted by medical staff to make a patient state assessment. In this paper we propose a time series analysis technique called data wavelets to derive trends in the data – this acts as a form of data compression for telemedicine and improves the quality of service of a network and also facilitates clinical decision support in the form of qualitative reasoning for patient state assessment. Our approach has been successfully applied to cardiovascular data from a neonatal ICU.

목차

Abstract
 1. Introduction
 2. Wavelet Analysis
 3. Results
 4. Discussion
  4.1 Data Compression to Reduce Transmission Costs
  4.2 Improving Quality of Service
  4.3 Clinical Data Support
 5. Related Work
 6. Conclusions
 References

키워드

저자

• Apkar Salatian [ School of Information Technology and Communications American University of Nigeria, Yola Bypass ]
• Francis Adepoju [ School of Information Technology and Communications American University of Nigeria, Yola Bypass ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605