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has been cited by the following article:

• TITLE: Signal averaging for noise reduction in anesthesia monitoring and control with communication channels

  AUTHORS: Zhi-Bin Tan, Le-Yi Wang, Hong Wang

  KEYWORDS: Anesthesia Depth; Anesthesia Monitoring; Anesthesia Control; Signal Averaging; Noise Reduction; Open and Closed Loop Systems; Communications; Networked Systems

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.7, November 20, 2009

  ABSTRACT: This paper investigates impact of noise and signal averaging on patient control in anesthesia applications, especially in networked control system settings such as wireless connected systems, sensor networks, local area networks, or tele-medicine over a wide area network. Such systems involve communication channels which introduce noises due to quantization, channel noises, and have limited communication bandwidth resources. Usually signal averaging can be used effectively in reducing noise effects when remote monitoring and diagnosis are involved. However, when feedback is intended, we show that signal averaging will lose its utility substantially. To explain this phenomenon, we analyze stability margins under signal averaging and derive some optimal strategies for selecting window sizes. A typical case of anesthe-sia depth control problems is used in this development.