Using compressed sensing for wireless in-home sleep staging

施冠竹

Abstract

There is increasing interest in the development of wireless in-home sleep staging systems that allow the patient to be monitored remotely while remaining in the comfort of their home. However, the problem of transmitting large amounts of polysomnography data over the Internet must be solved. A previously proposed system for in-home sleep staging deals with the high data rate by using the set partitioning in hierarchical trees (SPIHT) algorithm, a compression algorithm for image processing. However, a microcontroller cannot meet the requirements for SPIHT. The present study proposes a system architecture that uses the compressed sensing (CS) algorithm, an algorithm for sensor networks that has recently replaced SPIHT. The results show that the CS algorithm has a higher compression ratio and lower resource requirements compared to those for SPIHT.

背景:近年來越來越多人感興趣開發居家睡眠信號蒐集和判讀系統但是如何處理在互聯網上傳送的大量PSG訊號是一個重大的議題前人提出在居家蒐集PSG訊號的系統架構,架構中存在個缺陷為解決PSG資料量太大的問題系統上使用到影像壓縮著名演算法SPIHT(set partitioning in hierarchical tree)在微處理器上有著較嚴格的資源限制為解決這些問題我們在壓縮演算法上改採用近年來在sensor network上所使用的縮演算法CS(compressed sensing)在相同的品質要求下我們所使用的壓縮演算法CS可以使用比SPIHT更好的省電效果

Introduction

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