title: Using off-the-shelf lossy compression for wireless home sleep staging.
abstract: BACKGROUND
  Recently, there has been increasing interest in the development of wireless home sleep staging systems that allow the patient to be monitored remotely while remaining in the comfort of their home. However, transmitting large amount of Polysomnography (PSG) data over the Internet is an important issue needed to be considered. In this work, we aim to reduce the amount of PSG data which has to be transmitted or stored, while having as little impact as possible on the information in the signal relevant to classify sleep stages.
  
  
  METHODS
  We examine the effects of off-the-shelf lossy compression on an all-night PSG dataset from 20 healthy subjects, in the context of automated sleep staging. The popular compression method Set Partitioning in Hierarchical Trees (SPIHT) was used, and a range of compression levels was selected in order to compress the signals with various degrees of loss. In addition, a rule-based automatic sleep staging method was used to automatically classify the sleep stages.
  
  
  RESULTS
  Considering the criteria of clinical usefulness, the experimental results show that the system can achieve more than 60% energy saving with a high accuracy (>84%) in classifying sleep stages by using a lossy compression algorithm like SPIHT.
  
  
  CONCLUSIONS
  As far as we know, our study is the first that focuses how much loss can be tolerated in compressing complex multi-channel PSG data for sleep analysis.
  
  
  CONCLUSIONS
  We demonstrate the feasibility of using lossy SPIHT compression for wireless home sleep staging.
authors: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan; Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan.
authors: Kun-Chan
authors: KC
authors: Lan
authors: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan; Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan.
authors: Da-Wei
authors: DW
authors: Chang
authors: Department of Psychology, National Cheng Kung University, Tainan 701, Taiwan.
authors: Chih-En
authors: CE
authors: Kuo
authors: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
authors: Ming-Zhi
authors: MZ
authors: Wei
authors: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
authors: Yu-Hung
authors: YH
authors: Li
authors: Department of Psychology, National Cheng Kung University, Tainan 701, Taiwan.
authors: Fu-Zen
authors: FZ
authors: Shaw
authors: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan; Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan. Electronic address: sfliang@mail.ncku.edu.tw.
authors: Sheng-Fu
authors: SF
authors: Liang
mesh_terms: D000465:Algorithms; D058256:Brain Waves / Q000502:physiology*; D044962:Data Compression / Q000379:methods*; D004569:Electroencephalography; D004576:Electromyography; D004585:Electrooculography; D005260:Female; D006801:Humans; D008297:Male; D017286:Polysomnography; D012815:Signal Processing, Computer-Assisted; D012894:Sleep Stages / Q000502:physiology*; D014851:Wakefulness / Q000502:physiology; D059015:Wireless Technology; D055815:Young Adult
keywords: Home sleep staging; PSG; SPIHT compression; Sleep EEG