Study of Energy-Efficient Biomedical Data Compression Methods in the Wireless Body Area Networks (WBANs) and Remote Healthcare Networks

被引:1
作者
Ahmadzadeh, Safiyyeh [1 ]
机构
[1] Islamic Azad Univ, Dept Comp Engn, Urmia Branch, Orumiyeh, Iran
关键词
Compression; Lossy; Lossless; Biomedical image; Low-power; Energy-efficient; Biomedical signal; IMAGE COMPRESSION; LOSSY COMPRESSION; WAVELET TRANSFORM; DCT; TRANSMISSION; INTERNET; LOSSLESS; ALGORITHM; FUSION; THINGS;
D O I
10.1007/s10776-023-00599-6
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Wireless Body Area Network (WBAN) is a wireless network of short-range communication protocols for remote healthcare monitoring with the possibility of giving freedom of human body movements. Sensor nodes (motes) are usually located under the skin, implanted deep in the body, or ingested, as in the rare case of smart pills for medical and non-medical usage. Since the necessary connections of wearable and implantable devices are wireless, and the components use low batteries, processing and transferring the critical data can deplete the nodes' power. In most cases, it is impossible to exchange or re-power batteries. Holter monitoring, loop recorders, and wireless capsule endoscopy are some of the WBAN's applications for saving and transferring medical data. Wireless capsule endoscopy is the application for image transmission in WBANs, and the image compression in common is a specific segment of capsule endoscopy. Since the better compression of images increases the frame rate and typically improves the diagnosis process, selecting the compression algorithm should be relevant. The considerable scope of this comprehensive study pays attention to the various biomedical data compression approaches in WBANs. This paper focuses on power-efficient schemes of remote healthcare networks. In this survey article, the energy-based biomedical data compression approaches of WBANs and remote healthcare networks are accurately classified based on lossy, lossless, and hybrid techniques; later, a comprehensive comparison of each specific method's power consumption is presented.
引用
收藏
页码:252 / 269
页数:18
相关论文
共 92 条
  • [1] Abdellatif A. A., 2019, GOOGLE PATENTS
  • [2] Quality Controlled ECG Compression using Discrete Cosine Transform (DCT) and Laplacian Pyramid (LP)
    Aggarwal, Vibha
    Patterh, Manjeet Singh
    [J]. 2009 INTERNATIONAL CONFERENCE ON MULTIMEDIA, SIGNAL PROCESSING AND COMMUNICATION TECHNOLOGIES, 2009, : 12 - +
  • [3] Agung B. W. R., 2012, 2012 IEEE International Conference on Communication, Networks and Satellite (ComNetSat 2012), P167, DOI 10.1109/ComNetSat.2012.6380799
  • [4] Ahn E., 2019, MED IMAGE ANAL
  • [5] Internet of Things security: A survey
    Alaba, Fadele Ayotunde
    Othman, Mazliza
    Hashem, Ibrahim Abaker Targio
    Alotaibi, Faiz
    [J]. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2017, 88 : 10 - 28
  • [6] Performance enhanced ripplet transform based compression method for medical images
    Anitha, J.
    Sophia, P. Eben
    Le Hoang Son
    de Albuquerque, Victor Hugo C.
    [J]. MEASUREMENT, 2019, 144 : 203 - 213
  • [7] SVD-based robust image steganographic scheme using RIWT and DCT for secure transmission of medical images
    Arunkumar, S.
    Subramaniyaswamy, V
    Vijayakumar, V.
    Chilamkurti, Naveen
    Logesh, R.
    [J]. MEASUREMENT, 2019, 139 : 426 - 437
  • [8] Feed-Forward Neural Network-Based Predictive Image Coding for Medical Image Compression
    Ayoobkhan, Mohamed Uvaze Ahamed
    Chikkannan, Eswaran
    Ramakrishnan, Kannan
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (08) : 4239 - 4247
  • [9] Azar J., 2019, ENERGY EFFICIENT IOT
  • [10] Baby MK, 2017, 2017 INTERNATIONAL CONFERENCE ON NETWORKS & ADVANCES IN COMPUTATIONAL TECHNOLOGIES (NETACT), P178, DOI 10.1109/NETACT.2017.8076763