Hyppää sisältöön
    • Suomeksi
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction

Tuan Nguyen Gia; Mingzhe Jiang; Tomi Westerlund; Pasi Liljeberg; Amir-Mohammad Rahmani; Hannu Tenhunen

Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction

Tuan Nguyen Gia
Mingzhe Jiang
Tomi Westerlund
Pasi Liljeberg
Amir-Mohammad Rahmani
Hannu Tenhunen
Katso/Avaa
CIT2015-Fog Computing.pdf (1.060Mb)
Lataukset: 

doi:10.1109/CIT/IUCC/DASC/PICOM.2015.51
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2021042714073
Tiivistelmä


Internet of Things technology provides a competent and structured approach to improve health and wellbeing of mankind. One of the feasible ways to offer healthcare services based on IoT is to monitor human's health in real-time using ubiquitous health monitoring systems which have the ability to acquire bio-signals from sensor nodes and send the data to the gateway via a particular wireless communication protocol. The real-time data is then transmitted to a remote cloud server for real-time processing, visualization, and diagnosis. In this paper, we enhance such a health monitoring system by exploiting the concept of fog computing at smart gateways providing advanced techniques and services such as embedded data mining, distributed storage, and notification service at the edge of network. Particularly, we choose Electrocardiogram (ECG) feature extraction as the case study as it plays an important role in diagnosis of many cardiac diseases. ECG signals are analyzed in smart gateways with features extracted including heart rate, P wave and T wave via a flexible template based on a lightweight wavelet transform mechanism. Our experimental results reveal that fog computing helps achieving more than 90% bandwidth efficiency and offering low-latency real time response at the edge of the network.

Kokoelmat
  • Rinnakkaistallenteet [19207]

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

JulkaisuajatTekijätNimekkeetAsiasanatTiedekuntaLaitosOppiaineYhteisöt ja kokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste