ECG-Based Arrhythmia Detection SNN Algorithm Using STDP and Spike Inference for Smart Health City 


Vol. 45,  No. 12, pp. 2193-2201, Dec.  2020
10.7840/kics.2020.45.12.2193


PDF
  Abstract

Due to changes in the medical system, an aging population, and the current COVID-19 crisis, a lot of interest and investment in the healthcare industry is increasing. The development of machine learning technology led by deep learning drives its applications to healthcare services. However, the conventional deep learning models consume a lot of power and are difficult to miniaturize, so they are not suitable for wearable devices required by smart cities. Accordingly, interests in spiking neural network (SNN), a next-generation artificial intelligence research field with low power and parallelism, are emerging as an alternative. In this paper, SNN is designed with STDP, an unsupervised learning algorithm that learns time difference between pre and post synapses. It is also applied to ECG arrhythmia data sets and produces accuracy, sensitivity and specificity according to cumulative spike-based inference. With the experiment results, we want to show the possibility of SNN as a healthcare technology and new implications too.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

C. Lee, W. Lee, S. Han, C. Park, "ECG-Based Arrhythmia Detection SNN Algorithm Using STDP and Spike Inference for Smart Health City," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 12, pp. 2193-2201, 2020. DOI: 10.7840/kics.2020.45.12.2193.

[ACM Style]

Choongseop Lee, Wongyu Lee, Seungwoo Han, and Cheolsoo Park. 2020. ECG-Based Arrhythmia Detection SNN Algorithm Using STDP and Spike Inference for Smart Health City. The Journal of Korean Institute of Communications and Information Sciences, 45, 12, (2020), 2193-2201. DOI: 10.7840/kics.2020.45.12.2193.

[KICS Style]

Choongseop Lee, Wongyu Lee, Seungwoo Han, Cheolsoo Park, "ECG-Based Arrhythmia Detection SNN Algorithm Using STDP and Spike Inference for Smart Health City," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 12, pp. 2193-2201, 12. 2020. (https://doi.org/10.7840/kics.2020.45.12.2193)

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880