Spike-based QRS complex detection in ECG signals

Activity: Talk or presentationContributed talkscience-to-science

Description

The problem of QRS detection in ECG signals addresses the identification of heart beats in electrocardiogram signals. This pattern detection problem for bio-signals is taken as a use case to investigate the feasibility and effectiveness of spike-based encoding of time-varying signals by means of threshold-based sampling. We compare the state-of-the-art detection algorithm based on equidistant sampling with threshold-based approaches, comprising signal processing techniques and spiking neural networks (SNN). In contrast to equidistant sampling, this approach allows a reduction of the input data stream by a factor of 10 on average while maintaining comparable detection performance.
Period26 Mar 2024
Event titleSNNSys Workshop on Spiking Neural Networks at AIRoV 24
Event typeConference
LocationAustriaShow on map

Fields of science

  • 202017 Embedded systems
  • 202028 Microelectronics
  • 202027 Mechatronics
  • 202015 Electronics
  • 202037 Signal processing
  • 102019 Machine learning
  • 202036 Sensor systems
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202023 Integrated circuits
  • 202022 Information technology
  • 202041 Computer engineering

JKU Focus areas

  • Digital Transformation