TSSummarize: A Visual Strategy to Summarize Biosignals

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Visual tools enhance the human ability to detect structures found on time series. Medical doctors and data-scientists rely on their visual abilities to perform time series analysis. A visual tool that would summarize several sources of information of time series would be of great value and is not yet provided in the literature. This work proposes a novel unsupervised visual strategy to summarize a time series and compact several layers of information. The strategy extracts information from the Self-Similarity Matrix (SSM). This data source is able to segment the time series, detect events and show relationships between subsequences. The visual strategy has been tested on several use-cases from the medical domain, proving to be type agnostic, intuitive and compact.

Original languageEnglish
Title of host publicationProceedings of 2021 IEEE 7th International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665441261
DOIs
Publication statusPublished - 25 Mar 2021
Event7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021 - Chennai, India
Duration: 25 Mar 202127 Mar 2021

Conference

Conference7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021
Country/TerritoryIndia
CityChennai
Period25/03/2127/03/21

Keywords

  • biosignals
  • events
  • segmentation
  • summarize
  • time series
  • unsupervised
  • visualization

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