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@INPROCEEDINGS{Schumm_Probabilistic_Appraisal_Of_Unobtrusively_Measured_ECG_Signals_2009,
     author = {Schumm, Johannes and Arnrich, Bert and Tr{\"{o}}ster, Gerhard},
   keywords = {arnrich_physio, SEAT},
      title = {Probabilistic Appraisal Of Unobtrusively Measured ECG Signals},
  booktitle = {ISSNIP Biosignals and Biorobotics Conference 2010},
       year = {2010},
   location = {Vitoria},
   abstract = {This paper focuses on appraising the signal quality of unobtrusive ECG measurements. When measuring ambulatory ECG in our daily life, the trade-off between signal quality and sensor comfort is obvious. Unobtrusive measurement systems do not achieve the same level of signal quality as systems using conventional wet ECG electrodes. To deal with this decrease in signal quality, we described in previous work how to transform the problem of appraising the quality of an ECG signal into a two-class classification problem. In this work, we extend this approach by introducing and investigating calibrated probabilistic outputs instead of binary decisions of the classifier. Probability estimates are important when the classification output is not used in isolation but is used for further processing and analysis. The working principle is demonstrated using Support Vector Machines (SVMs) as classification method. The system is evaluated with twelve subjects performing airplane passengers’ activities and a contactless ECG system incorporated into the airplane seat. As validation criteria we choose the Brier score that judges the quality of the calibration. The calibration process improves the Brier score from 0.114 to 0.068.}
}