[Abstract] Sounds of seizures

Highlights

  • Epileptologists can accurately identify certain seizure types based on sound alone.
  • Their consensus performance showed a PPV of 0.91 and a NPV of 0.66.
  • Hyperkinetic and tonic-clonic seizures were accurately identified.
  • Automatisms only and non-motor seizures were not accurately identified.

Abstract

Purpose

A phase I feasibility study to determine the accuracy of identifying seizures based on audio recordings.

Methods

We systematically generated 166 audio clips of 30 s duration from 83 patients admitted to an epilepsy monitoring unit between 1/2015 and 12/2016, with one clip during a seizure period and one clip during a non-seizure control period for each patient. Five epileptologists performed a blinded review of the audio clips and rated whether a seizure occurred or not, and indicated the confidence level (low or high) of their rating. The accuracy of individual and consensus ratings were calculated.

Results

The overall performance of the consensus rating between the five epileptologists showed a positive predictive value (PPV) of 0.91 and a negative predictive value (NPV) of 0.66. The performance improved when confidence was high (PPV of 0.96, NPV of 0.70). The agreement between the epileptologists was moderate with a kappa of 0.584. Hyperkinetic (PPV 0.92, NPV 0.86) and tonic-clonic (PPV and NPV 1.00) seizures were most accurately identified. Seizures with automatisms only and non-motor seizures could not be accurately identified. Specific seizure-related sounds associated with accurate identification included disordered breathing (PPV and NPV 1.00), rhythmic sounds (PPV 0.93, NPV 0.80), and ictal vocalizations (PPV 1.00, NPV 0.97).

Conclusion

This phase I feasibility study shows that epileptologists are able to accurately identify certain seizure types from audio recordings when the seizures produce sounds. This provides guidance for the development of audio-based seizure detection devices and demonstrate which seizure types could potentially be detected.

via Sounds of seizures – ScienceDirect

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