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Accepted for/Published in: JMIR Neurotechnology

Date Submitted: Jul 8, 2023
Date Accepted: Nov 21, 2023

The final, peer-reviewed published version of this preprint can be found here:

Application of a Low-Cost mHealth Solution for the Remote Monitoring of Patients With Epilepsy: Algorithm Development and Validation

Sriraam N, Raghu S, D Gommer E, M W Hilkman D, Temel Y, Vasudeva Rao S, Hegde A, Kubben P

Application of a Low-Cost mHealth Solution for the Remote Monitoring of Patients With Epilepsy: Algorithm Development and Validation

JMIR Neurotech 2023;2:e50660

DOI: 10.2196/50660

PMCID: 12671322

Application of Low-cost Mobile Health for Remote Monitoring of Epilepsy Patients

  • Natarajan Sriraam; 
  • S Raghu; 
  • Erik D Gommer; 
  • Danny M W Hilkman; 
  • Yasin Temel; 
  • Shyam Vasudeva Rao; 
  • AS Hegde; 
  • Pieter Kubben

ABSTRACT

Background:

The objective of this study is to investigate the feasibility of smartphones for processing larger electroencephalography (EEG) recordings for the application towards remote monitoring of epilepsy patients.

Objective:

We have developed a mobile application to automatically analyze and perform the classification of epileptic seizures.

Methods:

For this purpose, we have used the cross-database model developed in our previous study using successive decomposition index and matrix determinant as features, adaptive median feature baseline correction to overcome inter-database feature variation and post-processing based support vector machine for classification using five different EEG databases. The sezect (seizure detect) Android application was built using Chaquopy soft- ware development kit which uses Python language in Android Studio.

Results:

Different duration of EEG signals was tested on different versions of smartphones using sezect app to check its feasibility.

Conclusions:

The computational time required to process the real-time EEG data on smartphone and classification results suggests that mobile-health could be a great asset to monitor epilepsy patients. More details on sezect Android app can be found at: http://doi.org/10.5281/zenodo.3592415.


 Citation

Please cite as:

Sriraam N, Raghu S, D Gommer E, M W Hilkman D, Temel Y, Vasudeva Rao S, Hegde A, Kubben P

Application of a Low-Cost mHealth Solution for the Remote Monitoring of Patients With Epilepsy: Algorithm Development and Validation

JMIR Neurotech 2023;2:e50660

DOI: 10.2196/50660

PMCID: 12671322

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