This study will assess whether a movement detecting wristwatch can accurately detect seizures and seizure characteristics and record them into an online epilepsy diary. The patients may manually record a description into the online epilepsy diary of the symptoms they experienced before, during or after the seizure.
Typically, health care providers receive inaccurate patient self- reports. This pilot trial will document the feasibility of accurately recording and logging seizures into a cloud-based diary, under circumstances of controlled video-EEG monitoring to serve as a comparison "gold standard." More explicitly, we are testing the efficacy of the wristwatch in capturing movement parameters correlated with seizure activity and whether these parameters can be accurately uploaded into an online epilepsy diary. In the future, biosensor data could be valuable to more precisely obtain seizure data for clinical decision making as well as use in clinical trials.
Study Type
OBSERVATIONAL
Enrollment
30
Stanford Hospital and Clinics
Stanford, California, United States
Capture rate of convulsive seizure events by the watch and watch-diary interface compared to video electroencephalography (vEEG)
Time frame: up to 7 days
Capture rate of non-seizure events by the watch and watch-diary interface compared to vEEG
Time frame: up to 7 days
Frequency of movements of the watch diary interface vs vEEG
Time frame: up to 7 days
Amplitude of movements of the watch diary interface vs vEEG
Time frame: up to 7 days
Seizure semiology captured by the watch vs vEEG.
Time frame: up to 7 days.
Specificity of audio recordings of the watch vs vEEG
Will record audio through the watch and vEEG to assess the specificity of this parameter for epileptic vs nonepileptic seizures
Time frame: up to 7 days
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