3 ms·
Lots of different things. The software already uses NNs to detect the following: * Epileptogenic spikes * Seizures * Eyeblink artifacts * Muscle artifacts
by antognini 10y ago
Lots of different things. The software already uses NNs to detect the following:
* Epileptogenic spikes
* Seizures
* Eyeblink artifacts
* Muscle artifacts
* Movement artifacts
* Electrode artifacts
* QRS complexes
We are working on many more features:
* Sleep staging
* Other artifacts
* Bringing seizure detection to human-level performance
* K-complexes, sleep spindles and other features of sleep
The ultimate goal is to analyze and mark an EEG record the same way that an expert neurologist woul neurologist would.
- jason_slack 10y agoWhere do you get data to train the NNs for these items?
- antognini 10y agoWe have a network of neurologists who provide anonymized EEG records to us from a variety of hospitals and epilepsy monitoring units around the country. We then have an ever-shifting group of neurologists who mark the records for us so that we have labels we can train against. It's a little tricky in practice because EEG interpretations aren't always cut-and-dried. Some neurologists will mark a section as a seizure and others won't, or they'll mark the starting times and ending times differently, so you have to score the seizure with a "perception index" that varies from 0 to 1 instead of just being a binary yes/no. Sometimes a record has a very large number of spikes, so the neurologists will often miss a lot of them, so you also don't want to penalize your NN for catching real spikes that were mislabeled, etc. We have to spend a fair amount of time thinking about the specific cost function we want to optimize.
- deleted 10y ago[deleted]