Abstract
Objective: Electrical stimulation of intracranial electrodes can map the patient's specific functional regions and seizure related symptoms. In our clinical practice, evoked functional symptoms and electrographic responses are manually annotated and visualized in a schematic electrode overview: an error-prone and time-consuming process. We here present an open-source graphical user interface (GUI) that standardizes the workflow and automatizes the visualization of intracranial EEG (iEEG) electrical stimulation results. Methods: We defined categories of evoked clinical symptoms based on a literature study and consensus session. A co-design team participated in brainstorm sessions to set the requirements of the GUI. We built the GUI and tested its usability with qualitative and quantitative assessments (System Usability Scales (SUS) questionnaires). Results: The workflow included standardized annotation of categories of evoked clinical symptoms in the iEEG software. The GUI visualized these evoked clinical symptoms in a 2D schematic overview, a 3D visualization of the brain with locations of evoked symptoms, and showed additional annotations per stimulated electrodes in a table. A mean SUS score of 82.3 (SD 9.2) was reached, which is considered excellent. Conclusions: We present an in-house developed workflow and graphical user interface (GUI) to categorize and directly visualize evoked clinical symptoms resulting from electrical stimulation on intracranial electrodes. Significance: Our open-source GUI facilitates standardization of the intracranial stimulation workflow and directly enables straightforward and uniform interpretation of evoked clinical symptoms.
| Original language | English |
|---|---|
| Pages (from-to) | 492-502 |
| Number of pages | 11 |
| Journal | Clinical Neurophysiology Practice |
| Volume | 11 |
| DOIs | |
| Publication status | Published - Jan 2026 |
Keywords
- Clinical symptoms
- Co-design
- Electrical stimulation
- Evoked symptoms
- Focal epilepsy
- Graphical user interface
- Intracranial EEG
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