Novel Multimodal Neural, Physiological, and Behavioral Sensing and Machine Learning for Mental States

Recruiting
18 years or above
All
Phase N/A
90 participants needed
2 Locations

Brief description of study.

In this program, the investigators will develop novel multimodal neural-behavioral-physiological monitoring tools (software and hardware), and machine learning models for mental states within social processes and beyond. The tools consist of a multimodal skin-like wearable sensor for physiological and biochemical sensing; a conversational virtual human platform to evoke naturalistic social processes; audiovisual affect recognition software; synchronization tools; and machine learning methods to model the multimodal data. The investigators will demonstrate the tools in healthy subjects without neural recordings and in patients with drug-resistant epilepsy who already have intracranial EEG (iEEG) electrodes implanted based on clinical criteria for standard monitoring to localize seizures, which is unrelated to our study.

Eligibility of study

You may be eligible for this study if you meet the following criteria:

  • Conditions: No Condition, Study Mental State in Healthy Populations and Drug-resistant Epilepsy Patients With Existing iEEG
  • Age: 18 years or above
  • Gender: All

For the healthy population, all subjects over the age of 18 who are able and willing to give informed consent will be eligible.

For the epilepsy population, inclusion criteria are:

  • Patients who suffer from drug-resistant epilepsy and already have intracranial EEG (iEEG) electrodes implanted based on clinical criteria for their standard seizure localization (unrelated to our study) will be eligible. Most patients are healthy adults outside of their epilepsy.
  • Subjects >= 18 are only included in this study.
  • All patients with the above conditions and with already-implanted electrodes who are willing to participate and able to cooperate and follow research instructions will be recruited.

Updated on 31 Jul 2025. Study ID: R61MH135407

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