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This study seeks to contribute to the growing body of literature on hypnosis by providing robust, data-driven insights into the physiological mechanisms underlying trance states. The integration of electroencephalogram (EEG) and other wearable-derived physiological data will offer a comprehensive assessment of the changes that occur during a standardized hypnosis protocol: the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A). The results of this study are intended to facilitate derivation and validation of an Artificial Intelligence/Machine Learning (AI/ML)-based monitor that quantifies a patient's instantaneous emotional/arousal state along the spectrum that spans anxiety through states of calmness and trance. Future investigations will explore the ability of using such an interactive virtual system as a component of a closed-loop adaptive device to create optimal states of non-pharmacological sedation using personalized audiovisual content to allay anxiety and discomfort during medical procedures, such as percutaneous biopsies.
Full description
This is an interventional study that will acquire data to characterize the time course of physiological biomarkers and audiovisual observations of depth of trance before, during and upon emergence from a standardized hypnotic susceptibility protocol. The subjects will also complete the State Trait Anxiety Inventory (STAI) immediately before and after the hypnosis protocol. The differences in the biomarker signals among subjects of different degrees of hypnotic susceptibility and different pre-post levels of state anxiety will facilitate between- and within-subjects comparisons that will be supplemented by computer vision analysis of subject responses. The full data set will be used to facilitate derivation and validation of a novel machine-learning monitoring tool to measure instantaneous emotional/arousal levels along a spectrum that spans anxiety through calmness and trance.
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50 participants in 1 patient group
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Central trial contact
Saum Naderi, MA; Rachelle Weisman, MPH
Data sourced from clinicaltrials.gov
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