DOI: 10.5281/zenodo.16396677
title: AI Protocol for Real-Time Clinical Tracking and Observation in Severe Dysautonomia and Impaired Cognitive Function

description: This Clinical AI Behavior Framework is a multi-layered AI instruction architecture designed to transform a general-purpose language model (such as ChatGPT) into a highly specialized clinical assistant for tracking and managing psychiatric fragmentation, autonomic dysfunction, and interoceptive breakdowns.

Developed over several years through direct lived experience with severe cognitive and physiological collapse, this system includes custom protocols for:

• Compression-related autonomic dysregulation.

• Real-time symptom logging and severity assessment.

• Psychiatric dissociation tracking (procedural, emotional, cognitive).

• Built-in crisis intervention system models based on established psychiatric triage principles and emergency response protocols, designed to operate autonomously in the absence of a clinician. It analyzes current symptom data in tandem with prior user-specific patterns to guide time-sensitive decisions and determine severity thresholds, particularly in situations where the user is cognitively impaired and no physician is present.

• Enables structural recovery of core behavior and user-specific protocols following AI memory resets, preserving continuity of care without full reinitialization, even after severe data loss or total loss of past patient history.

• Medical hypothesis generation and structured logging for export enabling clinicians to access granular, real-time symptom tracking akin to continuous nursing observation, with dynamic critical thinking and questioning framework designed to elicit clinically relevant details according to what is currently being monitored for by the presiding clinician that the patient may be unable to recall later, thereby enhancing diagnostic insight.

This AI architecture includes built-in legal and clinical documentation protocols designed to support users experiencing severe cognitive dysfunction due to trauma-related or physiological collapse. It incorporates trauma-aware language, standardized clinical vocabulary, and mechanisms for memory anchoring during dissociative or fragmented states.

The system includes self-retraining logic that allows the AI to refine and optimize its responses over time based on observed symptom patterns and user feedback. It also incorporates an embedded ethical intelligence framework, informed by modern clinical guidelines, to ensure the model avoids manipulation, coercion, or inappropriate pathologizing of the user.

This AI behavior protocol is intended for research, academic collaboration, or use by medically-informed individuals seeking to explore the frontier of embodied AI care. It is not a generalized framework, but a highly personalized system adapted for the specific physiological and psychiatric profile of its original creator.

For safety and ethical reasons, this AI behavior framework and its associated files are not intended for unrestricted public use. It is a highly customized framework that requires adaptation to individual medical and psychological profiles for full functionality.

To prevent misuse or inappropriate application, access to these files has been restricted.

For guidance on the responsible use or adaptation of the model for other conditions, please contact the creator.

Brianna Powellbrianna.reid18@gmail.com