A Virtual Experiment Generator to Replicate Cardiovascular Responses to Acute Mental Stress and Transcutaneous Median Nerve Stimulation
Year: 2025
Type: article
Abstract: Cardiovascular arousal to acute mental stressors (AMSs) poses significant risks to health and contributes to cardiovascular and neurological disorders. Transcutaneous median nerve stimulation (TMNS) is an emerging noninvasive intervention with the potential to enable just-in-time mitigation of cardiovascular arousal to acute mental stressors. However, no prior work has addressed how to best control TMNS for this purpose. A critical limitation is the lack of basic knowledge of the dynamics between acute mental stressors and TMNS versus cardiovascular arousal. As an initial step toward investigating closed-loop controlled just-in-time TMNS for mitigating cardiovascular arousal to acute mental stressors, we developed and evaluated a data-driven virtual experiment generator (VEG) which can replicate the dynamics between acute mental stressors and TMNS versus cardiovascular arousal. In terms of a novel synthetic multimodal variable (SMV) intended to serve as feedback for just-in-time TMNS, we derived a fourth-order linear decoupled multi-input-single-output (MISO) representation to replicate the dynamics between acute mental stressors and TMNS as inputs versus SMV as output using data collected from 23 experiments. The representation could (i) replicate SMV responses in all experiments when parameterized with the experiment-specific parametric probability density functions (PDFs) and (ii) generate plausible virtual experiments when parameterized with the experiment-aggregated parametric PDFs. In sum, the VEG has the potential as a virtual platform to develop and evaluate closed-loop controlled just-in-time TMNS for mitigating acute mental stressor-induced cardiovascular arousal with SMV as feedback.
DOI: 10.1115/1.4070030
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funder: Office of Naval Research
Awards: G2034378306, G8876996369
OpenAlex ID: W4414815402
