Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: May 20, 2020
Date Accepted: Jul 26, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Investigating Digital Cardiovascular Biomarker Responses to Transcutaneous Cervical Vagus Nerve Stimulation: State-Space Modeling, Prediction, and Simulation
ABSTRACT
Background:
Transcutaneous cervical vagus nerve stimulation (tcVNS) is a promising alternative to implantable stimulation of the vagus nerve. With demonstrated potential in myriad applications ranging from systemic inflammation reduction to traumatic stress attenuation, closed-loop tcVNS during periods of risk could improve treatment efficacy and reduce ineffective delivery.
Objective:
Accomplishing this, however, requires a deeper understanding of biomarker changes in time. We thus elucidate herein the dynamics of relevant cardiovascular biomarkers – extracted from wearable sensing modalities – in response to tcVNS.
Methods:
In 24 human subjects undergoing a randomized double-blind clinical protocol, electrocardiography (ECG) and photoplethysmography (PPG) were used to measure heart rate (HR) and PPG amplitude responses to tcVNS. Modeling these responses in state-space, we (1) compared the biomarkers in predictability and active vs. sham differentiation, (2) studied the latency between stimulation onset and measurable effects, and (3) visualized the true and model-simulated biomarker responses to tcVNS.
Results:
The models predict approximately 80% of the variability observed. Moreover, (1) we find that PPG amplitude demonstrates superiority to HR (P = .03) in both of the aforementioned comparisons, (2) a consistent delay of > 5 s is quantified between tcVNS onset and cardiovascular effects, and (3) dynamic characteristics differentiate responses to tcVNS from sham.
Conclusions:
This work furthers the state of the art by modeling pertinent biomarker responses to tcVNS. Through subsequent analysis, we observe three key findings with implications involving wearable sensing for bioelectronic medicine, the dominant mechanism of action for tcVNS-induced effects on cardiovascular physiology, and the existence of dynamic biomarker signatures that can be leveraged to titrate therapy in closed-loop. Clinical Trial: ClinicalTrials.gov identifier NCT02992899
Citation
