Digital Cardiovascular Biomarker Responses to Transcutaneous Cervical Vagus Nerve Stimulation: State-Space Modeling, Prediction, and Simulation
| Autor: | Omer T. Inan, Matthew T. Wittbrodt, Asim H. Gazi, Viola Vaccarino, J. Douglas Bremner, Nil Z. Gurel, Amit J. Shah, Kristine L. S. Richardson |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Vagus Nerve Stimulation medicine.medical_treatment Health Informatics 03 medical and health sciences 0302 clinical medicine Double-Blind Method digital biomarkers Heart Rate noninvasive Photoplethysmogram Internal medicine Heart rate bioelectronic medicine Humans Medicine 030304 developmental biology Original Paper 0303 health sciences medicine.diagnostic_test business.industry cardiovascular state space dynamic models Vagus Nerve Neuromodulation (medicine) Vagus nerve Cardiovascular physiology wearable sensing neuromodulation Cardiology biomarker Biomarker (medicine) business Electrocardiography Biomarkers 030217 neurology & neurosurgery Vagus nerve stimulation |
| Zdroj: | JMIR mHealth and uHealth |
| ISSN: | 2291-5222 |
| DOI: | 10.2196/20488 |
| Popis: | BackgroundTranscutaneous 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. However, achieving this requires a deeper understanding of biomarker changes over time.ObjectiveThe aim of the present study was to reveal the dynamics of relevant cardiovascular biomarkers, extracted from wearable sensing modalities, in response to tcVNS.MethodsTwenty-four human subjects were recruited for a randomized double-blind clinical trial, for whom electrocardiography and photoplethysmography were used to measure heart rate and photoplethysmogram amplitude responses to tcVNS, respectively. Modeling these responses in state-space, we (1) compared the biomarkers in terms of their 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.ResultsThe models accurately predicted future heart rate and photoplethysmogram amplitude values with root mean square errors of approximately one-fifth the standard deviations of the data. Moreover, (1) the photoplethysmogram amplitude showed superior predictability (P=.03) and active vs sham separation compared to heart rate; (2) a consistent delay of greater than 5 seconds was found between tcVNS onset and cardiovascular effects; and (3) dynamic characteristics differentiated responses to tcVNS from the sham stimulation.ConclusionsThis work furthers the state of the art by modeling pertinent biomarker responses to tcVNS. Through subsequent analysis, we discovered three key findings with implications related to (1) wearable sensing devices for bioelectronic medicine, (2) the dominant mechanism of action for tcVNS-induced effects on cardiovascular physiology, and (3) the existence of dynamic biomarker signatures that can be leveraged when titrating therapy in closed loop.Trial RegistrationClinicalTrials.gov NCT02992899; https://clinicaltrials.gov/ct2/show/NCT02992899International Registered Report Identifier (IRRID)RR2-10.1016/j.brs.2019.08.002 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|