On-off closed-loop control of vagus nerve stimulation for the adaptation of heart rate

Ugalde, Hector M. Romero; Rolle, Virginie Le; Bel, Alain; Bonnet, Jean‐Luc; Andreu, David; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo

doi:10.1109/embc.2014.6945060

Cited by 14 publications

(5 citation statements)

References 10 publications

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“…Another example of how the framework could be adapted is the inclusion of a closed-loop control mechanism (Bilgutay et al, 1968; Tosato et al, 2006; Ugalde et al, 2014; Ojeda et al, 2016; Mylavarapu et al, 2023). These studies use live monitoring of the RR interval as an input for determining the timing and/or parameters for stimulating the nerve.…”

Section: Discussionmentioning

confidence: 99%

“…These studies use live monitoring of the RR interval as an input for determining the timing and/or parameters for stimulating the nerve. In this case, specific delays from R peaks in the ECG as seen in studies by Ojeda et al (2016) and Ugalde et al (2014), could be included in the framework as "train parameters" as timing of the stimulation impacts physiological effects but is not expected to influence evoked neural activity. In this example, an arrow would likely connect the "Physiological Context" box and the "Train Parameter" box depicted in Fig 1A . In addition to adding new stimulation parameters, studying VNS for other chronic conditions would require adding or removing physiological effects.…”

Section: Adaptability Of Ecapturs Frameworkmentioning

confidence: 99%

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Using neural biomarkers to personalize dosing of vagus nerve stimulation

Berthon,

Wernisch,

Stoukidi

et al. 2023

Preprint

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Background: Vagus nerve stimulation (VNS) is an established therapy for treating a variety of chronic diseases, such as epilepsy, depression, obesity, and for stroke rehabilitation. However, lack of precision and side-effects have hindered its efficacy and extension to new conditions. Objective: To achieve a better understanding of the relationship between VNS parameters and neural and physiological responses to enable the design of personalized dosing procedures to improve precision and efficacy of VNS therapies. Methods: We used biomarkers from recorded evoked neural activity and short-term physiological responses (throat muscle, cardiac and respiratory activity) to understand the response to a wide range of VNS parameters in anaesthetised pigs. Using signal processing, Gaussian processes (GP) and parametric regression models we analyse the relationship between VNS parameters and neural and physiological responses. Results: Firstly, we observe inter-subject variability for both neural and physiological responses. Secondly, we illustrate how considering multiple stimulation parameters in VNS dosing can improve the efficacy and precision of VNS therapies. Thirdly, we describe the relationship between different VNS parameters and the evoked neural activity and show how spatially selective electrodes can be used to improve fibre recruitment. Fourthly, we provide a detailed exploration of the relationship between the activations of neural fibre types and different physiological effects, and show that recordings of evoked neural activity are powerful biomarkers for predicting the short-term physiological effects of VNS. Finally, based on these results, we discuss how recordings of evoked neural activity can help design VNS dosing procedures that optimize short-term physiological effects safely and efficiently. Conclusion: Understanding of evoked neural activity during VNS provide powerful biomarkers that could improve the precision, safety and efficacy of VNS therapies.

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Section: Discussionmentioning

confidence: 99%

Section: Adaptability Of Ecapturs Frameworkmentioning

confidence: 99%

Using neural biomarkers to personalize dosing of vagus nerve stimulation

Berthon,

Wernisch,

Stoukidi

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…There has been an emerging interest in using closed-loop neuro-stimulation to achieve targeted control of cardiac parameters [ 38 ]. In fact, significant developments have been made in this area based on state transition models where an algorithm optimally selects the VNS parameters to regulate instantaneous HR synchronously with cardiac cycles [ 39 ].…”

Section: Discussionmentioning

confidence: 99%

Stochastic vagus nerve stimulation affects acute heart rate dynamics in rats

et al. 2018

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Vagus nerve stimulation (VNS) is an approved therapy for treatment of epilepsy and depression. While also shown to be promising in several preclinical and clinical studies to treat cardiovascular diseases, optimal therapeutic stimulation paradigms are still under investigation. Traditionally, parameters such as frequency, current, and duty cycle are used to adjust the efficacy of VNS therapy. This study explored the effect of novel stochastic VNS (S-VNS) on acute heart rate (HR) dynamics. The effect of S-VNS was evaluated in Sprague Dawley rats by comparing the acute HR and HR variability (HRV) responses to standard, periodic VNS (P-VNS) across different frequencies (FREQs, 10–30 Hz). Our results demonstrate that both S-VNS and P-VNS produced negative chronotropic effects in a FREQ-dependent manner with S-VNS inducing a significantly smaller drop in HR at 10 Hz and 20 Hz compared to P-VNS (p<0.05). S-VNS demonstrated a FREQ-dependent drop in the SD1/SD2 ratio, a measure of HRV, which was absent in P-VNS, suggesting that S-VNS may acutely modulate the nonlinear relationship between short- and long-term HRV. In conclusion, S-VNS is a novel stimulation procedure that may provide different physiological outcomes from standard P-VNS, as indicated by our analysis of HR dynamics. Our study provides a rationale for further detailed investigations into the therapeutic potential of S-VNS as a novel neuromodulation technique.

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“…This closed-loop system was used to determine the hemodynamic changes at each level of ventricular rate and to establish the optimal anterograde ventricular rate during atrial fibrillation. More recently, a VNS closed-loop control system was proposed in order to regulate the heart rate of a sheep with induced HF on a beat-tobeat basis (Ugalde et al, 2014), but due to hardware constraints of the neuromodulator, only an on-off approach was implemented. The experimental results confirmed that the closed-loop VNS with the tested parameter configurations significantly modified the spontaneous RR interval.…”

Section: Closed Loop Control In Hfmentioning

confidence: 99%