Litcius/Paper detail

Precise control of tibial nerve stimulation for bladder regulation via evoked compound action potential feedback mechanisms

Young-Soo Lim, Ji Hong Kim, Junho Kim, MinhDuc Hoang, Wonok Kang, Mattew Koh, Won Hyuk Choi, Steve Park, Unyong Jeong, Do Hwan Kim, Sung‐Min Park, Sung‐Min Park, Sung‐Min Park

2025Nature Communications14 citationsDOIOpen Access PDF

Abstract

Optimizing stimulation protocols for peripheral neuromodulation often depends on patient feedback, which can result in inconsistent clinical outcomes. Here we present a closed-loop control system for peripheral nerve stimulation (PNS) that utilizes evoked compound action potential (ECAP) feedback to regulate stimulation parameters, addressing the limitations of traditional methods. Unlike established closed-loop control techniques in the central nervous system, such as local field potential and spike analysis, a comparable approach for the peripheral nervous system remains underdeveloped. ECAPs can be consistently observed across peripheral nerves, providing a reliable measure of nerve activation. We developed a fully implantable device and neural interface for tibial nerve stimulation (TNS) that incorporates the proposed closed-loop system. This TNS system shows promise as a PNS treatment for alleviating overactive bladder symptoms. In a rat model, the system demonstrated longer micturition intervals and greater effectiveness compared to conventional motor response-based control. Precise control is essential for effective neuromodulation. Here, the authors present an evoked compound action potential-based control system and demonstrate its efficacy in tibial nerve stimulation compared to empirical methods, offering a foundation for quantitative closed-loop control

Topics & Concepts

StimulationCompound muscle action potentialAction (physics)NeuroscienceTibial nerveNerve stimulationMedicineComputer scienceElectrophysiologyBiologyPhysicsQuantum mechanicsVagus Nerve Stimulation ResearchUrinary Bladder and Prostate ResearchNeuroscience and Neural Engineering