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Automated Closed-loop Stimulation to Inhibit Neurogenic Bladder Overactivity

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Date 2023 May 3
PMID 37132028
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Abstract

Individuals with spinal cord injury (SCI) usually develop neurogenic detrusor overactivity (NDO), resulting in bladder urgency and incontinence, and reduced quality of life. Electrical stimulation of the genital nerves (GNS) can inhibit uncontrolled bladder contractions in individuals with SCI. An automated closed-loop bladder neuromodulation system currently does not exist but could improve this approach. We have developed a custom algorithm to identify bladder contractions and trigger stimulation from bladder pressure data without need for abdominal pressure measurement. The goal of this pilot study was to test the feasibility of automated closed-loop GNS using our custom algorithm to identify and inhibit reflex bladder contractions in real time. Experiments were conducted in a single session in a urodynamics laboratory in four individuals with SCI and NDO. Each participant completed standard cystometrograms without and with GNS. Our custom algorithm monitored bladder vesical pressure and controlled when GNS was turned on and off. The custom algorithm detected bladder contractions in real time, successfully inhibiting a total of 56 contractions across all four subjects. There were eight false positives, six of those occurring in one subject. It took approximately 4.0 ± 2.6 s for the algorithm to detect the onset of a bladder contraction and trigger stimulation. The algorithm maintained stimulation for approximately 3.5 ± 1.7 s, which was enough to inhibit activity and relieve feelings of urgency. Automated closed-loop stimulation was well-tolerated and subjects reported that algorithm decisions generally matched with their perceptions of bladder activity. The custom algorithm automatically, successfully identified bladder contractions to trigger stimulation to inhibit bladder contractions acutely. Closed-loop neuromodulation using our custom algorithm is feasible, but further testing is needed refine this approach for use in a home environment.

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