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Related Concept Videos

Urinary Bladder01:23

Urinary Bladder

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The urinary bladder is a hollow, muscular sac that temporarily stores urine before it is expelled from the body. It can hold approximately 600 mL of urine prior to micturition. The bladder is retroperitoneal and located behind the pubic symphysis in the pelvic floor.
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Urination, or micturition involves the coordination of the bladder's detrusor muscle and two sphincters to ensure controlled bladder emptying.
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Uroflowmetry is a non-invasive urodynamic test designed to measure various aspects of urination, including volume, flow rate, and the time to void. This test is crucial for diagnosing and assessing conditions such as bladder outlet obstruction, bladder dysfunction, incomplete bladder emptying, incontinence, and urinary tract blockages caused by benign prostatic hyperplasia (BPH) and urethral strictures.Pre-Test Instructions:Before a uroflowmetry test, patients are typically advised to drink...
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Related Experiment Video

Updated: Mar 6, 2026

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device
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Real-time, autonomous bladder event classification and closed-loop control from single-channel pressure data.

Robert Karam, Swarup Bhunia, Steve Majerus

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    Summary
    This summary is machine-generated.

    Context-Aware Thresholding (CAT) accurately detects bladder contractions in real-time for individuals with Spinal Cord Injury (SCI). This technology enables faster, closed-loop bladder control, improving quality of life.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Urology

    Background:

    • Urinary incontinence significantly impacts quality of life globally.
    • Neuromodulation offers treatment for urgency, especially in Spinal Cord Injury (SCI) patients.
    • Current open-loop stimulation systems have limitations; event-driven stimulation requires advanced bladder function classification.

    Purpose of the Study:

    • To present the first real-time detection of multiple bladder contractions using Context-Aware Thresholding (CAT).
    • To evaluate CAT's accuracy, noise tolerance, and speed in human subjects with SCI and Neurogenic Detrusor Overactivity (NDO).
    • To demonstrate autonomous closed-loop bladder control using CAT in a clinical case study.

    Main Methods:

    • Real-time urodynamic data acquisition from human subjects with SCI and NDO.
    • Application of Context-Aware Thresholding (CAT) algorithm for bladder contraction detection.
    • Live closed-loop system implementation for autonomous bladder control.

    Main Results:

    • CAT achieved 92% accuracy with a low false positive rate (0.3/contraction) on 15 subjects' data.
    • CAT detected events 1.4 seconds faster than human experimenters.
    • Successful autonomous closed-loop control inhibited four consecutive bladder contractions and increased bladder capacity by 40% in a case study.

    Conclusions:

    • CAT is a robust, accurate, and noise-tolerant method for real-time bladder contraction detection.
    • This technology enables faster event response compared to manual detection.
    • CAT facilitates autonomous closed-loop bladder control, offering a promising advancement for managing NDO in SCI patients.