# Fecobionics monitoring and prediction of biofeedback therapy outcome in patients with obstructed defecation.

> **NIH NIH R01** · CALIFORNIA MEDICAL INNOVATIONS INSTITUTE · 2023 · $370,000

## Abstract

ABSTRACT
Defecatory disorders affect 25% of the population and they are poorly recognized and treated. The incidence of
defecatory disorders including chronic constipation is rising and it poses a major healthcare burden. The
underlying mechanisms for these disorders are often not well understood. Obstructed defecation (dyssynergia)
has several causes and is subdivided in four subtypes. Despite the high prevalence and incidence, diagnostics and
treatment options are sparse. A significant problem in anorectal physiology testing is a lack of physiologically
relevant and practical diagnostic test for identifying the underlying mechanisms to identify proper treatment.
Current diagnostic tests provide incomplete and often conflicting information because they do not simulate feces
or the defecation process. Not surprisingly, results of these tests correlate poorly with symptoms and treatment
outcomes. Biofeedback therapy is a well-established therapy for obstructed defecation but despite the substantial
potential and promising results, biofeedback therapy is only done at specialized centers and should be advanced closer
to the point of care. The objective of this small R01 proposal is to monitor and predict the outcome of biofeedback
therapy based on unprecedented integrated visual feedback from the novel simulated feces device termed Fecobionics.
The device is electronic simulated feces that has the consistency and shape of normal stool. Fecobionics will
provide mechanistic understanding of defecation for the examiner by visualizing the geometric (cross-sectional
area, bending and shape of device) and manometric profiles of the simulated feces before and during defecation.
The central hypothesis is that the Fecobionics device that mimics natural dynamic defecation provides valid
data on rectal emptying attempts for the various components of the defecatory system such as the tone of anal
sphincters and puborectalis muscle, and on mechanosensory properties. The objective is to monitor and predict
biofeedback therapy based on mechanism-based and highly integrated data that can be visualized during
anorectal neuromuscular exercises. For the proposed studies, we will select dyssynergia patients, who will be
monitored with Fecobionics before, during and after biofeedback therapy. The hypothesis is Fecobionics data
will correlate better to symptoms based on constipation scores than conventional technologies and that such
data can be used to predict responders and non-responders to therapy. Our proposal seeks to shift current
research in constipation therapy by use of a novel device that provides mechanistic insights by simulating
defecation pathophysiologically and examining the mechanistic changes multi-dimensionally: Pressure,
deformability, biomechanics, and topographic changes to monitor underlying defects in patients with obstructed
defecation, especially in dyssynergia. The unique aspects of our proposal are to simulate stool with a bionics
device that...

## Key facts

- **NIH application ID:** 10568352
- **Project number:** 1R01DK134689-01
- **Recipient organization:** CALIFORNIA MEDICAL INNOVATIONS INSTITUTE
- **Principal Investigator:** Hans Gregersen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $370,000
- **Award type:** 1
- **Project period:** 2023-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10568352

## Citation

> US National Institutes of Health, RePORTER application 10568352, Fecobionics monitoring and prediction of biofeedback therapy outcome in patients with obstructed defecation. (1R01DK134689-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10568352. Licensed CC0.

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