Wear a soft abdominal patch
Proposed to capture abdominal sound activity during intended wear periods, using a soft patch format that still needs bench, comfort, and real-world signal validation.
AGNI BY ANTRAM · INVESTIGATIONAL WEARABLE CONCEPT
Your gut has a signal.
You've just never seen it.
AGNI is a proposed soft abdominal patch designed to study gut-sound activity during intended wear periods and place it beside lightweight meal, symptom, sleep, stress, and routine context. The aim is to reduce guesswork, not remove every note or identify a trigger meal.
Research-first Early cohort forming Not diagnostic
START WHERE YOU ARE
What would you like to understand better?
01BloatingNotice when fullness or pressure appears and what surrounds it.2 min
02ConstipationBuild a clearer view of rhythm, difficulty, routine, and context.2 min
03Energy & foodExplore how energy windows line up with meals and the rest of your day.2 min
04Food responseMove from isolated food guesses to repeatable meal-context notes.2 min
Symptoms are episodic, delayed, and easy to misattribute to the wrong meal.
Your digestion still lives mostly in memory.
AGNI is being built to help change that — not by watching for disease, but by pairing signal with context.
HOW IT IS INTENDED TO WORK
Wear the context.
Keep living.
Add the moments that matter
Brief meal and symptom notes can turn signal data into a record you can revisit, with timestamps that help compare what happened around the same day.
Review patterns, not verdicts
See recurring timing and context while staying clear about uncertainty and the limits of general-wellness information.
THE PRODUCT HYPOTHESIS
A record that keeps the context attached.
AGNI is being designed around timing, context, and repeatable observations, not a one-number verdict.
Investigational signal record
Explore whether abdominal-sound activity can be captured repeatedly during ordinary life.
Meal & routine context
Keep meal timing, portion, hydration, movement, and daily routine beside a symptom record.
Focused check-ins
Use a short reflection to decide what pattern is worth tracking next without naming a cause.
Pattern review
Compare repeated observations over time and bring a more useful record into a clinician conversation when needed.
THREE WAYS TO LEARN
A record is more useful when the context stays attached.
ApproachWhen you learnWhat it capturesLimitation
AGNI conceptDuring intended wear periodsInvestigational signals plus user-entered contextStill requires prospective validation
Manual diaryWhen you remember to logWhat you choose to write downEffort and recall can reduce detail
One-off testAt one point in timeA specific sample or measurementDoes not show the full daily context
THE SCIENCE
Promising signals.
Claims still to earn.
Published work shows that abdominal sounds can be captured and analysed, while systematic reviews also highlight small samples, variable methods, and limited real-world validation. That is the boundary ANTRAM intends to test, not hide.
- Bench and tissue-path testing
- Artefact and repeatability studies
- Human feasibility and comfort studies
- Prospective usefulness validation
WHAT AGNI MUST PROVE
Capture. Repeat. Compare. Validate.
01Bench & tissue-path tests02Artefact & repeatability03Human feasibility & comfort04Prospective usefulness
Any future sensor-derived metric or algorithm requires its own protocol, reference standard, predefined endpoint, error analysis, and external validation. Full roadmap
RESEARCH LIBRARY / CREDIT WHERE IT IS DUE
Built on published work.
Bound by its limits.
These independent studies shape ANTRAM's research questions. None validates AGNI itself, and no reported performance should be interpreted as AGNI performance.
Measuring Diet Intake and Gastrointestinal Symptoms in IBS
Wright-McNaughton et al. validated the FAST diary for contemporaneous food and symptom recording in 51 people with IBS.
PubMed · PMID 31800544Diagnostic Accuracy of Computerized Bowel Sound Analysis
Huang et al. found promising results but only 4 eligible studies, with important concerns about validity and applicability.
PubMed · PMID 38594814SonicGuard: A Multichannel Acoustic Sensor
Mansour et al. evaluated long-duration abdominal sound capture across laboratory, phantom, and small human tests.
PubMed · PMID 38544106Computerised Analysis of Bowel Sounds
Inderjeeth et al. mapped associations between bowel-sound features and GI conditions while highlighting heterogeneity.
PubMed · PMID 30115115Bristol Stool Form Scale Reliability
Chumpitazi et al. examined how reliably adults and children classify stool form, including weaker agreement at category boundaries.
PubMed · PMID 26690980Flexible Mechano-Acoustic Sensors for Body Sounds
Dang et al. reviewed flexible wearable sensing approaches and the remaining path from signal capture to health application.
PubMed · PMID 40145538Our evidence rule: cite the source, name the limitation, and never borrow another device's result.
View all evidence & creditsQUESTIONS
The product, the evidence, the boundaries.
What is AGNI?
AGNI is ANTRAM’s in-development gut-health and nutrition wearable concept. It is being designed to place investigational abdominal signals beside the meals, symptoms, and routines that shape everyday life.
What can I do with AGNI today?
Today, you can use the short check-ins to identify a starting pattern worth observing. The wearable, signal capture, and longitudinal review experience are still in development.
What is the wearable intended to capture?
ANTRAM is investigating whether a soft abdominal wearable can repeatedly capture abdominal-sound activity during daily life. Signal quality, comfort, algorithms, and useful outputs all require validation.
How is AGNI different from a symptom diary or one-off test?
The product hypothesis is to connect passive, investigational sensing with a light context record over time. A manual diary depends on memory and effort; a one-off test captures only one point in time. AGNI must still prove that this approach produces useful information.
Can AGNI diagnose a condition or identify a trigger food?
No. A repeated association can suggest a better question to investigate, but it cannot prove a cause, intolerance, or medical condition.
Who should not rely on this instead of medical care?
Anyone with severe, sudden, or worsening symptoms — or with a condition like IBD that requires clinical monitoring — should not substitute a check-in or wearable for a doctor. See the gut health library for guidance on which conditions need a clinician, not an app.
What research is this based on?
Published work supports studying contemporaneous symptom diaries and abdominal acoustic sensing, but it does not validate AGNI. We publish the sources, their limitations, and the validation work still required in the research library.
EARLY ACCESS
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