96% proven accuracy in measuring voided volume through extensive research
On the accuracy of Bladderly’s sound-based voided volume measurement.
96% proven accuracy through extensive research
Validation of an algorithm for sound-based voided volume estimation
Accurate tracking of patients' urinary patterns is critical for diagnosis and treatment of lower urinary tract symptoms (LUTS), allowing healthcare providers to monitor progress, adjust treatment plans as needed, and optimize patient outcomes. Bladder diaries are an essential tool for this, as recommended by urology guidelines. However, traditional paper diaries-measure and log urine volume using a measuring cup- which leads to:
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Poor compliance due to the inconvenience of using a voiding cup.
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Inaccurate data from human error and lack of standardized tools
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Subjective readings often result in errors of ±50-100mL
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Low compliance rates: as low as 50% due to the inconvenience of manual logging (Source)
*Palnaes & Klarskov, 1994 - This study is mentioned in the original text as the source for the subjective readings error range of ±50-100mL.
As a result, they have limited accuracy, making it difficult to assess patient patterns and limiting evidence-based diagnosis and follow-up.
A Better Solution: Sound-Based Voided Volume Measurement
Bladderly takes a completely different approach. Instead of asking you to measure anything, our app simply listens to the sound of urination and uses advanced technology to calculate the volume automatically.
How We Validated Our Technology
We conducted rigorous testing to ensure Bladderly's measurements are trustworthy:
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Large-scale testing: We collected data from 508 participants, generating 584 valid measurements
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Advanced AI analysis: We used artificial intelligence (specifically a 2D-CNN model) to analyze sound patterns from urination
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Scientific validation method: We compared our sound-based measurements against precise weight-based measurements (the gold standard)
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Cross-validation: We used fivefold cross-validation to ensure consistent performance
What Our Research Found
The results exceeded our expectations:
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Strong correlation: 0.92 correlation with weight-based measurements (p < 0.001)
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Excellent accuracy: Measurements were within ±10 mL (95% confidence interval)
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Minimal difference: Average difference of just -5.5 mL between methods
To put this in perspective, the standard clinical device used to measure bladder volume (portable bladder scanners) has an average error of 16.7 mL – three times higher than Bladderly's average difference of 5.5 mL.
*D. R. Small - This study is referenced in the original as the source for the measurement error of portable bladder scanners (average difference of 16.7 mL).
Inclusive Technology:
Scientifically Validated for Both Men and Women
Unlike competitors who focus exclusively on men's urinary health, Bladderly was developed with scientific rigor for everyone. We recognize that anatomical differences, urination postures and behaviors significantly affect sound patterns, requiring distinct approaches:
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Gender-specific algorithms: We've developed and validated separate models for both men and women
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Comprehensive data collection: Our research included substantial sample sizes for both genders
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Equal commitment to accuracy: Our technology delivers exceptional precision regardless of gender
This inclusive approach ensures that all users receive equally accurate results, addressing a significant gap in the market where women's urinary health tracking has been historically underserved by technology solutions.
Accuracy of voided volume Estimation by gender
Male
>96%
Female
>94%
Conclusion:
A Smarter Way to Track Urinary Health
Bladderly’s sound-based voided volume estimation offers a clinically proven, user-friendly alternative to traditional voiding diaries. For those managing urinary conditions, monitoring progress, or sharing information with healthcare providers, Bladderly offers clinical-grade accuracy with everyday convenience. Manage your urinary health smartly with Bladderly, a proven solution.
Validation of an algorithm for sound-based voided volume estimation
Published: 02 January 2024
nature.com Scientific Reports volume 14, Article number: 138 (2024)