Comparison between uroflowmetry and sonouroflowmetry in recording of urinary flow in healthy men

Krhút, Jan; Gärtner, Marcel; Sýkora, Radek; Hurtík, Petr; Burda, Michal; Luňáček, Libor; Zvarová, Katarína; Zvara, Peter

doi:10.1111/iju.12796

Cited by 23 publications

(37 citation statements)

References 5 publications

(13 reference statements)

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“…In their study using 25 male volunteers, the flow pattern showed a good visual correlation between the 2 methods. However, Qmax showed a weak correlation (PCC = 0.38) and Qavg, voided volume showed moderate correlation (PCC = 0.57 and PCC = 0.68, respectively) [8]. In female patients, Qmax showed a weak correlation between uroflowmetry and sonouroflowmetry (PCC = 0.38) [9] after analyzing 183 re-cordings of 36 healthy female volunteers.…”

Section: Discussionmentioning

confidence: 94%

“…Sound-based analysis of uroflowmetry has been tried previously. The technical concept of sonouroflowmetry was introduced in 2009 [3] and clinical trials of sonouroflowmetry in male and female patients were reported in 2015 and 2016, respectively [8,9]. In their study using 25 male volunteers, the flow pattern showed a good visual correlation between the 2 methods.…”

Section: Discussionmentioning

confidence: 99%

“…In their initial feasibility study, they found similar flow curves among men, despite subtle differences in the voiding time and flow rates compared to standard uroflowmetry [8,9].…”

Section: Original Articlementioning

confidence: 96%

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A Novel Mobile Acoustic Uroflowmetry: Comparison With Contemporary Uroflowmetry

et al. 2021

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This study aimed to evaluate the accuracy and reliability of a new smartphone-based acoustic uroflowmetry compared to conventional uroflowmetry. Methods: This was a prospective validation study enrolling 128 subjects from September 2017 to April 2018 comparing a novel acoustic uroflowmetry to conventional uroflowmetry in an outpatient urologic clinic at Seoul National University Bundang Hospital. Visual comparison of flow patterns and uroflow parameters such as maximum flow rate (Qmax), average flow rate (Qavg), and voided volume were compared between the 2 techniques. Reliability and accuracy of the uroflowmetry results were compared using Pearson correlation coefficient (PCC) and Student t-test, respectively. Results: One hundred twelve participants were included in the study. Of these, 77 had baseline urologic comorbidities while 35 were normal participants. Flow patterns between the 2 uroflowmetry techniques demonstrated strong visual correlation. When compared to conventional uroflowmetry, all 3 parameters of voiding in male participants showed a very robust correlation with PCC of 0.88, 0.91, and 0.95 for Qmax, Qavg, and voided volume, respectively. Among female participants, we observed a PCC of 0.78, 0.93, and 0.96 for Qmax, Qavg, and voided volume, respectively. The Qmax showed a statistically significant difference in both sexes between the 2 methods, although the absolute value was small. Conclusions: Uroflowmetry using acoustic analysis demonstrates comparable findings to conventional uroflowmetry. This provides an opportunity to perform uroflowmetry in the clinic or at home in a reliable, inexpensive manner. Future large-scale prospective studies are required to further validate our results.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

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A Novel Mobile Acoustic Uroflowmetry: Comparison With Contemporary Uroflowmetry

et al. 2021

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“…For example, an extendable wand can deploy the urinalysis strip toward the potential location of the female urine stream. Another approach for implementing the uroflowmetry module is sonouroflowmetry, which uses sound to estimate the urine flow rate and volume 60 . Sonouroflowmetry can be implemented for both male and female users, in sitting or standing positions, while avoiding optical scans of the user's body parts.…”

Section: Current Limitationsmentioning

confidence: 99%

A mountable toilet system for personalized health monitoring via the analysis of excreta

et al. 2020

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Technologies for the longitudinal monitoring of a person's health are poorly integrated with clinical workflows, and have rarely produced actionable biometric data for healthcare providers. Here, we describe easily deployable hardware and software for the long-term analysis of a user's excreta through data collection and models of human health. The 'smart' toilet, which is selfcontained and operates autonomously by leveraging pressure and motion sensors, analyses the user's urine using a standard-of-care colorimetric assay that traces red-green-blue values from images of urinalysis strips, calculates the flow rate and volume of urine using computer vision as a uroflowmeter, and classifies stool according to the Bristol stool form scale using deep learning, with performance that is comparable to the performance of trained medical personnel. Each user of the toilet is identified through their fingerprint and the distinctive features of their anoderm, and the data are securely stored and analysed in an encrypted cloud server. The toilet may find uses in the screening, diagnosis and longitudinal monitoring of specific patient populations.

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“…An artificial spike of high‐intensity sound, which occurred at the beginning of each recording, was detected and eliminated. Subsequently, the matching datasets of UF and SUF were compared with respect to the following parameters: flow time recorded using UF was compared to the duration of the sound signal recorded by SUF; UF recorded voided volume was compared to the calculated area under the SUF curve; and UF recorded maximal flow rate (Q max ) was compared to the peak intensity of the sound signal …”

Section: Methodsmentioning

confidence: 99%