A mathematical model of bowel sound generation

Du, Xuhao; Allwood, Gary; Webberley, K. Mary; Osseiran, Adam; Wan, Wenchao; Volikova, Antonina I; Marshall, Barry J.

doi:10.1121/1.5080528

Cited by 14 publications

(18 citation statements)

References 20 publications

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“…The most frequent type of BS in the recordings was the SB, which is a simple pulse probably caused by a single contraction of the bowel muscle [25,28,29]. An SB, with its distinctive peak frequencies, is noticeable in the time domain.…”

Section: Resultsmentioning

confidence: 99%

“…Ulusar recognized BS as single bursts and multiple bursts based on their waveform to build a BS classification model using Bayesian theory. Du et al also proposed a mathematical model for BS generation to explain different types of BS [28]. As summarized above, there are several classifications of BS based on different sound characteristics, and the quantities of different types of BS were not studied in their work.…”

Section: Introductionmentioning

confidence: 99%

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Bowel Sounds Identification and Migrating Motor Complex Detection with Low-Cost Piezoelectric Acoustic Sensing Device

Allwood

Webberley

et al. 2018

Sensors

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Interpretation of bowel sounds (BS) provides a convenient and non-invasive technique to aid in the diagnosis of gastrointestinal (GI) conditions. However, the approach’s potential is limited by variation between BS and their irregular occurrence. A short, manual auscultation is sufficient to aid in diagnosis of only a few conditions. A longer recording has the potential to unlock additional understanding of GI physiology and clinical utility. In this paper, a low-cost and straightforward piezoelectric acoustic sensing device was designed and used for long BS recordings. The migrating motor complex (MMC) cycle was detected using this device and the sound index as the biomarker for MMC phases. This cycle of recurring motility is typically measured using expensive and invasive equipment. We also used our recordings to develop an improved categorization system for BS. Five different types of BS were extracted: the single burst, multiple bursts, continuous random sound, harmonic sound, and their combination. Their acoustic characteristics and distribution are described. The quantities of different BS during two-hour recordings varied considerably from person to person, while the proportions of different types were consistent. The sensing devices provide a useful tool for MMC detection and study of GI physiology and function.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bowel Sounds Identification and Migrating Motor Complex Detection with Low-Cost Piezoelectric Acoustic Sensing Device

Allwood

Webberley

et al. 2018

Sensors

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“…Two key features were related to the rate of contraction and the motility of the gut, the component interval time, and the burst number. These have been described previously in our mathematical model of bowel sound generation (20). Amplitude during the fasting recording was also an important feature.…”

Section: Resultsmentioning

confidence: 99%

“…However, our recordings were much longer, and we used a much broader range of features (8 time-domain and 18 frequency-domain features) in the final model (26). Sounds are generated as the contents move through the entire length of the digestive system, especially by the movement of gases through valves (20,28). Given that IBS corresponds with changes in gut motility, the amount of water, and the gases in the contents, it is unsurprising that a variety of sound features characterize this condition.…”

Section: Discussionmentioning

confidence: 99%

“…Subsequently, frequency-domain and time-domain features were extracted from each bowel sound, and the approximate location of origin of each bowel sound was determined. The features included many previously identified in the medical (18) and biomedical engineering literature (19) and novel features we developed through our modeling of bowel sound generation (20). The basic process flow of the methodology for gathering the data and creating a machine learning model is presented in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

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Noninvasive Diagnosis of Irritable Bowel Syndrome via Bowel Sound Features: Proof of Concept

Allwood

Webberley

et al. 2019

Clin Transl Gastroenterol

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INTRODUCTION: Irritable bowel syndrome (IBS) is a common and debilitating disorder estimated to affect approximately 11% of the world's population. Typically, IBS is a diagnosis of exclusion after patients undergo a costly and invasive colonoscopy to exclude organic disease. Clinician's and researchers have identified a need for a new cost-effective, accurate, and noninvasive diagnostic test for IBS. METHODS: Using a diagnostic case-control study, we explored the use of bowel sounds to characterize IBS with a view to diagnostic use. We recruited participants with an existing clinical diagnosis of IBS or healthy (asymptomatic) digestive systems. We recorded bowel sounds for 2 hours after fasting and then for 40 minutes after a standard meal. RESULTS: We here report our results including our accuracy in characterizing IBS-related bowel sounds and differentiation between participants with IBS and healthy participants. Leave-one-out cross-validation of our model developed using the first 31 IBS and 37 healthy participants gave 90% sensitivity and 92% specificity for IBS diagnosis. Independent testing using the next 15 IBS and 15 healthy participants demonstrated 87% sensitivity and 87% specificity for IBS diagnosis. CONCLUSIONS: These preliminary results provide proof of concept for the use of bowel sound analysis to identify IBS. A prospective study is needed to confirm these findings. TRANSLATIONAL IMPACT: Our belt and model offer hope of a new approach for IBS diagnosis in primary practice. Combined with screening tests for organic disease, it would offer greater confidence to patients and could reduce the burden of unnecessary colonoscopies for health care systems and patients.

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A Laboratory Set-up for the Multisystem Body Sounds Measurement: a Feasibility Study

Jablonski

2021

IFAC-PapersOnLine

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A mathematical model of bowel sound generation

Cited by 14 publications

References 20 publications

Bowel Sounds Identification and Migrating Motor Complex Detection with Low-Cost Piezoelectric Acoustic Sensing Device

Bowel Sounds Identification and Migrating Motor Complex Detection with Low-Cost Piezoelectric Acoustic Sensing Device

Noninvasive Diagnosis of Irritable Bowel Syndrome via Bowel Sound Features: Proof of Concept

A Laboratory Set-up for the Multisystem Body Sounds Measurement: a Feasibility Study

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