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Abdominal sounds (ABS) have been traditionally used for assessinggastrointestinal (GI) disorders. However, the assessment requires a trainedmedical professional to perform multiple abdominal auscultation sessions, whichis resource-intense and may fail to provide an accurate picture of patients'continuous GI wellbeing. This has generated a technological interest indeveloping wearables for continuous capture of ABS, which enables a fullerpicture of patient's GI status to be obtained at reduced cost. This paper seeksto evaluate the feasibility of extracting heart rate (HR) from such ABSmonitoring devices. The collection of HR directly from these devices wouldenable gathering vital signs alongside GI data without the need for additionalwearable devices, providing further cost benefits and improving generalusability. We utilised a dataset containing 104 hours of ABS audio, collectedfrom the abdomen using an e-stethoscope, and electrocardiogram as ground truth.Our evaluation shows for the first time that we can successfully extract HRfrom audio collected from a wearable on the abdomen. As heart sounds collectedfrom the abdomen suffer from significant noise from GI and respiratory tracts,we leverage wavelet denoising for improved heart beat detection. The meanabsolute error of the algorithm for average HR is 3.4 BPM with mean directionalerror of -1.2 BPM over the whole dataset. A comparison tophotoplethysmography-based wearable HR sensors shows that our approach exhibitscomparable accuracy to consumer wrist-worn wearables for average andinstantaneous heart rate.

Heart Rate Extraction from Abdominal Audio Signals