Abdominal sounds (ABS) have been traditionally used for assessing
gastrointestinal (GI) disorders. However, the assessment requires a trained
medical professional to perform multiple abdominal auscultation sessions, which
is resource-intense and may fail to provide an accurate picture of patients'
continuous GI wellbeing. This has generated a technological interest in
developing wearables for continuous capture of ABS, which enables a fuller
picture of patient's GI status to be obtained at reduced cost. This paper seeks
to evaluate the feasibility of extracting heart rate (HR) from such ABS
monitoring devices. The collection of HR directly from these devices would
enable gathering vital signs alongside GI data without the need for additional
wearable devices, providing further cost benefits and improving general
usability. We utilised a dataset containing 104 hours of ABS audio, collected
from the abdomen using an e-stethoscope, and electrocardiogram as ground truth.
Our evaluation shows for the first time that we can successfully extract HR
from audio collected from a wearable on the abdomen. As heart sounds collected
from the abdomen suffer from significant noise from GI and respiratory tracts,
we leverage wavelet denoising for improved heart beat detection. The mean
absolute error of the algorithm for average HR is 3.4 BPM with mean directional
error of -1.2 BPM over the whole dataset. A comparison to
photoplethysmography-based wearable HR sensors shows that our approach exhibits
comparable accuracy to consumer wrist-worn wearables for average and
instantaneous heart rate.Comment: ICASSP 202