TY - JOUR
T1 - Practicing Digital Gastroenterology through Phonoenterography Leveraging Artificial Intelligence
T2 - Future Perspectives Using Microwave Systems
AU - Redij, Renisha
AU - Kaur, Avneet
AU - Muddaloor, Pratyusha
AU - Sethi, Arshia K.
AU - Aedma, Keirthana
AU - Rajagopal, Anjali
AU - Gopalakrishnan, Keerthy
AU - Yadav, Ashima
AU - Damani, Devanshi N.
AU - Chedid, Victor G.
AU - Wang, Xiao Jing
AU - Aakre, Christopher A.
AU - Ryu, Alexander J.
AU - Arunachalam, Shivaram P.
N1 - Funding Information:
This work was supported by the Advanced Analytics and Practice Innovation unit for Artificial Intelligence and Informatics research within the Department of Medicine, Mayo Clinic, Rochester, MN USA. This work was also supported by the GIH Division for the GIH Artificial Intelligence Laboratory (GAIL) and Microwave Engineering and Imaging Laboratory (MEIL), Department of Medicine, Mayo Clinic, Rochester, MN USA.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - Production of bowel sounds, established in the 1900s, has limited application in existing patient-care regimes and diagnostic modalities. We review the physiology of bowel sound production, the developments in recording technologies and the clinical application in various scenarios, to understand the potential of a bowel sound recording and analysis device—the phonoenterogram in future gastroenterological practice. Bowel sound production depends on but is not entirely limited to the type of food consumed, amount of air ingested and the type of intestinal contractions. Recording technologies for extraction and analysis of these include the wavelet-based filtering, autoregressive moving average model, multivariate empirical mode decompression, radial basis function network, two-dimensional positional mapping, neural network model and acoustic biosensor technique. Prior studies evaluate the application of bowel sounds in conditions such as intestinal obstruction, acute appendicitis, large bowel disorders such as inflammatory bowel disease and bowel polyps, ascites, post-operative ileus, sepsis, irritable bowel syndrome, diabetes mellitus, neurodegenerative disorders such as Parkinson’s disease and neonatal conditions such as hypertrophic pyloric stenosis. Recording and analysis of bowel sounds using artificial intelligence is crucial for creating an accessible, inexpensive and safe device with a broad range of clinical applications. Microwave-based digital phonoenterography has huge potential for impacting GI practice and patient care.
AB - Production of bowel sounds, established in the 1900s, has limited application in existing patient-care regimes and diagnostic modalities. We review the physiology of bowel sound production, the developments in recording technologies and the clinical application in various scenarios, to understand the potential of a bowel sound recording and analysis device—the phonoenterogram in future gastroenterological practice. Bowel sound production depends on but is not entirely limited to the type of food consumed, amount of air ingested and the type of intestinal contractions. Recording technologies for extraction and analysis of these include the wavelet-based filtering, autoregressive moving average model, multivariate empirical mode decompression, radial basis function network, two-dimensional positional mapping, neural network model and acoustic biosensor technique. Prior studies evaluate the application of bowel sounds in conditions such as intestinal obstruction, acute appendicitis, large bowel disorders such as inflammatory bowel disease and bowel polyps, ascites, post-operative ileus, sepsis, irritable bowel syndrome, diabetes mellitus, neurodegenerative disorders such as Parkinson’s disease and neonatal conditions such as hypertrophic pyloric stenosis. Recording and analysis of bowel sounds using artificial intelligence is crucial for creating an accessible, inexpensive and safe device with a broad range of clinical applications. Microwave-based digital phonoenterography has huge potential for impacting GI practice and patient care.
KW - artificial intelligence
KW - bowel sounds
KW - computer-aided auscultation
KW - digital health
KW - gastroenterology
KW - microwave acoustic sensors
KW - microwave telemetry
KW - PEG
KW - phonoenterogram
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U2 - 10.3390/s23042302
DO - 10.3390/s23042302
M3 - Review article
C2 - 36850899
AN - SCOPUS:85148973227
SN - 1424-3210
VL - 23
JO - Sensors
JF - Sensors
IS - 4
M1 - 2302
ER -