Segment-Based Spotting of Bowel Sounds Using Pretrained Models in Continuous Data Streams
Author:
Affiliation:
1. University of Freiburg, Freiburg, Germany
2. Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
3. I. Medical Clinic & Deutsches Zentrum Immuntherapie DZI, University Hospital Erlangen, Erlangen, Germany
Funder
Erlangen National High Performance Computing Center
Friedrich-Alexander-Universität Erlangen-Nürnberg
NHR
federal and Bavarian state authorities
Deutsche Forschungsgemeinschaft
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/10171108/10121629.pdf?arnumber=10121629
Reference37 articles.
1. Long-Term Bowel Sound Monitoring and Segmentation by Wearable Devices and Convolutional Neural Networks
2. Deep 3D Body Landmarks Estimation for Smart Garments Design
3. Automatic Bowel Motility Evaluation Technique for Noncontact Sound Recordings
4. Adaptive Activity Spotting Based on Event Rates
5. Development of a bowel sound detector adapted to demonstrate the effect of food intake
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3. The sound of surgery-development of an acoustic trocar system enabling laparoscopic sound analysis;International Journal of Computer Assisted Radiology and Surgery;2024-06-03
4. Multi-scale Bowel Sound Event Spotting in Highly Imbalanced Wearable Monitoring Data: Algorithm Development and Validation (Preprint);2023-07-25
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