Abstract:
This paper reports an ultra-low power real time bowel sound detector with integrated feature extractor for physiologic measure of meal instances in artificial pancreas devices. The system can aid in improving long term diabetic patient care and consists of a front end detector and signal processing unit. The front end detector transduces the initial bowel sound recorded from a piezoelectric sensor into a voltage signal. The signal processor uses a feature extractor to determine whether a bowel sound is detected. The feature extractor consists of a low noise, low power signal front-end, peak and trough locator, signal slope and width detector, digitizer, and bowel pulse locator. The system was fabricated in a standard 0.18 μm CMOS process, and the bowel sound detection system was characterized and verified with experimentally recorded bowel sounds. The integrated instrument consumes 53 μW of power from a 1 V supply in a 0.96 mm2 area, and is suitable for integration with portable devices.
Keywords
Bowel sound; Artificial pancreas; Glucose monitoring; Feature extractor; Charge amplifier; Piezoelectric sensor
Citation: Khandaker A. Al Mamun, Nicole McFarlane Integrated Real Time Bowel Sound Detector For Artificial Pancreas Systems doi:10.1016/j.sbsr.2016.01.004.
Received: 14 August 2015, Accepted: 8 January 2016, Available online: 11 January 2016
Copyright: © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Conclusion
Online bowel sound monitoring in an artificial pancreas can enable real time physiological monitoring of meal instance, gastrointestinal motility and monitoring of patient information and compliance. Implementation of such a bowel sound monitoring system in a portable insulin pump will require system integration in a limited chip space and demands low power operation. We have demonstrated an integrated ultra-low power bowel monitoring system which consumes 53 μW of power and can be implemented in a 0.96 mm2 chip space which is a compact implemented system compared to current state of the art bowel monitoring systems. The monitoring system extracts bowel features in real time and can be seamlessly integrated in a portable system. The system provides a non-invasive way to detect and correlate physiological measures in real time with motility or meal instances. The prototype instrument shows 85% accuracy with low false positives, which is sufficient for determining whether a patient has eaten when monitored continuously. The instrument can be used to analyze bowel patterns and is suitable as a low power front end solution of a complex bowel signal processing system.
Acknowledgments
The authors would like to thank Dr. Nathanael Paul for his valuable input, Mr. Nate Henry for help with data collection, Mr. Chirag K. Tailor for help in writing the LabVIEW data acquisition program, and Mr. Md. Habib Ullah Habib for help in figure graphics. The authors also thank MOSIS for chip fabrication. This chip was used to teach a course in mixed signal VLSI design.
