Refined acoustic sensor for fetal heartbeat rate monitoring

This dissertation presents an innovative acoustic detection scheme for a fetal heartbeat, the “Refined Acoustic Sensor for Fetal Heartbeat Rate Monitoring.” The system uses acoustic sensors with acoustic impedance matching diaphragms, processed by signal acquisition circuits. It calculates the heart...

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Bibliographic Details
Main Author: Liu, Wenpeng
Other Authors: Poenar Daniel Puiu
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/181456
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Institution: Nanyang Technological University
Language: English
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Summary:This dissertation presents an innovative acoustic detection scheme for a fetal heartbeat, the “Refined Acoustic Sensor for Fetal Heartbeat Rate Monitoring.” The system uses acoustic sensors with acoustic impedance matching diaphragms, processed by signal acquisition circuits. It calculates the heartbeat through an innovative calculation algorithm, which enables the acquisition and processing of tiny signals to achieve monitoring of fetal health parameters. This research has been validated in multiple stages, from theoretical modeling to lab-stage experiments, sparing no effort to improve the accuracy, reliability, and user-friendliness of fetal heartbeat monitoring. The project is solving three major difficulties: acquisition of weak signals, amplification of weak signals, and processing of acoustic signals. For weak signals, a composite diaphragm structure with a softer "propagation layer" is used to match acoustic impedance with the skin, reducing reflection and improving comfort while minimizing airborne noise. A special acoustic amplifier chip and filter circuit amplifies weak signals while reducing noise. Innovative algorithms process acoustic signals by utilizing both upper/lower half-waves and S1S2 phases to increase accuracy, with adaptive distances and windows enhancing computational efficiency. In addition, considering privacy and info-security issues, certain data are obtained through simulation methods, and future collaboration with medical institutions is planned to ensure the data's authenticity and the system's clinical applicability.