Journal
IRBM
Volume 41, Issue 4, Pages 205-211Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.irbm.2019.11.003
Keywords
Fetal movements; Wearable system; Accelerometer; Machine learning
Categories
Funding
- French National Research Agency [ANR-14-CE24-0035-01]
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Objectives: This paper presents a novel wearable system for in-home and long-term fetal movement monitoring on a reliable and easily accessible basis. Material and methods: The system mainly consists of four accelerometers for fetal movement signal acquisition, a microcontroller for signal processing and an Android-based device interacting with the microcontroller via Bluetooth Low Energy (BLE), providing the mother with information related to the fetal movement in an intelligible way. Results: The proposed system can deliver reliable results with a specificity of 0.99 and a sensitivity of 0.77 for fetal movement time series signal classification. Conclusion: The proposed wearable system will provide a good alternative to optimize the use of medical professionals and hospital resources, and has potential applications in the field of e-Health home care. Besides, the fetal movement acceleration signals acquired with volunteers (pregnant women) help establish an initial database for future medical analysis of sensor-recorded fetal behaviors. (C) 2019 AGBM. Published by Elsevier Masson SAS. All rights reserved.
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