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Volume 25
Issue 5
10.3390/s25051552
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors

by
Atcharawan Rattanasak
1,
Talit Jumphoo
2,
Wongsathon Pathonsuwan
2,
Kasidit Kokkhunthod
2,
Khwanjit Orkweha
3,
Khomdet Phapatanaburi
4,*,
Pattama Tongdee
5,
Porntip Nimkuntod
6,
Monthippa Uthansakul
1 and
Peerapong Uthansakul
1,*
1
School of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
2
Institute of Research and Development, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
3
Department of Integrated Engineering, Rajamangala University of Technology Tawan-Ok, Chanthaburi 22210, Thailand
4
Department of Telecommunication Engineering, Faculty of Engineering and Technology, Rajamangala University of Technology Isan (RMUTI), Nakhon Ratchasima 30000, Thailand
5
School of Obstetrics and Gynecology, Institute of Medicine, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
6
School of Medicine, Institute of Medicine, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
*
Authors to whom correspondence should be addressed.
Sensors 2025, 25(5), 1552; https://doi.org/10.3390/s25051552
Submission received: 26 January 2025 / Revised: 22 February 2025 / Accepted: 28 February 2025 / Published: 2 March 2025
(This article belongs to the Section Internet of Things)
Versions Notes

Abstract

Counting fetal movements is essential for assessing fetal health, but manually recording these movements can be challenging and inconvenient for pregnant women. This study presents a wearable device designed to detect fetal movements across various settings, both within and outside medical facilities. The device integrates accelerometer and gyroscope sensors with Internet of Things (IoT) technology to accurately differentiate between fetal and non-fetal movements. Data were collected from 35 pregnant women at Suranaree University of Technology (SUT) Hospital. This study evaluated ten signal extraction methods, six machine learning algorithms, and four feature selection techniques to enhance classification performance. The device utilized Particle Swarm Optimization (PSO) for feature selection and Extreme Gradient Boosting (XGB) with PSO hyper-tuning. It achieved a sensitivity of 90.00%, precision of 87.46%, and an F1-score of 88.56%, reflecting commendable results. The IoT-enabled technology facilitated continuous monitoring with an average latency of 423.6 ms. It ensured complete data integrity and successful transmission, with the capability to operate continuously for up to 48 h on a single charge. The findings substantiate the efficacy of the proposed approach in detecting fetal movements, thereby demonstrating a practical and valuable technology for fetal movement detection applications.
Keywords: fetal movement detection; internet of things; wearable device; machine learning fetal movement detection; internet of things; wearable device; machine learning

Share and Cite

MDPI and ACS Style

Rattanasak, A.; Jumphoo, T.; Pathonsuwan, W.; Kokkhunthod, K.; Orkweha, K.; Phapatanaburi, K.; Tongdee, P.; Nimkuntod, P.; Uthansakul, M.; Uthansakul, P. An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors. Sensors 2025, 25, 1552. https://doi.org/10.3390/s25051552

AMA Style

Rattanasak A, Jumphoo T, Pathonsuwan W, Kokkhunthod K, Orkweha K, Phapatanaburi K, Tongdee P, Nimkuntod P, Uthansakul M, Uthansakul P. An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors. Sensors. 2025; 25(5):1552. https://doi.org/10.3390/s25051552

Chicago/Turabian Style

Rattanasak, Atcharawan, Talit Jumphoo, Wongsathon Pathonsuwan, Kasidit Kokkhunthod, Khwanjit Orkweha, Khomdet Phapatanaburi, Pattama Tongdee, Porntip Nimkuntod, Monthippa Uthansakul, and Peerapong Uthansakul. 2025. "An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors" Sensors 25, no. 5: 1552. https://doi.org/10.3390/s25051552

APA Style

Rattanasak, A., Jumphoo, T., Pathonsuwan, W., Kokkhunthod, K., Orkweha, K., Phapatanaburi, K., Tongdee, P., Nimkuntod, P., Uthansakul, M., & Uthansakul, P. (2025). An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors. Sensors, 25(5), 1552. https://doi.org/10.3390/s25051552

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