A Wearable Sensor for Respiratory Volume Estimation With Self-Organizing Wireless Transmission Method

In recent years, wearable devices for respiratory 2 volume measurement have demonstrated a trend towards 3 increased intelligence and miniaturization; they often need to 4 balance accuracy, comfort, and robustness to meet the needs of 5 long-term data collection. With the increasing application of 6 Internet of Things (IoT) devices in life, wearable devices also have 7 strong IoT attributes, they need to focus on interactivity with 8 external devices. Therefore, this paper proposes a noninvasive 9 flexible wearable device with respiratory detection, which is fixed 10 to the chest and abdomen during operation and can monitor tidal 11 volume (TV) and respiratory rate (RR) in near real-time, a design 12 that strikes a good balance. In the test, most users have less than 13 5% error in the measurement of RR and less than 15% error in 14 the measurement of TV in a stationary state. There will be a partial 15 decrease in accuracy in the exercise state, but it still has a reference 16 significance, which is suitable for providing data for long-term 17 monitoring. In addition, this paper proposes a lightweight 18 networking scheme, which helps the data interaction and 19 management of wearable devices or with other devices. The 20 content discussed in this paper is highly scalable and suitable for 21 different application scenarios of respiratory monitoring. This 22 kind of versatile and flexible solution is also a future trend. 23 24

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-27
DOI
https://doi.org/10.1109/jiot.2025.3572531
Primary Topic
Bluetooth and Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

A Wearable Sensor for Respiratory Volume Estimation With Self-Organizing Wireless Transmission Method

Guochun Wan, Lan Chen, Liyu Xie, Jiahui Wang
IEEE Internet of Things Journal
Bluetooth and Wireless Communication Technologies
article

A Wearable Sensor for Respiratory Volume Estimation With Self-Organizing Wireless Transmission Method

Guochun Wan, Lan Chen, Liyu Xie, Jiahui Wang
article en

Abstract

In recent years, wearable devices for respiratory 2 volume measurement have demonstrated a trend towards 3 increased intelligence and miniaturization; they often need to 4 balance accuracy, comfort, and robustness to meet the needs of 5 long-term data collection. With the increasing application of 6 Internet of Things (IoT) devices in life, wearable devices also have 7 strong IoT attributes, they need to focus on interactivity with 8 external devices. Therefore, this paper proposes a noninvasive 9 flexible wearable device with respiratory detection, which is fixed 10 to the chest and abdomen during operation and can monitor tidal 11 volume (TV) and respiratory rate (RR) in near real-time, a design 12 that strikes a good balance. In the test, most users have less than 13 5% error in the measurement of RR and less than 15% error in 14 the measurement of TV in a stationary state. There will be a partial 15 decrease in accuracy in the exercise state, but it still has a reference 16 significance, which is suitable for providing data for long-term 17 monitoring. In addition, this paper proposes a lightweight 18 networking scheme, which helps the data interaction and 19 management of wearable devices or with other devices. The 20 content discussed in this paper is highly scalable and suitable for 21 different application scenarios of respiratory monitoring. This 22 kind of versatile and flexible solution is also a future trend. 23 24

IEEE Internet of Things JournalVol. 12(15)
Tongji University (CN), Shanghai Institute of Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 88%
Bluetooth and Wireless Communication Technologies
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A Wearable Sensor for Respiratory Volume Estimation With Self-Organizing Wireless Transmission Method — Guochun Wan, Lan Chen, et al. · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS