A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications
The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/1/104 |
| _version_ | 1797497613339066368 |
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| author | Jin-Woo Jeong Woochan Lee Young-Joon Kim |
| author_facet | Jin-Woo Jeong Woochan Lee Young-Joon Kim |
| author_sort | Jin-Woo Jeong |
| collection | DOAJ |
| description | The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring. The device is implemented in a compact size (diameter: 30 mm, thickness: 4.5 mm) where the biopotential is measured and wirelessly transmitted to a smartphone or a laptop for real-time monitoring, data recording and analysis. Adaptive digital filtering is applied to eliminate any interference noise that can occur during a regular at-home environment, while minimizing the data process time. The accuracy of ECG and EMG signal coverage is assessed using Bland–Altman analysis by comparing with a reference physiological signal acquisition instrument (RHS2116 Stim/Recording System, Intan). Signal coverage of R-R peak intervals showed almost identical outcome between this proposed work and the RHS2116, showing a mean difference in heart rate of 0.15 ± 4.65 bpm and a Wilcoxon’s <i>p</i> value of 0.133. A 24 h continuous recording session of ECG and EMG is conducted to demonstrate the robustness and stability of the device based on extended time wearability on a daily routine. |
| first_indexed | 2024-03-10T03:21:44Z |
| format | Article |
| id | doaj.art-0d81ee96c1284f3ba65286f879945386 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:21:44Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0d81ee96c1284f3ba65286f8799453862023-11-23T12:16:55ZengMDPI AGSensors1424-82202021-12-0122110410.3390/s22010104A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare ApplicationsJin-Woo Jeong0Woochan Lee1Young-Joon Kim2Department of Electronic Engineering, Gachon University, Seongnam 13120, KoreaDepartment of Electrical Engineering, Incheon National University, Incheon 22012, KoreaDepartment of Electronic Engineering, Gachon University, Seongnam 13120, KoreaThe acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring. The device is implemented in a compact size (diameter: 30 mm, thickness: 4.5 mm) where the biopotential is measured and wirelessly transmitted to a smartphone or a laptop for real-time monitoring, data recording and analysis. Adaptive digital filtering is applied to eliminate any interference noise that can occur during a regular at-home environment, while minimizing the data process time. The accuracy of ECG and EMG signal coverage is assessed using Bland–Altman analysis by comparing with a reference physiological signal acquisition instrument (RHS2116 Stim/Recording System, Intan). Signal coverage of R-R peak intervals showed almost identical outcome between this proposed work and the RHS2116, showing a mean difference in heart rate of 0.15 ± 4.65 bpm and a Wilcoxon’s <i>p</i> value of 0.133. A 24 h continuous recording session of ECG and EMG is conducted to demonstrate the robustness and stability of the device based on extended time wearability on a daily routine.https://www.mdpi.com/1424-8220/22/1/104ECG/EMG sensingphysiological monitorsmart wearable devicewireless communicationrehabilitation training |
| spellingShingle | Jin-Woo Jeong Woochan Lee Young-Joon Kim A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications Sensors ECG/EMG sensing physiological monitor smart wearable device wireless communication rehabilitation training |
| title | A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications |
| title_full | A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications |
| title_fullStr | A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications |
| title_full_unstemmed | A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications |
| title_short | A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications |
| title_sort | real time wearable physiological monitoring system for home based healthcare applications |
| topic | ECG/EMG sensing physiological monitor smart wearable device wireless communication rehabilitation training |
| url | https://www.mdpi.com/1424-8220/22/1/104 |
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