Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms
This study presents a long-term vital signs sensing gown consisting of two components: a miniaturized monitoring device and an intelligent computation platform. Vital signs are signs that indicate the functional state of the human body. The general physical health of a person can be assessed by moni...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Biosensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-6374/12/11/964 |
| _version_ | 1797468963283664896 |
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| author | Li-Wei Ko Yang Chang Bo-Kai Lin Dar-Shong Lin |
| author_facet | Li-Wei Ko Yang Chang Bo-Kai Lin Dar-Shong Lin |
| author_sort | Li-Wei Ko |
| collection | DOAJ |
| description | This study presents a long-term vital signs sensing gown consisting of two components: a miniaturized monitoring device and an intelligent computation platform. Vital signs are signs that indicate the functional state of the human body. The general physical health of a person can be assessed by monitoring vital signs, which typically include blood pressure, body temperature, heart rate, and respiration rate. The miniaturized monitoring device is composed of a compact circuit which can acquire two kinds of physiological signals including bioelectrical potentials and skin surface temperature. These two signals were pre-processed in the circuit and transmitted to the intelligent computation platform for further analysis using three algorithms, which incorporate R-wave detection, ECG-derived respiration, and core body temperature estimation. After the processing, the derived vital signs would be displayed on a portable device screen, including ECG signals, heart rate (<i>HR</i>), respiration rate (<i>RR</i>), and core body temperature. An experiment for validating the performance of the intelligent computation platform was conducted in clinical practices. Thirty-one participants were recruited in the study (ten healthy participants and twenty-one clinical patients). The results showed that the relative error of <i>HR</i> is lower than 1.41%, <i>RR</i> is lower than 5.52%, and the bias of core body temperature is lower than 0.04 °C in both healthy participant and clinical patient trials. In this study, a miniaturized monitoring device and three algorithms which derive vital signs including <i>HR</i>, <i>RR</i>, and core body temperature were integrated for developing the vital signs sensing gown. The proposed sensing gown outperformed the commonly used equipment in terms of usability and price in clinical practices. Employing algorithms for estimating vital signs is a continuous and non-invasive approach, and it could be a novel and potential device for home-caring and clinical monitoring, especially during the pandemic. |
| first_indexed | 2024-03-09T19:14:46Z |
| format | Article |
| id | doaj.art-f7f7cc5bb6be4437bc16fdaad8b97497 |
| institution | Directory Open Access Journal |
| issn | 2079-6374 |
| language | English |
| last_indexed | 2024-03-09T19:14:46Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj.art-f7f7cc5bb6be4437bc16fdaad8b974972023-11-24T03:55:06ZengMDPI AGBiosensors2079-63742022-11-01121196410.3390/bios12110964Vital Signs Sensing Gown Employing ECG-Based Intelligent AlgorithmsLi-Wei Ko0Yang Chang1Bo-Kai Lin2Dar-Shong Lin3Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), Institute of Bioinformatics and Systems Biology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300, TaiwanCenter for Intelligent Drug Systems and Smart Bio-Devices (IDS2B), Institute of Bioinformatics and Systems Biology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300, TaiwanDepartment of Biological Science & Technology, National Yang Ming Chiao Tung University, Hsinchu 300, TaiwanDepartment of Pediatrics, Mackay Memorial Hospital, Taipei 104, TaiwanThis study presents a long-term vital signs sensing gown consisting of two components: a miniaturized monitoring device and an intelligent computation platform. Vital signs are signs that indicate the functional state of the human body. The general physical health of a person can be assessed by monitoring vital signs, which typically include blood pressure, body temperature, heart rate, and respiration rate. The miniaturized monitoring device is composed of a compact circuit which can acquire two kinds of physiological signals including bioelectrical potentials and skin surface temperature. These two signals were pre-processed in the circuit and transmitted to the intelligent computation platform for further analysis using three algorithms, which incorporate R-wave detection, ECG-derived respiration, and core body temperature estimation. After the processing, the derived vital signs would be displayed on a portable device screen, including ECG signals, heart rate (<i>HR</i>), respiration rate (<i>RR</i>), and core body temperature. An experiment for validating the performance of the intelligent computation platform was conducted in clinical practices. Thirty-one participants were recruited in the study (ten healthy participants and twenty-one clinical patients). The results showed that the relative error of <i>HR</i> is lower than 1.41%, <i>RR</i> is lower than 5.52%, and the bias of core body temperature is lower than 0.04 °C in both healthy participant and clinical patient trials. In this study, a miniaturized monitoring device and three algorithms which derive vital signs including <i>HR</i>, <i>RR</i>, and core body temperature were integrated for developing the vital signs sensing gown. The proposed sensing gown outperformed the commonly used equipment in terms of usability and price in clinical practices. Employing algorithms for estimating vital signs is a continuous and non-invasive approach, and it could be a novel and potential device for home-caring and clinical monitoring, especially during the pandemic.https://www.mdpi.com/2079-6374/12/11/964miniaturized circuitECGvital signheart raterespirationcore body temperature |
| spellingShingle | Li-Wei Ko Yang Chang Bo-Kai Lin Dar-Shong Lin Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms Biosensors miniaturized circuit ECG vital sign heart rate respiration core body temperature |
| title | Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms |
| title_full | Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms |
| title_fullStr | Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms |
| title_full_unstemmed | Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms |
| title_short | Vital Signs Sensing Gown Employing ECG-Based Intelligent Algorithms |
| title_sort | vital signs sensing gown employing ecg based intelligent algorithms |
| topic | miniaturized circuit ECG vital sign heart rate respiration core body temperature |
| url | https://www.mdpi.com/2079-6374/12/11/964 |
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