LI-Care: A LabVIEW and IoT Based eHealth Monitoring System

被引:3
作者
Swain, Kunjabihari [1 ]
Cherukuri, Murthy [1 ]
Mishra, Sunil Kumar [2 ]
Appasani, Bhargav [2 ]
Patnaik, Suprava [2 ]
Bizon, Nicu [3 ,4 ]
机构
[1] Natl Inst Sci & Technol, Dept Elect & Elect Engn, Berhampur 761008, India
[2] Kalinga Inst Ind Technol, Sch Elect Engn, Bhubaneswar 751024, India
[3] Univ Pitesti, Fac Elect Commun & Comp, Pitesti 110040, Romania
[4] Univ Politehn Bucuresti, Doctoral Sch, Bucharest 060042, Romania
关键词
eHealth care; LabVIEW; Internet of Things; patient monitoring; NI myRIO; physiological parameter monitoring; biomedical; HEALTH-CARE; COMPREHENSIVE SURVEY; BIG DATA; INTERNET; THINGS; METAMATERIAL; SENSOR;
D O I
10.3390/electronics10243137
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a Laboratory Virtual Instrument Engineering Workbench (LabVIEW) and Internet of Things (IoT)-based eHealth monitoring system called LI-Care to facilitate the diagnosis of the health condition cost-effectively. The system measures the heart rate, body temperature, blood pressure, oxygen level, and breathing rate, and provides an electrocardiogram (ECG). The required sensors are integrated on a web-based application that keeps track of the essential parameters and gives an alarm indication if one or more physiological parameters go beyond the safe level. It also employs a webcam to obtain the patient view at any time. LabVIEW enables the effortless interfacing of various biomedical sensors with the computer and provides high-speed data acquisition and interactive visualizations. It also provides a web publishing tool to access the interactive window remotely through a web browser. The web-based application is accessible to doctors who are experts in that particular field. They can obtain the real-time reading and directly perform a diagnosis. The parameters measured by the proposed system were validated using the traditional measurement systems, and the Root Mean Square (RMS) errors were obtained for the various parameters. The maximum RMS error as a percentage was 0.159%, which was found in the temperature measurement, and its power consumption is 1 Watt/h. The other RMS errors were 0.05% in measurement of systolic pressure, 0.029% in measurement of diastolic pressure, 0.059% in measurement of breathing rate, 0.002% in measurement of heart rate, 0.076% in measurement of oxygen level, and 0.015% in measurement of ECG. The low RMS errors and ease of deployment make it an attractive alternative for traditional monitoring systems. The proposed system has potential applications in hospitals, nursing homes, remote monitoring of the elderly, non-contact monitoring, etc.
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页数:15
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