Real Time Patient Monitoring System Using BLYNK

Ranjana, S.; Hegde, Ramakrishna; Divya, C.

doi:10.1109/discover52564.2021.9663681

Cited by 5 publications

(1 citation statement)

References 7 publications

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“…Hence, it can be said that the use of the internet has now become a basic need in everyday life, therefore, in research on designing IoTbased vital sign parameter monitoring tools must be used by the elderly, where the monitoring tool is very efficient both in terms of time and cost operational. Telehealthcare uses the Blynk application as a tool to monitor vital health sign parameters that can be seen visually on smartphones [21], [22].…”

Section: Resultsmentioning

confidence: 99%

Low-cost Physiological Parameter Development using Internet of Things Based for Monitoring Health Elderly

Utomo

Triwiyanto

Luthfiyah

et al. 2022

Open Access Maced J Med Sci

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BACKGROUND: In today’s digital era, the development of technology and information is so fast not only in the world of medicine and medical equipment but also in the model of health services so that many e-services are found, such as Alodokter and Halodoc. As well Internet of Things (IoT)-based technology IoT makes the method that can be used for remote services easy to reach and low cost, this is very significant in helping home care services in the elderly. AIM: The goal of this research is to develop the design of telehealthcare based on IoT, especially the vital signs of monitoring for the early detection of diseases in the elderly through health-care services. METHODS: This type of research is experimental with the design of equipment design using IoT based with parameters of a biomedical temperature sensor, heart rate, and SpO2 sensor for monitoring health elderly integrated into smartphone applications through programming Arduino ESP 32 microcontroller as a transmitter. RESULTS: The results of this study consist of two stages, including first determining the accuracy value of biomedical sensor data results by measuring the error factor, namely, for beats per minute sensor, data have a deviation error of 1.6 and SpO2 deviation error of 0.25 and temperature deviation error of 0.16 with a confidence level of 0.05% and second comparing parameter values to standard values using t-test tests with p > 0.05 results means that there is no significant difference between parameter values and standard values. CONCLUSION: The results of this study can be concluded that the physiological parameters, such as spo2, bpm and body temperature can be used for health monitoring in the elderly, and it is hoped that the results of this research design can be used for early detection of the elderly for routine health checks using a smartphone application.

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Section: Resultsmentioning

confidence: 99%