The Emerging Wireless Body Area Network on Android Smartphones: A Review

Puspitaningayu, Pradini; Widodo, Arif; Yundra, Eppy

doi:10.1088/1757-899x/288/1/012116

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…In [ 38 ], Puspitaningayu et al gathered and processed the data from an embedded system using Bluetooth low energy links and a cable connection. Wagner et al [ 39 ] and Nandkishor et al [ 40 ] proposed similar systems for Android operating system-based hosts with some variations.…”

Section: Significance Of Iomt Sensor Data and Their Transmission And ...mentioning

confidence: 99%

An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models

Mishra,

Liberman,

Brahamanpally

2024

Sensors

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The sensors used in the Internet of Medical Things (IoMT) network run on batteries and need to be replaced, replenished or should use energy harvesting for continuous power needs. Additionally, there are mechanisms for better utilization of battery power for network longevity. IoMT networks pose a unique challenge with respect to sensor power replenishment as the sensors could be embedded inside the subject. A possible solution could be to reduce the amount of sensor data transmission and recreate the signal at the receiving end. This article builds upon previous physiological monitoring studies by applying new decision tree-based regression models to calculate the accuracy of reproducing data from two sets of physiological signals transmitted over cellular networks. These regression analyses are then executed over three different iteration varieties to assess the effect that the number of decision trees has on the efficiency of the regression model in question. The results indicate much lower errors as compared to other approaches indicating significant saving on the battery power and improvement in network longevity.

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Section: Significance Of Iomt Sensor Data and Their Transmission And ...mentioning

confidence: 99%

An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models

Mishra,

Liberman,

Brahamanpally

2024

Sensors

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“…To monitor vital signs in the body, WBAN is structured in an architecture consisting of nodes, microcontroller chips, wireless communication modules, and data communication devices connected to certain networks. Figure 1 below is an illustration of the WBAN architecture [15].…”

Section: Wireless Body Area Network (Wban)mentioning

confidence: 99%

Analysis of Android-based Body Health Monitoring System Results using Fuzzy Mamdani Method

Handayani¹,

Taqwa²,

Hadi³

et al. 2022

Atlantis Highlights in Engineering

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In a health monitoring system, an Android-based Health Detector (AHD) application uses fuzzy Mamdani to detect health concerns. The data given can be used as an input for multi-sensor readings produced from physiological health detection. The body's total health is determined when the detected health is merged with the fuzzy Mamdani algorithm. Anger, apathy, and apathy were calculated as variables. The fuzzy Mamdani method to body health problems involves creating fuzzy sets, applying implications functions, and synthesizing rules. This study found that aging affects both men's and women's health. Persons over 65 are more likely than younger people to suffer health issues, even if only a minority of them have been diagnosed. The fuzzy Mamdani technique had a high accuracy rate of 93.33 percent in this study.

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“…Sensor ini dapat mengirimkan data secara nirkabel yang bertujuan untuk meningkatkan berbagai pelayanan kesehatan dan kualitas hidup. Arsitektur WBAN terdiri dari berbagai sensor yang disebut dengan nodes [17], chip mikrokontroller, modul komunikasi nirkabel, dan berbagai perangkat komunikasi data yang terkoneksi pada jaringan tertentu [18].…”

Section: Tinjauan Pustaka a Wban Sebagai Monitoring Kesehatanunclassified

Perancangan Alat Kesehatan Wireless Body Area Network Multisensor Berbasis Aplikasi Android

Mustaqiim,

Taqwa,

Handayani

et al. 2021

quateknika

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In this study, we designed a multisensory medical device to carry out a process of monitoring body health that was integrated into the system so that the patient's health could be detected. This tool uses Wireless Body Area Network technology that can work with Android-based platforms in real time. In designing this tool, it is designed to detect body health automatically by displaying information about body temperature, blood pressure, heart rate and oxygen levels in the blood, then sending notifications to the server without wasting time, and recording physical health information data automatically. Real-time display on the smartphone, owned by the user and provides a readable body health status that is healthy, an indication or needs action.

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The Emerging Wireless Body Area Network on Android Smartphones: A Review

Cited by 7 publications

References 4 publications

An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models

An Optimal, Power Efficient, Internet of Medical Things Framework for Monitoring of Physiological Data Using Regression Models

Analysis of Android-based Body Health Monitoring System Results using Fuzzy Mamdani Method

Perancangan Alat Kesehatan Wireless Body Area Network Multisensor Berbasis Aplikasi Android

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