Sensors for wireless body area networks

Ruskova, Ivelina; Gieva, Elitsa

doi:10.1049/pbhe010e_ch8

Cited by 2 publications

(3 citation statements)

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“…Additional comparison parameters for different environments could be found in [106]. The sensor use in the AAL/ELE platform is shown also in [107] and the position in the use-case scenarios is demonstrated in [108].…”

Section: Activity Recognition For Sportsmentioning

confidence: 99%

Healthcare Sensing and Monitoring

Angelov

Nikolakov²,

Ruskova

et al. 2019

Lecture Notes in Computer Science

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This chapter presents an overview of many wearable devices of different types that have been proven in medical and home environments as being helpful in Quality of Life enhancement of elder adults. The recent advances in electronics and microelectronics allow the development of low-cost devices that are widely used by many people as monitoring tools for well-being or preventive purposes. Remote healthcare monitoring, which is based on noninvasive and wearable sensors, actuators and modern communication and information technologies offers efficient solutions that allows people to live in their comfortable home environment, being somehow protected. Furthermore, the expensive healthcare facilities are getting free to be used for intensive care patients as the preventive measures are getting at home. The remote systems can monitor very important physiological parameters of the patients in real time, observe health conditions, assessing them, and most important, provide feedback. Sensors are used in electronics medical and non-medical equipment and convert various forms of vital signs into electrical signals. Sensors can be used for life-supporting implants, preventive measures, long-term monitoring of disabled or ill patients. Healthcare organizations like insurance companies need real-time, reliable, and accurate diagnostic results provided by sensor systems that can be monitored remotely, whether the patient is in a hospital, clinic, or at home.

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Section: Activity Recognition For Sportsmentioning

confidence: 99%

Healthcare Sensing and Monitoring

Angelov

Nikolakov²,

Ruskova

et al. 2019

Lecture Notes in Computer Science

Self Cite

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“…The authors in [4] were testing the dates from the Bioharness in abnormal Heart Rate (HR) conditions which is a one of the expected scenarios in living environment. There are also several authors who are talking about the same topic but they are using some different sensors and methods, like in [5][6][7]. New generation smart watches have been used to measure the physiological parameters as HR, Galvanic Skin Resistance (GSR), temperature and EQ02 in a multi parameter body-worn system [7].…”

Section: Related Workmentioning

confidence: 99%

“…There are also several authors who are talking about the same topic but they are using some different sensors and methods, like in [5][6][7]. New generation smart watches have been used to measure the physiological parameters as HR, Galvanic Skin Resistance (GSR), temperature and EQ02 in a multi parameter body-worn system [7]. There are capable to log and transmit the physiological data describing a wearer's cardiorespiratory and thermal status.…”

Section: Related Workmentioning

confidence: 99%

System Development for Monitoring Physiological Parameters in Living Environment

Mladenovski¹,

Achkoski²,

Goleva

2019

Lecture Notes in Computer Science

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Nowadays, sensors, algorithms and software applications are embedded in people's everyday lives. To be more precise, living environment is significantly dependent on previously mentioned technology especially in the field of medicine.The ultimate goal of this research is to collect data from different medical sensors platform, which can be used in initial medical assessment and management in the living environment. Furthermore, collected data from sport's activity were analysed in order to measure the strength of linear association between variables.First, research on market available equipment is performed which is focused on medical sensors for assisted living in people's everyday environment. Second, research on hardware in terms of tablet, desktop machines, iPad etc. is conducted and scenarios of using the hardware are elaborated. Regarding the scenarios, the concept that demonstrates the advantages and disadvantages of the system for ambient assisted living is shown. The architecture of the system followed by sensors, computer networks, terminals is included and the technology for achieving the system's functionality is presented. Next, the Zephyr Bioharness 3 sensor for measuring physiological data is used for collecting data in the living environment. Finally, integration of the sensor with the most convenient terminal in the living environment is done and collected data are visualized via MATLAB. The parameters monitored are Heart Rate (HR), Respiratory Rate (RR), Peak Acceleration (PkAcc). The proof of the correlation between listed parameters describes the physiological status in the living environment.The ratio between HR and PkAcc is 0.91. It is a strong positive correlation. It means that changes in heart beats are linearly followed by the peak acceleration. Next, the ratio between HR and RR is 0.88. It is also a strong positive correlation. It means that changes in heart beats are linearly followed by the respiratory rate. The ratio between RR and PkAcc is 0.84. Again, it is a strong positive correlation. It means that changes in respiratory rate are linearly followed by the peak acceleration.

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Sensors for wireless body area networks

Cited by 2 publications

References 0 publications

Healthcare Sensing and Monitoring

Healthcare Sensing and Monitoring

System Development for Monitoring Physiological Parameters in Living Environment

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