Multifunctional communication gateway for implementation in telemedicine systems

Kozarik, Jozef; Zavodnik, T.; Cernaj, L.; Debnar, T.; Micjan, Michal; Donoval, Martin; Gasparek, K.; Vavrinský, Erik; Kosnáčová, Helena

doi:10.1109/asdam55965.2022.9966748

Cited by 1 publication

(2 citation statements)

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“…These measurements include PPG and ECG recording. Physiological measurements were performed with our existing standalone device, which shares common hardware and backend solutions with the planned smart headband prototype [79]- [81]. The PPG signals were obtained specifically from the MAXM86146 Optical Biosensing Module (Analog Devices, Wilmington, MA, USA) using 3 different wavelengths of SFH 7016 LEDs (OSRAM GmbH, Munich, Germany) and the ECG from TI ADS1299 circuit (Texas Instruments, Dallas, TX, USA).…”

Section: Physiological Measurementsmentioning

confidence: 99%

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Pilot Experiments and Hardware Design of Smart Electrooculographic Headband for People With Muscular Paralysis

Kosnacova,

Horvath,

Stremy

et al. 2024

IEEE Access

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Millions of individuals worldwide suffer from a motor disability, impeding their ability to perform daily tasks independently. Modern technologies, such as electrooculography (EOG), offer tools to enhance their quality of life. EOG, an electrophysiological method, detects DC potentials influenced by eye movements, making it particularly advantageous for individuals with motor impairments who retain ocular mobility. This article describes pilot experiments that includes the basic design of an electrodes configuration for peripheral solutions, their optimization, and the addition of sensors to measure other vital physiological parameters such as photoplethysmography (PPG) and electrocardiography (ECG) on demand. We tested all the EOG methodologies and connections that our device should contain, using the Mindmedia Nexus-10 MKII for EOG, the Analog Devices MAXM86146 optical biosensor module for PPG signals, the Texas Instruments ADS1299 biopotential circuit for ECG. The evaluation and filtering of the collected data were carried out in the MATLAB environment. Finally, we present a hardware concept based on a new approach that, unlike standard EOG, incorporates three large-area conductive fabric electrodes in a headband for practical and comfortable long-term non-manual human-machine interface (HMI). Our measurements are crucial for monitoring the patients' health status, mood variations, and can help prevent complications or speed up treatment. The primary goal of this research was to present our innovative concept and confirm its feasibility, bringing us closer to the realization of a fully developed and functional device.

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Section: Physiological Measurementsmentioning

confidence: 99%

“…All the data transferred through 2.4 GHz network goes to the server through our dedicated base station which is connected directly to server with private APN tunnel. Therefore, our device can be easily incorporated into our existing telemedicine system [79].…”

Section: Cpu Digital Blockmentioning

confidence: 99%