Faculty of Computer Science and Engineering
Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5
The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest
faculties in that field in the region.
The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.
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Item type:Publication, Prediction of Oxygen Saturation from Graphene Respiratory Signals with PPG Trained DNN(SCITEPRESS - Science and Technology Publications, 2024); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Prediction of Oxygen Saturation from Graphene Respiratory Signals with PPG Trained DNN(SCITEPRESS - Science and Technology Publications, 2024); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis(MDPI, 2022-08-23); Madevska Bogdanova, AnaThe HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Wearable Patch for Mass Casualty Screening with Graphene Sensors(2022); Madevska Bogdanova, AnaWearable sensors are reaching maturity, at the same time as technologies for communicating physiological data and those for analyzing massive amounts of data. The combination of the three technologies invites for applications in mass screening of personal health through smart algorithm deployment on data from wearable patches. We propose and present an architecture for a wearable patch to be used in mass casualty emergency situations, or for hospital bedside monitoring. The proposed patch will contain multiple sensors of physiological parameters. We propose to create respiration and heartbeat sensors made of laser induced graphene. We show that graphene on flexible substrates can be utilized in conjunction with the Python heart rate analysis toolkit - HeartPy to reliably acquire physiological data from human subjects. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Wearable Patch for Mass Casualty Screening with Graphene Sensors(2022); Madevska Bogdanova, AnaWearable sensors are reaching maturity, at the same time as technologies for communicating physiological data and those for analyzing massive amounts of data. The combination of the three technologies invites for applications in mass screening of personal health through smart algorithm deployment on data from wearable patches. We propose and present an architecture for a wearable patch to be used in mass casualty emergency situations, or for hospital bedside monitoring. The proposed patch will contain multiple sensors of physiological parameters. We propose to create respiration and heartbeat sensors made of laser induced graphene. We show that graphene on flexible substrates can be utilized in conjunction with the Python heart rate analysis toolkit - HeartPy to reliably acquire physiological data from human subjects. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis(Sensors, 2022-08-23); Madevska Bogdanova, AnaThe HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development.