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.

Browse

Settings

Author: search.filters.author.Spasenović, MarkoHas files: No

Search Results

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Prediction of Oxygen Saturation from Graphene Respiratory Signals with PPG Trained DNN
    (SCITEPRESS - Science and Technology Publications, 2024)
    ;
    Vićentić, Teodora
    ;
    Madevska Bogdanova, Ana
    ;
    Ilić, Stefan
    ;
    Tomić, Miona
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Prediction of Oxygen Saturation from Graphene Respiratory Signals with PPG Trained DNN
    (SCITEPRESS - Science and Technology Publications, 2024)
    ;
    Vićentić, Teodora
    ;
    Madevska Bogdanova, Ana
    ;
    Ilić, Stefan
    ;
    Tomić, Miona
    This paper explores the feasibility of using wearable laser-induced graphene (LIG) sensors to estimate oxygen saturation (SpO2) as an alternative to traditional photoplethysmography (PPG) oximeters, particularly in mass casualty triage scenarios. Positioned on the chest, the LIG sensor continuously monitors respiratory signals in real-time. The study leverages deep neural network (DNN) trained on PPG signals to process LIG respiratory signals, revealing promising results. Key performance metrics include a mean squared error (MSE) of 0.152, a mean absolute error (MAE) of 1.13, a root mean square error (RMSE) of 1.23, and an R2 score of 0.68. This innovative approach, combining PPG and respiratory signals from graphene, offers a potential solution for 2D sensors in emergency situations, enhancing the monitoring and management of various medical conditions. However, further investigation is required to establish the clinical applications and correlations between these signals. This study marks a significant step toward advancing wearable sensor technology for critical health- care scenarios.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Wearable Graphene Sensor for Pulse Measurement
    (Institute of Technical Sciences of SASA, 2021)
    Vićentić, Teodora
    ;
    Rašljić Rafajilović, Milena
    ;
    ;
    Madevska Bogdanova, Ana
    ;
    Pašti, Igor
    Graphene is a material that has been widely used in different types of sensors, due to its optimal electrical and mechanical properties. Recently discovered laser-induced graphene (LIG) has opened new perspectives for a versatile and durable physical sensing platform, capable of detecting various physical parameters. In this study, LIG was produced by CO2 laser irradiation of polyimide film. LIG-based sensor was used to measure human pulse. Fabricated LIG sensors were attached to a subject’s body. A temporal change in resistance was recorded for different sensor embodiments, including as-fabricated on polyimide tape and transferred into a PDMS matrix. The measured change in resistance is induced by bending of the sensor due to vein pulsing. The measured resistance time traces were analyzed with the Python HeartPy module to extract pulse information, demonstrating agreement with commercially available sensors.