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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Author: search.filters.author.Albuquerque, CarlosHas files: Yes

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    Sensor-based systems for the measurement of Functional Reach Test results: a systematic review
    (PeerJ, 2024)
    Francisco, Luís
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    Duarte, João
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    Godinho, António Nunes
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    Albuquerque, Carlos
    The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person's balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based systems to objectively and accurately measure FRT results. This systematic review was performed in various scientific databases or publishers, including PubMed Central, IEEE Explore, Elsevier, Springer, the Multidisciplinary Digital Publishing Institute (MDPI), and the Association for Computing Machinery (ACM), and considered studies published between January 2017 and October 2022, related to methods for the automation of the measurement of the Functional Reach Test variables and results with sensors. Camera-based devices and motion-based sensors are used for Functional Reach Tests, with statistical models extracting meaningful information. Sensor-based systems offer several advantages over traditional manual measurement techniques, as they can provide objective and precise measurements of the reach distance, quantify postural sway, and capture additional parameters related to the movement.
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    Can sensors be used to measure the Arm Curl Test results? a systematic review
    (Springer Science and Business Media LLC, 2024-01-31)
    Matos, Tomás
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    Vornicoglo, Daniel
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    Coelho, Paulo Jorge
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    Albuquerque, Carlos
    <jats:title>Abstract</jats:title><jats:p>There is growing interest in the automated measurement of physical fitness tests, such as the Arm Curl Test, to enable more objective and accurate assessments. This review aimed to systematically analyze the types of sensors and technological methods used for automated Arm Curl Test measurement and their benefits for different populations. The search consisted of the search related to the possibilities to measure the Arm Curl Test results with sensors in scientific databases, including PubMed Central, IEEE Explore, Elsevier, Springer, MDPI, ACM, and PMC, published from January 2010 to October 2022. The analysis included 30 studies from 15 nations with diverse populations analyzed. According to data extraction, the most prevalent sensors were chronometers, accelerometers, stadiometers, and dynamometers. In the investigations, statistical analysis predominated. The study shows how automated sensor technologies can objectively measure the Arm Curl Test. The detected sensors combined with statistical analysis techniques can enhance assessments. Applications for the Arm Curl Test may be improved even more with more research on cutting-edge sensors and algorithms. This evaluation offers insightful information about utilizing sensor-based automation to enhance Arm Curl Testing.</jats:p>
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    Ten meter walk test with mobile devices: A dataset with accelerometer, magnetometer, and gyroscope
    (Elsevier BV, 2024-02)
    Gabriel, Cristiana Lopes
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    Pires, Ivan Miguel
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    Gonçalves, Norberto Jorge
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    Coelho, Paulo Jorge
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    Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection
    (MDPI, 2022-08-26)
    Neves, Paulo Alexandre
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    Simões, João
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    Costa, Ricardo
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    Pimenta, Luís
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    Gonçalves, Norberto Jorge
    Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer’s disease, or other conditions may not take food or medicine regularly. Therefore, the ability to monitor could be beneficial for them and for the doctors that can analyze the patterns of eating habits and their correlation with overall health. Many sensors help accurately detect food intake episodes, including electrogastrography, cameras, microphones, and inertial sensors. Accurate detection may provide better control to enable healthy nutrition habits. This paper presents a systematic review of the use of technology for food intake detection, focusing on the different sensors and methodologies used. The search was performed with a Natural Language Processing (NLP) framework that helps screen irrelevant studies while following the PRISMA methodology. It automatically searched and filtered the research studies in different databases, including PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Then, the manual analysis selected 30 papers based on the results of the framework for further analysis, which support the interest in using sensors for food intake detection and nutrition assessment. The mainly used sensors are cameras, inertial, and acoustic sensors that handle the recognition of food intake episodes with artificial intelligence techniques. This research identifies the most used sensors and data processing methodologies to detect food intake.
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    A Brief Review on Gender Identification with Electrocardiography Data
    (MDPI, 2022-08-16)
    Bastos, Eduarda Sofia
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    Duarte, Rui Pedro
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    Marinho, Francisco Alexandre
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    Rudenko, Roman
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    Vitaliyivna Denysyuk, Hanna
    Cardiac diseases have increased over the years; thus, it is essential to predict their possible signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs. Sensors available in commonly used devices may strive for the proper and early identification of various cardiac diseases. The primary purpose of this review is to analyze studies related to gender discretization based on data from different sensors including electrocardiography and echocardiography. The analyzed studies were published between 2010 and 2022 in various scientific databases, including PubMed Central, Springer, ACM, IEEE Xplore, MDPI, and Elsevier, based on the analysis of different cardiovascular diseases. It was possible to verify that most of the analyzed studies measured similar parameters as traditional methods including the QRS complex and other waves that characterize the various individuals.
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    Can the Eight Hop Test Be Measured with Sensors? A Systematic Review
    (MDPI, 2022-05-08)
    Pimenta, Luís
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    Garcia, Nuno M
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    Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyzed in detail. Our analysis found that the Eight Hop Test measurements can be performed with motion, force, and imaging sensors.
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    Development Technologies for the Monitoring of Six-Minute Walk Test: A Systematic Review
    (MDPI, 2022-01-12)
    Pires, Ivan Miguel
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    Vitaliyivna Denysyuk, Hanna
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    Villasana, María Vanessa
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    Sá, Juliana
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    Marques, Diogo Luís
    In the pandemic time, the monitoring of the progression of some diseases is affected and rehabilitation is more complicated. Remote monitoring may help solve this problem using mobile devices that embed low-cost sensors, which can help measure different physical parameters. Many tests can be applied remotely, one of which is the six-minute walk test (6MWT). The 6MWT is a sub-maximal exercise test that assesses aerobic capacity and endurance, allowing early detection of emerging medical conditions with changes. This paper presents a systematic review of the use of sensors to measure the different physical parameters during the performance of 6MWT, focusing on various diseases, sensors, and implemented methodologies. It was performed with the PRISMA methodology, where the search was conducted in different databases, including IEEE Xplore, ACM Digital Library, ScienceDirect, and PubMed Central. After filtering the papers related to 6MWT and sensors, we selected 31 papers that were analyzed in more detail. Our analysis discovered that the measurements of 6MWT are primarily performed with inertial and magnetic sensors. Likewise, most research studies related to this test focus on multiple sclerosis and pulmonary diseases.