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

Search Results

Now showing 1 - 10 of 27

Some of the metrics are blocked by your
consent settings
Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection
(MDPI, 2022-08-26)
Neves, Paulo Alexandre
;
Simões, João
;
Costa, Ricardo
;
Pimenta, Luís
;
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.
Some of the metrics are blocked by your
consent settings
CoviHealth: A pilot study with teenagers in schools of Centre of Portugal
(Springer, Cham, 2020-12-03)
Villasana, María Vanessa
;
Pires, Ivan Miguel
;
Sá, Juliana
;
Garcia, Nuno M
;
. Obesity is one of the most common problem that can be avoid with the correct education of the teenagers. There are different methods, but the use of the mobile devices to promote the creation of social challenges is important, because the teenagers act mainly in groups. The use of questionnaires, challenges and gamification purposes may promote the use of this type of mobile applications by teenagers. It is a special population that needs the adoption of different interactive technologies. The studies available are not validated by healthcare professionals. First of all, we started to analyze the related work of obesity problem, mobile applications, and different methodologies adopted with teenagers. By the end, seven students participated in the study with the performance of visualization of daily tips and curiosities, answering questionnaires, monitoring of physical activity and gamification. The teenagers were satisfied with the strategies adopted, but this study was affected by the pandemic situation around the world. In general, the participants were satisfied with the use of the mobile, and they would like to use it in the future for the improvement of their nutrition and physical activity habits.
Some of the metrics are blocked by your
consent settings
Control and Prevention of Personal Stress
(IEEE, 2020-12-10)
Marques, Hugo
;
Carvalho, Hugo
;
Morgado, José
;
Garcia, Nuno M
;
Pires, Ivan Miguel
Stress is or could be one of the most talked-about and recurring things in recent years, because of the world that we live. Stress is our body's response to a pressure thing or situation in our life. In this way, countless things have a stressful impact on our lives. On the other hand, stress is usually due to something new or unexpected, that somehow is beyond our control. The effects on our body are evident, inevitably having symptoms. When we are exposed to stress, certain hormones are released in our body, and the immune system is working on selfdefence. During this, breathing becomes faster, heart rate increases, muscles contract and blood pressure also increases. Thus, the organism is ready to act to protect itself. It is where our project comes in, because, with these symptoms of our body, they allow stress to be identified. This paper is focused on precisely that, because, by reading the person's vital data, we can establish standards of normality, which, when they suffer variation, may indicate to us in advance that the person is stressed and help him to control himself so that there is no more significant damage. With this, we hope to obtain positive results in people's lives and routine, causing the stress rate to drop worldwide.
Some of the metrics are blocked by your
consent settings
Experimental Study on Wound Area Measurement with Mobile Devices
(MDPI, 2021-08-26)
Ferreira, Filipe
;
Pires, Ivan Miguel
;
Ponciano, Vasco
;
Costa, Mónica
;
Villasana, María Vanessa
Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely. This study proposes a method for measuring the wound area with mobile devices. The proposed approach relies on a multi-step process consisting of image capture, conversion to grayscale, blurring, application of a threshold with segmentation, identification of the wound part, dilation and erosion of the detected wound section, identification of accurate data related to the image, and measurement of the wound area. The proposed method was implemented with the OpenCV framework. Thus, it is a solution for healthcare systems by which to investigate and treat people with skin-related diseases. The proof-of-concept was performed with a static dataset of camera images on a desktop computer. After we validated the approach’s feasibility, we implemented the method in a mobile application that allows for communication between patients, caregivers, and healthcare professionals.
Some of the metrics are blocked by your
consent settings
Monitoring of Cardiovascular Diseases: An Analysis of the Mobile Applications Available in the Google Play Store
(MDPI, 2022-06-15)
Vitaliyivna Denysyuk, Hanna
;
Amado, João
;
Gonçalves, Norberto Jorge
;
;
Garcia, Nuno M
Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the needs of the patients. This study reviews mobile applications that allow patients to monitor and report cardiovascular diseases. It presents a review of 14 mobile applications that were free to download in Portugal and classified and compared according to their characteristics. The selection criteria combined the following keywords: “patient”, “cardiac/or heart”, “report”, and (“tracking” or “monitoring”). Based on the analysis, we point out the errors of the applications and present some solutions. To finish, we investigated how mobile applications can help patients track and self-report cardiovascular diseases.
Some of the metrics are blocked by your
consent settings
Identification of Activities of Daily Living through Artificial Intelligence: an accelerometry-based approach
(Elsevier, 2020-01-01)
Pires, Ivan Miguel
;
Marques, Gonçalo
;
Garcia, Nuno M
;
The accelerometer is available on most of these mobile devices. It allows the acquisition and calculation of different physical parameters. Due to the use of pattern recognition, it also enables the identification of several Activities of Daily Living (ADL), such as walking, running, going downstairs, going upstairs, and standing. The feature extraction step performs the extraction of the five most significant distances between peaks, the average, standard deviation, variance and median of extracted peaks and raw data, and the maximum and minimum of raw data. The focus of this paper is the implementation of multiple artificial intelligence methods for the recognition of ADL, including Logistic Regression, Combined nomenclature rule inducer, Neural Network, Naive Bayes, Support Vector Machine, Decision Tree, Stochastic Gradient Descent, and k-Nearest Neighbor.
Some of the metrics are blocked by your
consent settings
Technological solutions for sign language recognition: a scoping review of research trends, challenges, and opportunities
(IEEE, 2022-03-22)
;
Pires, Ivan Miguel
;
;
;
Melero, Francisco José
Sign languages are critical in conveying meaning by the use of a visual-manual modality and are the primary means of communication of the deaf and hard of hearing with their family members and with the society. With the advances in computer graphics, computer vision, neural networks, and the introduction of new powerful hardware, the research into sign languages has shown a new potential. Novel technologies can help people learn, communicate, interpret, translate, visualize, document, and develop various sign languages and their related skills. This paper reviews the technological advancements applied in sign language recognition, visualization, and synthesis. We defined multiple research questions to identify the underlying technological drivers that strive to improve the challenges in this domain. This study is designed in accordance with the PRISMA methodology. We searched for articles published between 2010 and 2021 in multiple digital libraries (i.e., Elsevier, Springer, IEEE, PubMed, and MDPI). To automate the initial steps of PRISMA for identifying potentially relevant articles, duplicate removal and basic screening, we utilized a Natural Language Processing toolkit. Then, we performed a synthesis of the existing body of knowledge and identified the different studies that achieved significant advancements in sign language recognition, visualization, and synthesis. The identified trends based on analysis of almost 2000 papers clearly show that technology developments, especially in image processing and deep learning, are driving new applications and tools that improve the various performance metrics in these sign language-related task. Finally, we identified which techniques and devices contribute to such results and what are the common threads and gaps that would open new research directions in the field.
Some of the metrics are blocked by your
consent settings
Daily motionless activities: A dataset with accelerometer, magnetometer, gyroscope, environment, and GPS data
(Nature Publishing Group, 2022-03-25)
Pires, Ivan Miguel
;
Garcia, Nuno M
;
;
The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in diferent locations, including the pants pockets, in a wristband, over the bedside table, on a table, inside the car, or on other furniture, for the acquisition of accelerometer, magnetometer, gyroscope, GPS, and microphone data. The data was collected by 25 individuals (15 men and 10 women) in diferent environments in Covilhã and Fundão municipalities (Portugal). The dataset includes the sensors’ captures related to a minimum of 2000 captures for each motionless activity, which corresponds to 2.8h (approximately) for each one. This dataset includes 8.4h (approximately) of captures for further analysis with data processing techniques, and machine learning methods. It will be useful for the complementary creation of a robust method for the identifcation of these type of activities.
Some of the metrics are blocked by your
consent settings
Can the Eight Hop Test Be Measured with Sensors? A Systematic Review
(MDPI, 2022-05-08)
Pimenta, Luís
;
Garcia, Nuno M
;
;
;
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.
Some of the metrics are blocked by your
consent settings
Personal Digital Life Coach for Physical Therapy
(IEEE, 2020-12-10)
Popovski, Goce
;
Ponciano, Vasco
;
Marques, Gonçalo
;
Pires, Ivan Miguel
;
The functional tests are essential to test the functionality of different types of people, and specialty for older adults. The primary purpose of this paper is to create a method for the automatic measurement of the results of the different functional tests. These are the Heel-rise Test, Functional Reach Test, Timed Up and Go Test, Ten Meter Walk Test, Eight hop test, Up-down hop test, Side hop test, Single hop test, Chair Stand Test, Arm Curl Test, and Chair Sit and Reach test. The use of sensors may increase the accuracy of the measurements of these tests. These tests may identify several diseases, and it will be subject to further research in the future.

Faculty of Computer Science and Engineering

Browse

Filters

Settings

Sort By

Results per page

Search Results