| 1. |
- Apiola, Mikko, et al.
(author)
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Experiences from Digital Learning Analytics in Finland and Sweden : A Collaborative Approach
- 2019
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In: 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). - : IEEE. - 9781538692967 - 9789532330984 ; , s. 627-632, s. 627-632
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Conference paper (peer-reviewed)abstract
- Digital learning management systems (LMS) are revolutionizing learning in many areas, including computer science education (CSE). They are capable of tracking learners' characteristics, such as prior knowledge, and other learning habits, and may offer more personalized learning or guidance on useful learning practices. LMSs collect large amounts of data. Proper processing of such collected data can offer valuable insights about the learning process, support for higher quality education, insights on why some students drop out of courses, and so on. In this paper, we briefly review and discuss the global trends in digital learning and learning lnalytics (LA), specifically from the viewpoint of two LMS systems and related LA research, one in Finland and one in Sweden. In this paper, we address the context-, and course-specific nature of LA by developing the idea of cross-country and cross-systems learning analytics. Second, we consider our research especially from an educational perspective to identify the most beneficial practices for teachers and students. Third, we discuss, based on findings from our projects, future avenues for research.
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| 2. |
- Tomasic, Ivan, et al.
(author)
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Comparison of publicly available beat detection algorithms performanances on the ECGs obtained by a patch ECG device
- 2019
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In: 2019 42ND INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO). - : IEEE. - 9789532330984 ; , s. 275-278
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Conference paper (peer-reviewed)abstract
- Eight ECG beat detection algorithms, from the PhysioNet's WFDR and Cardiovascular Signal toolboxes, were tested on twenty measurements, obtained by the Savvy patch ECG device, for their accuracy in beat detection. On each subject, one measurement is obtained while sitting and one while running. Each measurement lasted from thirty seconds to one minute. The measurements obtained while running were more challenging for all the algorithms, as most of them almost perfectly detected all the beats on the measurements obtained in sitting position. However, when applied on the measurements obtained while running, all the algorithms have performed with decreased accuracy. Considering overall percentage of the faulty detected peaks, the four best algorithms were jqrs, from the Cardiovascular Signal Toolbox, and ecgpuwave, gqrs, and wqrs, from the WEDB Toolbox, with percentages of faulty detected beats 1.7, 2.3, 2.9, and 3, respectively.
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| 3. |
- Tomasic, Ivan, et al.
(author)
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Comparison of publicly available beat detection algorithms performances on the ECGs obtained by a patch ECG device
- 2019
-
In: 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9789532330984 ; , s. 275-278
-
Conference paper (peer-reviewed)abstract
- Eight ECG beat detection algorithms, from the PhysioNet's WFDB and Cardiovascular Signal toolboxes, were tested on twenty measurements, obtained by the Savvy patch ECG device, for their accuracy in beat detection. On each subject, one measurement is obtained while sitting and one while running. Each measurement lasted from thirty seconds to one minute. The measurements obtained while running were more challenging for all the algorithms, as most of them almost perfectly detected all the beats on the measurements obtained in sitting position. However, when applied on the measurements obtained while running, all the algorithms have performed with decreased accuracy. Considering overall percentage of the faulty detected peaks, the four best algorithms were jqrs, from the Cardiovascular Signal Toolbox, and ecgpuwave, gqrs, and wqrs, from the WFDB Toolbox, with percentages of faulty detected beats 1.7, 2.3, 2.9, and 3, respectively.
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| 4. |
- Trobec, R., et al.
(author)
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Detection and Treatment of Atrial Irregular Rhythm with Body Gadgets and 35-channel ECG
- 2019
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In: 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9789532330984 ; , s. 301-308
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Conference paper (peer-reviewed)abstract
- The atrial irregular rhythm, often reflected in atrial fibrillation, undulation or flutter, is recognized as one of the major causes of brain stroke and entails an increased risk of thromboembolic events because it increases the likelihood of blood clots formation. Its early detection is becoming an increasingly important preventive measure. The paper presents a simple methodology for the detection of atrial irregular rhythm by ECG body gadget that can perform long-term measurements, e.g. several weeks or more. Multichannel ECG, on the body surface, gives a more detailed insight into the atrial activity in comparison to standard 12-lead ECG. The information from MECG is compared with single-channel patch ECG. The obtained results suggest that the proposed methodology could be useful in treatments of atrial irregular rhythm. One can obtain a reliable information about the time and duration of fibrillation events, or determine arrhythmic focuses and conductive pathways in heart atria, or study the effects of antiarrhythmic drugs on existing arrhythmias and on an eventual development of new types of arrhythmias.
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