1
|
Francisti J, Balogh Z, Reichel J, Benko Ľ, Fodor K, Turčáni M. Identification of heart rate change during the teaching process. Sci Rep 2023; 13:16674. [PMID: 37794176 PMCID: PMC10550993 DOI: 10.1038/s41598-023-43763-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 09/28/2023] [Indexed: 10/06/2023] Open
Abstract
Internet of Things (IoT) technology can be used in many areas of everyday life. The objective of this paper is to obtain physiological functions in a non-invasive manner using commonly available IoT devices. The aim of the research is to point out the possibility of using physiological functions as an identifier of changes in students' level of arousal during the teaching process. The motivation of the work is to find a correlation between the change in heart rate, the student's level of arousal and the student's partial and final learning results. The research was focused on the collection of physiological data, namely heart rate and the evaluation of these data in the context of identification of arousal during individual teaching activities of the teaching process. The experiment was carried out during the COVID-19 pandemic via distance learning. During the teaching process, individual activities were recorded in time and HR was assigned to them. The benefit of the research is the proposed methodology of the system, which can identify changes in students' arousal in order to increase the efficiency of the teaching process. Based on the results of the designed system, they could also alert teachers who should be able to modify their teaching style in specific situations so that it is suitable for students and provides a basis for better teaching and understanding of educational materials. The presented methodology will be able to guarantee an increase in the success of the teaching process itself in terms of students' understanding of the teaching materials.
Collapse
Affiliation(s)
- Jan Francisti
- Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia
| | - Zoltán Balogh
- Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia
- Kandó Kálmán Faculty of Electrical Engineering, Óbuda University, Budapest, Hungary
| | - Jaroslav Reichel
- Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia
| | - Ľubomír Benko
- Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia
| | - Kristián Fodor
- Kandó Kálmán Faculty of Electrical Engineering, Óbuda University, Budapest, Hungary.
| | - Milan Turčáni
- Department of Informatics, Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Nitra, Slovakia
| |
Collapse
|
2
|
Shiwani MA, Chico TJA, Ciravegna F, Mihaylova L. Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies. SENSORS (BASEL, SWITZERLAND) 2023; 23:5752. [PMID: 37420916 PMCID: PMC10300851 DOI: 10.3390/s23125752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/01/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.
Collapse
Affiliation(s)
- Muhammad Ali Shiwani
- Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield S1 3JD, UK
| | - Timothy J. A. Chico
- Department of Infection, Immunity and Cardiovascular Disease, The Medical School, The University of Sheffield, Sheffield S10 2RX, UK
| | - Fabio Ciravegna
- Dipartimento di Informatica, Università di Torino, 10124 Turin, Italy
| | - Lyudmila Mihaylova
- Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield S1 3JD, UK
| |
Collapse
|
3
|
Boudet G, Chausse P, Thivel D, Rousset S, Mermillod M, Baker JS, Parreira LM, Esquirol Y, Duclos M, Dutheil F. How to Measure Sedentary Behavior at Work? Front Public Health 2019; 7:167. [PMID: 31355172 PMCID: PMC6633074 DOI: 10.3389/fpubh.2019.00167] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 06/05/2019] [Indexed: 12/23/2022] Open
Abstract
Background: Prolonged sedentary behavior (SB) is associated with increased risk for chronic conditions. A growing number of the workforce is employed in office setting with high occupational exposure to SB. There is a new focus in assessing, understanding and reducing SB in the workplace. There are many subjective (questionnaires) and objective methods (monitoring with wearable devices) available to determine SB. Therefore, we aimed to provide a global understanding on methods currently used for SB assessment at work. Methods: We carried out a systematic review on methods to measure SB at work. Pubmed, Cochrane, Embase, and Web of Science were searched for peer-reviewed English-language articles published between 1st January 2000 and 17th March 2019. Results: We included 154 articles: 89 were cross-sectional and 65 were longitudinal studies, for a total of 474,091 participants. SB was assessed by self-reported questionnaires in 91 studies, by wearables devices in also 91 studies, and simultaneously by a questionnaire and wearables devices in 30 studies. Among the 91 studies using wearable devices, 73 studies used only one device, 15 studies used several devices, and three studies used complex physiological systems. Studies exploring SB on a large sample used significantly more only questionnaires and/or one wearable device. Conclusions: Available questionnaires are the most accessible method for studies on large population with a limited budget. For smaller groups, SB at work can be objectively measured with wearable devices (accelerometers, heart-rate monitors, pressure meters, goniometers, electromyography meters, gas-meters) and the results can be associated and compared with a subjective measure (questionnaire). The number of devices worn can increase the accuracy but make the analysis more complex and time consuming.
Collapse
Affiliation(s)
- Gil Boudet
- Faculté de Médecine, Institut de Médecine du Travail, Université Clermont-Auvergne, Clermont-Ferrand, France
| | - Pierre Chausse
- Cellule d'Accompagnement Technologique-Department of Technological Accompaniment, CNRS, LaPSCo, Université Clermont Auvergne, Clermont-Ferrand, France
| | - David Thivel
- Laboratory of the Metabolic Adaptations to Exercise Under Physiological and Pathological Conditions (AME2P EA 3533), Université Clermont Auvergne, Clermont-Ferrand, France.,Institut Universitaire de France, Paris, France
| | - Sylvie Rousset
- Unité de Nutrition Humaine, INRA, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Martial Mermillod
- Institut Universitaire de France, Paris, France.,LPNC, CNRS, Université Grenoble Alpes, Université Savoie Mont Blanc, Grenoble, France
| | - Julien S Baker
- School of Science and Sport, Institute of Clinical Exercise and Health Sciences, University of the West of Scotland, Hamilton, United Kingdom
| | - Lenise M Parreira
- Faculté de Médecine, Institut de Médecine du Travail, Université Clermont-Auvergne, Clermont-Ferrand, France
| | - Yolande Esquirol
- Occupational and Preventive Medicine, INSERM UMR-1027, Université Paul Sabatier Toulouse 3, CHU Toulouse, Toulouse, France
| | - Martine Duclos
- Sport Medicine and Functional Explorations, CRNH, INRA UMR-1019, University Hospital of Clermont-Ferrand, Université Clermont Auvergne, CHU Clermont-Ferrand, Clermont-Ferrand, France
| | - Frédéric Dutheil
- LaPSCo, Physiological and Psychosocial Stress, Preventive and Occupational Medicine, CNRS, University Hospital of Clermont-Ferrand, Université Clermont Auvergne, CHU Clermont-Ferrand, WittyFit, Clermont-Ferrand, France.,Faculty of Health, School of Exercise Science, Australian Catholic University, Melbourne, VIC, Australia
| |
Collapse
|