Analysis of stress’s effects on cardiac dynamics: A case study on undergraduate students

Cubillos-Calvachi, Juan; Piedrahita-Gonzalez, Juan; Gutiérrez-Ardila, Carlos; Montenegro-Marín, Carlos Enrique; Gaona-García, Paulo Alonso; Burgos, Daniel

doi:10.1016/j.ijmedinf.2020.104104

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…We assume that during testing, the level of stress may increase and thus the heart rate will also increase. The dependence of heart rate and stress has already been studied by many authors [4][5][6][7][8][9]. We also reveal the dependence of the student's heart rate before learning that they would be tested and during testing, and we monitored this change.…”

Section: Introductionmentioning

confidence: 84%

“…The time was set empirically so that the time quantum allocated to answer the questions evokes competition among students and thus indirectly the middle situation and the change (expected increase) of HR. The relationship between stress and HR has already been described by the authors in their research [3,4]. A smart wristband was used to monitor the participants' physiological conditions, measuring their heart rate.…”

Section: Methodsmentioning

confidence: 99%

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Application Experiences Using IoT Devices in Education

et al. 2020

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The Internet of Things (IoT) is becoming a regular part of our lives. The devices can be used in many sectors, such as education and in the learning process. The article describes the possibilities of using commonly available devices such as smart wristbands (watches) and eye tracking technology, i.e., using existing technical solutions and methods that rely on the application of sensors while maintaining non-invasiveness. By comparing the data from these devices, we observed how the students’ attention affects their results. We looked for a correlation between eye tracking, heart rate, and student attention and how it all impacts their learning outcomes. We evaluate the obtained data in order to determine whether there is a degree of dependence between concentration and heart rate of students.

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Section: Introductionmentioning

confidence: 84%

Section: Methodsmentioning

confidence: 99%

Application Experiences Using IoT Devices in Education

et al. 2020

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“…Finally, the heart rate data are analyzed using the theory of probability. The previous system is used for studying stress' effects on cardiac dynamics [ 24 ].…”

Section: Related Workmentioning

confidence: 99%

IoT Based System for Heart Monitoring and Arrhythmia Detection Using Machine Learning

Cañón-Clavijo

Herrera‐Viedma

Gaona-García

et al. 2023

Journal of Healthcare Engineering

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Internet of Things (IoT) technologies allow building a digital representation of people, objects, or physical phenomena to be available on the Internet. Thus, stakeholders can access this information from remote places or computational systems could analyze this data to find patterns, make decisions, or execute actions. For instance, a doctor could diagnose patients by analyzing the received data from an IoT system even when patients are located in a remote place. This article proposes an IoT system for monitoring electrocardiogram (ECG) signal and processing heart data in order to generate an alert when an arrhythmia is present. This system involves a Polar H10 heart sensor, machine-learning models to classify heart events, and communication technology to share and store patient’s information. In the first place, the architecture of the IoT monitoring system and the communication between the components are described by discussing the designing criteria. Second, the experimentation process performs the training and the assessment of three classification algorithms, random forest, convolutional neural network, and k-nearest neighbors. The results show that k-nearest neighbor has the best accuracy percentage classifying the arrhythmias under study (premature ventricular contraction 94%, fusion of ventricular beat 81%, and supraventricular premature beat 82%); also, it is able to discern normal and unclassifiable beats with 93% and 97%, respectively.

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“…Stress can also be measured using intelligent wearable devices 5 , 71 . In the research, the authors used wearable devices that can measure heart activity (HR, HRV) and identify the presence of stress based on the obtained values.…”

Section: Related Workmentioning

confidence: 99%

“…In our research, we used the physiological function of the heart rate (HR). To be able to measure the HR of students and not disturb them in class, we used wireless smart wristbands which contained a sensor capable of measuring the mentioned physiological function 5 .…”

Section: Introductionmentioning

confidence: 99%

Identification of heart rate change during the teaching process

Francisti,

Balogh,

Reichel

et al. 2023

Sci Rep

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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.

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Analysis of stress’s effects on cardiac dynamics: A case study on undergraduate students

Cited by 7 publications

References 9 publications

Application Experiences Using IoT Devices in Education

Application Experiences Using IoT Devices in Education

IoT Based System for Heart Monitoring and Arrhythmia Detection Using Machine Learning

Identification of heart rate change during the teaching process

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