Towards assisted electrocardiogram interpretation using an AI-enabled Augmented Reality headset

Lampreave, P.; Jiménez-Pérez, Guillermo; Sanz, Ismael; Gómez, Alberto; Cámara, Óscar

doi:10.1080/21681163.2020.1835544

Cited by 5 publications

(5 citation statements)

References 24 publications

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“…A sample of the differences can be seen in Figure 7. Devices designed primarily for AR include Microsoft HoloLens [59], Magic Leap One [60], Google Glass [51], and Meta 2 [61], to name a few. There are also some more specialized AR hardware options such as the Daqri Smart Helmet [62].…”

Section: Hardwarementioning

confidence: 99%

Augmented Reality: Current and New Trends in Education

Kamińska,

Zwoliński,

Laska-Leśniewicz

et al. 2023

Electronics

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The educational landscape is an environment prone to change due to the volatile and ever-changing nature of the digital society in which we all live. Although the world moves at different speeds and any generalization is bound to have some exceptions, there is evidence from research conducted in different places and contexts that educational methods are becoming increasingly digitized and driven by technological innovation. Among the technological trends fueled in many cases by the COVID-19 pandemic and the need to stay at home but online, augmented reality solutions received an additional boost as a valid and versatile educational technology worth exploring and eventually integrating into several teaching methods already in use. Although the technology still faces problems related to affordability, accessibility, and the technical skills required of users, some ongoing projects have already provided evidence that using augmented reality solutions as teaching and learning tools can improve teacher and student learning outcomes by increasing engagement and interactivity. The same issues arose when personal computers, tablets, and smartphones were first discussed as valuable tools for education and have now found their way into most classrooms. This paper reviews some of the key concepts related to augmented reality, as well as some current trends, benefits, and concerns related to its integration into educational contexts in areas such as life sciences, engineering, and health. The work conducted and presented in this paper provides an interesting insight into a technology that has given rise to global phenomena such as Pokémon Go, and continues to improve in terms of portability, usability, and overall user experience. Throughout the paper and in the conclusion section, we discuss the relevance of using the best features of augmented reality and how they can contribute to positive educational outcomes.

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Section: Hardwarementioning

confidence: 99%

Augmented Reality: Current and New Trends in Education

Kamińska,

Zwoliński,

Laska-Leśniewicz

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

Section: Hardwarementioning

confidence: 99%

Augmented Reality: Current and New Trends in Education

Kamińska¹,

Zwoliński²,

Laska-Leśniewicz³

et al. 2023

Preprint

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The education landscape is an environment prone to change due to the volatile and ever-changing nature of the digital society in which we all live. Although the world moves at a different pace and any generalization is bound to have several exceptions, there is evidence from research conducted in different places and contexts that educational methods are becoming increasingly digitized and driven by technological innovation. Among technological trends fuelled in many cases by the COVID-19 pandemic and the need to stay at home but online, augmented reality solutions received an additional push as a valid and versatile educational technology worth exploring and eventually integrating into several teaching methods already in use. Although the technology still faces problems related to its affordability, accessibility, and the technical skills required of users, some ongoing projects have already provided evidence that using augmented reality solutions as teaching and learning tools can improve teachers’ and students’ learning outcomes by increasing their engagement and interactivity. The same issues arose when personal computers, tablets, and smartphones were first discussed as valuable tools for education and have now found their way into most classrooms. This paper reviews some of the key concepts related to augmented reality, as well as some current trends, benefits, and concerns related to its inclusion in educational contexts in areas such as life sciences, engineering, and health. The work carried out and presented in this paper provides an interesting insight into a technology that has led to global phenomena, such as Pokémon Go, and is constantly improving in terms of portability, usability, and overall user experience. Throughout the paper and in the conclusions section, we discuss the relevance of using the best features of augmented reality and how they can contribute to positive educational outcomes.

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“…The ECG signals are pre-processed to eliminate noise at high frequency range. The features are extracted using DWT to locate different parameters of the ECG signal like detecting peaks (P, Q, R, S and T) and QRS interval [17,18] which are helpful for diagnosing of arrhythmia conditions.…”

Section: Denoising Processmentioning

confidence: 99%

“…Some learning methods in the literature are Recurrent Neural Networks (RNNs), Deep Neural Networks (DNNs) [16,17] and Convolutional Neural Networks (CNNs) [18]. CNN model has two dimensional hidden layer/ weight connected to the upper layer/ weight.…”

Section: Convnet Classificationmentioning

confidence: 99%

See 1 more Smart Citation

ConvNet: 1D-Convolutional Neural Networks for Cardiac Arrhythmia Recognition Using ECG Signals

Slama¹,

Sahli²,

Maalmi³

et al. 2021

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In healthcare, diagnostic tools of cardiac diseases are commonly known by the electrocardiogram (ECG) analysis. Atypical electrical activity can produce a cardiac arrhythmia. Various difficulties can be imposed to clinicians e.g., myocardial infarction arrhythmia via the non-stationarity and irregularity heart beat signals. Through the assistance of computer-aided diagnosis methods, timely specification of arrhythmia diseases reduces the mortality rate of affected patients. In this study, a 1 Lead QRS complex -layer deep convolutional neural network is proposed for the recognition of arrhythmia datasets. By the use of this CNN model, we planned a complete structure of the classification architecture after a pre-processing stage counting the denoising and QRS complex signals detection procedure. The chief benefit of the new proposed methodology is that the automatically training the QRS complexes without requiring all original extracted ECG signals. The proposed model was trained on the increased ECG database and separated into five classes. Experimental results display that the established CNN method has improved performance when compared to the state-of-the-art studies.

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Towards assisted electrocardiogram interpretation using an AI-enabled Augmented Reality headset

Cited by 5 publications

References 24 publications

Augmented Reality: Current and New Trends in Education

Augmented Reality: Current and New Trends in Education

Augmented Reality: Current and New Trends in Education

ConvNet: 1D-Convolutional Neural Networks for Cardiac Arrhythmia Recognition Using ECG Signals

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