A non-contact heart-rate monitoring system for long-term assessments of HRV

Ciucu, Radu; Dragomir, Dan; Adochiei, Ioana-Raluca; Serițan, George; Cepișcă, Costin; Adochiei, Felix-Constantin

doi:10.1109/atee.2017.7905060

Cited by 17 publications

(4 citation statements)

References 18 publications

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“…Let us stress the fact that although pure sparse signals (built of exactly k<<N atoms from a specified dictionary) are difficult to find, conventional results are valid for signals that are "almost sparse" (which can be built of k<<N non-negligible atoms) with respect to dictionaries that can be overcomplete (contain more atoms than their intrinsic dimension), as in the case of some classes of biomedical signals. Taking into consideration this fact, it has been found useful to adapt the theory of CS to the field of processing ECG and electroencephalographic (EEG) signals [2][3][4] as well as for applications [5] such as compression, transmission, reconstruction of ECG signals, ECG filtering and monitoring [6,27,[30][31][32].…”

Section: Compressed Sensed Overviewmentioning

confidence: 99%

“…Many of the papers that address CS focus on how to build specific dictionaries for signal reconstruction [13][14][15][16][17][18][19][20][21][22][23][24][25][26]. In the case of the ECG signal, due to its particularities, namely, the quasi-periodicity of the P, Q, R and S waves and the preservation of their shapes, many of the methods proposed in the literature focus on the advantages offered by these features specific to the ECG signal [27][28][29][30][31][32][33][34][35][36][37]. Thus, a large part of the methods proposed regarding CS of ECG signals aim at building dictionaries specific to these signals.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Dictionary Selection in Compressive Sensing for ECG Signals Compression and Classification

2022

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The paper proposes a comparative analysis of the projection matrices and dictionaries used for compressive sensing (CS) of electrocardiographic signals (ECG), highlighting the compromises between the complexity of preprocessing and the accuracy of reconstruction. Starting from the basic notions of CS theory, this paper proposes the construction of dictionaries (constructed directly by cardiac patterns with R-waves, centered or not-centered) specific to the application and the results of their testing. Several types of projection matrices are also analyzed and discussed. The reconstructed signals are analyzed quantitatively and qualitatively by standard distortion measures and by the classification of the reconstructed signals. We used a k-nearest neighbors (KNN) classifier to evaluate the reconstructed models. The KNN module was trained with the models from the mega-dictionary used in the classification block and tested with the models reconstructed with class-specific dictionaries. In addition to the KNN classifier, a neural network was used to test the reconstructed signals. The neural network was a multilayer perceptron (MLP). Moreover, the results are compared with those obtained with other compression methods, and ours proved to be superior.

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Section: Compressed Sensed Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Study on Dictionary Selection in Compressive Sensing for ECG Signals Compression and Classification

2022

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“…The Smart Home can assist its inhabitants with daily tasks such as cooking, cleaning, etc. Also, it can be part of a health monitoring system that can provide timely reminders for medication or signal specialized personnel to respond in case of a medical emergency [3]- [7].…”

Section: Introductionmentioning

confidence: 99%

Open Source Architecture for Iot Based SCADA System for Smart Home

Grigorescu

Serițan

Enache

et al. 2020

The Scientific Bulletin of Electrical Engineering Faculty

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The Internet of Things is considered an emerging technology with the potential to penetrate all aspects of our lives. However, with great power comes great responsibility and the privacy and security needed for critical infrastructure or sensitive commercial operations is very different than the needs of a Smart Home. Additionally, the available security resources from the private sector are totally different than the ones available to a homeowner. In this context, we developed an open source architecture for IoT which is based on the advantages of a SCADA system and can be easily applied to a Smart Home. This architecture assures a high-security level, even for low technical skills homeowners, with minimal costs.

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“…In this paper, we proposed a platform dedicated to recording ECG, HR and SpO2 using a WBAN application for Android devices as well as tracking using GPS and BARO altitude data from the mobile terminal for real-time positioning on a 3D model of a mountain. In the Materials and Methods section, we will describe the data types used for the tracking application, the correlation between the altitude and GPS data, the topography iles used in the 3D reconstruction of the mountain area and the methods we used for the representation of HR and ECG and SpO2 on the 3D map [18,19]. The results section will showcase each platform component.…”

Section: Introductionmentioning

confidence: 99%

A Data Analysis platform for high altitude bio monitoring using DEVOPS principles and time series machine learning

2019

J. adv. tec. eng. res.

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In this paper we propose a software platform for correlating real-time physiological data using microservices and time series analysis with machine learning. We use a devops type architecture with multiple containers governing speci ic aspects of our platform. In order to run the analytics and correlation protocol several microservices had been designed to orchestrate and process multiple data streams in real time. The data ingested by our platform is provided in an intuitive data visualization interface that binds together digital elevation models and geospatial data with the blood oxygen saturation and heart rate of a subject. The platform provides an accurate representation of a subjects physical performance in high altitude/low oxygen environments.

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A non-contact heart-rate monitoring system for long-term assessments of HRV

Cited by 17 publications

References 18 publications

A Study on Dictionary Selection in Compressive Sensing for ECG Signals Compression and Classification

A Study on Dictionary Selection in Compressive Sensing for ECG Signals Compression and Classification

Open Source Architecture for Iot Based SCADA System for Smart Home

A Data Analysis platform for high altitude bio monitoring using DEVOPS principles and time series machine learning

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