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Francisco L, Duarte J, Godinho AN, Zdravevski E, Albuquerque C, Pires IM, Coelho PJ. Sensor-based systems for the measurement of Functional Reach Test results: a systematic review. PeerJ Comput Sci 2024; 10:e1823. [PMID: 38660214 PMCID: PMC11042010 DOI: 10.7717/peerj-cs.1823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/26/2023] [Indexed: 04/26/2024]
Abstract
The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person's balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based systems to objectively and accurately measure FRT results. This systematic review was performed in various scientific databases or publishers, including PubMed Central, IEEE Explore, Elsevier, Springer, the Multidisciplinary Digital Publishing Institute (MDPI), and the Association for Computing Machinery (ACM), and considered studies published between January 2017 and October 2022, related to methods for the automation of the measurement of the Functional Reach Test variables and results with sensors. Camera-based devices and motion-based sensors are used for Functional Reach Tests, with statistical models extracting meaningful information. Sensor-based systems offer several advantages over traditional manual measurement techniques, as they can provide objective and precise measurements of the reach distance, quantify postural sway, and capture additional parameters related to the movement.
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Affiliation(s)
- Luís Francisco
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
| | - João Duarte
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
| | | | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University of Sts. Cyril and Methodius, Skopje, North Macedonia
| | - Carlos Albuquerque
- Child Studies Research Center (CIEC), University of Minho, Braga, Portugal
- Higher School of Health, Polytechnic Institute of Viseu, Viseu, Portugal
- Nursing School of Coimbra (ESEnfC), Health Sciences Research Unit: Nursing (UICISA: E), Coimbra, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, Águeda, Portugal
| | - Paulo Jorge Coelho
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), Coimbra, Portugal
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2
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Francisco L, Duarte J, Albuquerque C, Albuquerque D, Pires IM, Coelho PJ. Mobile Data Gathering and Preliminary Analysis for the Functional Reach Test. Sensors (Basel) 2024; 24:1301. [PMID: 38400459 PMCID: PMC10892343 DOI: 10.3390/s24041301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/11/2024] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper aims to describe a new tool to gather and analyze the data from inertial sensors to allow automation and increased reliability in the future by removing practitioner bias and facilitating the FRT procedure. A new tool for gathering and analyzing data from inertial sensors has been developed to remove practitioner bias and streamline the FRT procedure. The study involved 54 senior citizens using smartphones with sensors to execute FRT. The methods included using a mobile app to gather data, using sensor-fusion algorithms like the Madgwick algorithm to estimate orientation, and attempting to estimate location by twice integrating accelerometer data. However, accurate position estimation was difficult, highlighting the need for more research and development. The study highlights the benefits and drawbacks of automated balance assessment testing with mobile device sensors, highlighting the potential of technology to enhance conventional health evaluations.
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Affiliation(s)
- Luís Francisco
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
| | - João Duarte
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
| | - Carlos Albuquerque
- Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3004-011 Coimbra, Portugal;
- Higher School of Health, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal
- Child Studies Research Center (CIEC), University of Minho, 4710-057 Braga, Portugal
| | - Daniel Albuquerque
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, 3750-127 Águeda, Portugal; (D.A.); (I.M.P.)
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, 3750-127 Águeda, Portugal; (D.A.); (I.M.P.)
| | - Paulo Jorge Coelho
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), 3030-290 Coimbra, Portugal
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3
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Gabriel CL, Pires IM, Gonçalves NJ, Coelho PJ, Zdravevski E, Lameski P, Albuquerque C, Garcia NM, Carreto C. Ten meter walk test with mobile devices: A dataset with accelerometer, magnetometer, and gyroscope. Data Brief 2024; 52:109867. [PMID: 38146301 PMCID: PMC10749228 DOI: 10.1016/j.dib.2023.109867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 11/06/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023] Open
Abstract
This paper presents a dataset related to the performance of the Ten Meter Walking Test, a test to allow locomotor capacity in different research and clinical settings. One of the most important parameters to measure is the gait speed during a path of ten meters. The data available in this dataset consists of accelerometer, magnetometer, and gyroscope data acquired with a mobile device in a waistband. The experiments were performed two times by 109 individuals (30 males and 79 females) in different senior residences in the Fundão municipality (Portugal). The dataset includes 208 samples because the sensors reported some failures. The acquisition of the sensors data allows the creation of a technological method for the automatic measurement of features related to the Ten Meter Walk Test, promoting patient independence in measuring their physical health status.
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Affiliation(s)
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, Águeda, Portugal
| | - Norberto Jorge Gonçalves
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Paulo Jorge Coelho
- Polytechnic of Leiria, Leiria, Portugal
- Department of Electrical and Computer Engineering, INESC Coimbra, University of Coimbra, Pólo 2, 3030-290 Coimbra, Portugal
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Carlos Albuquerque
- Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Coimbra, Portugal
- Higher School of Health of the Polytechnic Institute of Viseu, Viseu, Portugal
- Child Studies Research Center (CIEC), University of Minho, Braga, Portugal
| | - Nuno M. Garcia
- Instituto de Telecomunicações, 6201-001 Covilhã, Portugal
- Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Carlos Carreto
- Research Unit for Inland Development, Polytechnic of Guarda, Guarda, Portugal
- CISE—Electromechatronic Systems Research Centre, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
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Vieira R, Silva D, Ribeiro E, Perdigoto L, Coelho PJ. Performance Evaluation of Computer Vision Algorithms in a Programmable Logic Controller: An Industrial Case Study. Sensors (Basel) 2024; 24:843. [PMID: 38339560 PMCID: PMC10856825 DOI: 10.3390/s24030843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/20/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024]
Abstract
This work evaluates the use of a programmable logic controller (PLC) from Phoenix Contact's PLCnext ecosystem as an image processing platform. PLCnext controllers provide the functions of "classical" industrial controllers, but they are based on the Linux operating system, also allowing for the use of software tools usually associated with computers. Visual processing applications in the Python programming language using the OpenCV library are implemented in the PLC using this feature. This research is focused on evaluating the use of this PLC as an image processing platform, particularly for industrial machine vision applications. The methodology is based on comparing the PLC's performance against a computer using standard image processing algorithms. In addition, a demonstration application based on a real-world scenario for quality control by visual inspection is presented. It is concluded that despite significant limitations in processing power, the simultaneous use of the PLC as an industrial controller and image processing platform is feasible for applications of low complexity and undemanding cycle times, providing valuable insights and benchmarks for the scientific community interested in the convergence of industrial automation and computer vision technologies.
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Affiliation(s)
- Rodrigo Vieira
- School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal (E.R.); (L.P.)
| | - Dino Silva
- School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal (E.R.); (L.P.)
| | - Eliseu Ribeiro
- School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal (E.R.); (L.P.)
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), 3030-290 Coimbra, Portugal
| | - Luís Perdigoto
- School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal (E.R.); (L.P.)
- Institute of Systems and Robotics, University of Coimbra, 3030-290 Coimbra, Portugal
| | - Paulo Jorge Coelho
- School of Technology and Management, Polytechnic University of Leiria, 2411-901 Leiria, Portugal (E.R.); (L.P.)
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), 3030-290 Coimbra, Portugal
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5
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Gabriel CL, Pires IM, Coelho PJ, Zdravevski E, Lameski P, Mewada H, Madeira F, Garcia NM, Carreto C. Mobile and wearable technologies for the analysis of Ten Meter Walk Test: A concise systematic review. Heliyon 2023; 9:e16599. [PMID: 37274667 PMCID: PMC10238910 DOI: 10.1016/j.heliyon.2023.e16599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 05/18/2023] [Accepted: 05/22/2023] [Indexed: 06/06/2023] Open
Abstract
Physical issues started to receive more attention due to the sedentary lifestyle prevalent in modern culture. The Ten Meter Walk Test allows measuring the person's capacity to walk along 10 m and analyzing the advancement of various medical procedures for ailments, including stroke. This systematic review is related to the use of mobile or wearable devices to measure physical parameters while administering the Ten Meter Walk Test for the analysis of the performance of the test. We applied the PRISMA methodology for searching the papers related to the Ten Meter Walk Test. Natural Language Processing (NLP) algorithms were used to automate the screening process. Various papers published in two decades from multiple scientific databases, including IEEE Xplore, Elsevier, Springer, EMBASE, SCOPUS, Multidisciplinary Digital Publishing Institute (MDPI), and PubMed Central were analyzed, focusing on various diseases, devices, features, and methods. The study reveals that chronometer and accelerometer sensors measuring spatiotemporal features are the most pertinent in the Gait characterization of most diseases. Likewise, all studies emphasized the close relation between the quality of the sensor's data obtained and the system's ultimate accuracy. In other words, calibration procedures are needed because of the body part where the sensor is worn and the type of sensor. In addition, using ambient sensors providing kinematic and kinetic features in conjunction with wearable sensors and consistently acquiring walking signals can enhance the system's performance. The most common weaknesses in the analyzed studies are the sample size and the unavailability of continuous monitoring devices for measuring the Ten Meter Walk Test.
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Affiliation(s)
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, 6201-001 Covilhã, Portugal
- Department of Informatics and Quantitative Methods, Research Centre for Arts and Communication (CIAC)/Pole of Digital Literacy and Social Inclusion, Polytechnic Institute of Santarém, 2001-904 , Santarém, Portugal
| | - Paulo Jorge Coelho
- Polytechnic of Leiria, Leiria, Portugal
- INESC Coimbra, University of Coimbra, Department of Electrical and Computer Engineering, Pólo 2, 3030-290, Coimbra, Portugal
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000, Skopje, Macedonia
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000, Skopje, Macedonia
| | - Hiren Mewada
- Department of Electrical Engineering, Prince Mohammad Bin Fahd University, Al Khobar, 31952, Kingdom of Saudi Arabia
| | - Filipe Madeira
- Department of Informatics and Quantitative Methods, Research Centre for Arts and Communication (CIAC)/Pole of Digital Literacy and Social Inclusion, Polytechnic Institute of Santarém, 2001-904 , Santarém, Portugal
| | - Nuno M. Garcia
- Instituto de Telecomunicações, 6201-001 Covilhã, Portugal
- Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
| | - Carlos Carreto
- Research Unit for Inland Development, Polytechnic of Guarda, Guarda, Portugal
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Duarte RP, Marinho FA, Bastos ES, Pinto RJ, Silva PM, Fermino A, Denysyuk HV, Gouveia AJ, Gonçalves NJ, Coelho PJ, Zdravevski E, Lameski P, Tripunovski T, Garcia NM, Pires IM. Corrigendum to "Extraction of notable points from ECG data: A description of a dataset related to 30-s seated and 30-s stand up" [Data in Brief, volume 46 (2023) 108874]. Data Brief 2023; 47:108994. [PMID: 36875224 PMCID: PMC9978457 DOI: 10.1016/j.dib.2023.108994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
Abstract
[This corrects the article DOI: 10.1016/j.dib.2022.108874.].
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Affiliation(s)
- Rui Pedro Duarte
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Francisco Alexandre Marinho
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Eduarda Sofia Bastos
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Rui João Pinto
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Pedro Miguel Silva
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Alice Fermino
- Computer Science Department, Universidade da Beira Interior, Covilhã 6200-001, Portugal
| | | | - António Jorge Gouveia
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Norberto Jorge Gonçalves
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Paulo Jorge Coelho
- School of Technology and Management, Polytechnic of Leiria, Leiria 2411-901, Portugal,Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), DEEC, Pólo II, Coimbra 3030-290, Portugal
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Toni Tripunovski
- Institute of Pathophysiology and Nuclear Medicine, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Nuno M. Garcia
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal
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Denysyuk HV, Pinto RJ, Silva PM, Duarte RP, Marinho FA, Pimenta L, Gouveia AJ, Gonçalves NJ, Coelho PJ, Zdravevski E, Lameski P, Leithardt V, Garcia NM, Pires IM. Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review. Heliyon 2023; 9:e13601. [PMID: 36852052 PMCID: PMC9958295 DOI: 10.1016/j.heliyon.2023.e13601] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 01/31/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023] Open
Abstract
The prevalence of cardiovascular diseases is increasing around the world. However, the technology is evolving and can be monitored with low-cost sensors anywhere at any time. This subject is being researched, and different methods can automatically identify these diseases, helping patients and healthcare professionals with the treatments. This paper presents a systematic review of disease identification, classification, and recognition with ECG sensors. The review was focused on studies published between 2017 and 2022 in different scientific databases, including PubMed Central, Springer, Elsevier, Multidisciplinary Digital Publishing Institute (MDPI), IEEE Xplore, and Frontiers. It results in the quantitative and qualitative analysis of 103 scientific papers. The study demonstrated that different datasets are available online with data related to various diseases. Several ML/DP-based models were identified in the research, where Convolutional Neural Network and Support Vector Machine were the most applied algorithms. This review can allow us to identify the techniques that can be used in a system that promotes the patient's autonomy.
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Key Words
- AI, Artificial Intelligence
- BNN, Binarized Neural Network
- CNN, Concolutional Neural Networks
- Cardiovascular diseases
- DL, Deep Learning
- DNN, Deep Neural Networks
- Diagnosis
- ECG sensors
- ECG, Electrocardiography
- GAN, Generative Adversarial Networks
- GMM, Gaussian Mixture Model
- GNB, Gaussian Naive bayes
- GRU, Gated Recurrent Unit
- LASSO, Least Absolute Shrinkage and Selection Operator
- LDA, Linear Discriminant Analysis
- LR, Linear Regression
- LSTM, Long Short-Term Memory
- ML, Machine Learning
- MLP, Multiplayer Perceptron
- MLR, Multiple Linear Regression
- NLP, Natural Language Processing
- POAF, Postoperative Atrial Fibrillation
- RF, Random Forest
- RNN, Recurrent Neural Network
- SHAP, SHapley Additive exPlanations
- SVM, Support Vector Machine
- Systematic review
- WHO, World Health Organization
- kNN, k-nearest neighbors
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Affiliation(s)
| | - Rui João Pinto
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Pedro Miguel Silva
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Rui Pedro Duarte
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Francisco Alexandre Marinho
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Luís Pimenta
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - António Jorge Gouveia
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Norberto Jorge Gonçalves
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
| | - Paulo Jorge Coelho
- Polytechnic of Leiria, Leiria, Portugal
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), Coimbra, Portugal
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, Macedonia
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, Macedonia
| | - Valderi Leithardt
- VALORIZA, Research Center for Endogenous Resources Valorization, Instituto Politécnico de Portalegre, 7300-555 Portalegre, Portugal
- COPELABS, Universidade Lusófona de Humanidades e Tecnologias, Lisboa, Portugal
| | - Nuno M. Garcia
- Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal
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8
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Duarte RP, Marinho FA, Bastos ES, Pinto RJ, Silva PM, Fermino A, Denysyuk HV, Gouveia AJ, Gonçalves NJ, Coelho PJ, Zdravevski E, Lameski P, Tripunovski T, Garcia NM, Pires IM. Extraction of notable points from ECG data: A description of a dataset related to 30-s seated and 30-s stand up. Data Brief 2023; 46:108874. [PMID: 36660441 PMCID: PMC9843242 DOI: 10.1016/j.dib.2022.108874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/01/2022] [Accepted: 12/29/2022] [Indexed: 01/07/2023] Open
Abstract
It is increasingly possible to acquire Electrocardiographic data with featured low-cost devices. The proposed dataset will help map different signals for various diseases related to Electrocardiography data. The dataset presented in this paper is related to the acquisition of electrocardiography data during the standing up and seated positions. The data was collected from 219 individuals (112 men, 106 women, and one other) in different environments, but they are in the Covilhã municipality. The dataset includes the 219 recordings and corresponds to the sensors' recordings of a 30 s sitting and a 30 s standing test, which checks to approximately 1 min for each one. This dataset includes 3.7 h (approximately) of recordings for further analysis with data processing techniques and machine learning methods. It will be helpful for the complementary creation of a robust method for identifying the characteristics of individuals related to Electrocardiography signals.
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Affiliation(s)
- Rui Pedro Duarte
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Francisco Alexandre Marinho
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Eduarda Sofia Bastos
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Rui João Pinto
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Pedro Miguel Silva
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Alice Fermino
- Computer Science Department, Universidade da Beira Interior, Covilhã 6200-001, Portugal
| | | | - António Jorge Gouveia
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Norberto Jorge Gonçalves
- Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
| | - Paulo Jorge Coelho
- School of Technology and Management, Polytechnic of Leiria, Leiria 2411-901, Portugal,Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), DEEC, Pólo II, Coimbra 3030-290, Portugal
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Toni Tripunovski
- Institute of Pathophysiology and Nuclear Medicine, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
| | - Nuno M. Garcia
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal,Corresponding author.
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9
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Prostota Y, Coelho PJ, Pina J, de Melo JS. Photochromic and photophysical properties of new benzo- and naphtho[1,3]oxazine switches. Photochem Photobiol Sci 2011; 10:1346-54. [PMID: 21706110 DOI: 10.1039/c1pp05067b] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Affiliation(s)
- Yaroslav Prostota
- Centro de Química - Vila Real, Universidade de Trás-os-Montes e Alto Douro, 5001-801, Vila Real, Portugal
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