{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:34:53Z","timestamp":1777656893393,"version":"3.51.4"},"reference-count":79,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,9]],"date-time":"2022-04-09T00:00:00Z","timestamp":1649462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Epilepsy is a chronic disease with a significant social impact, given that the patients and their families often live conditioned by the possibility of an epileptic seizure and its possible consequences, such as accidents, injuries, or even sudden unexplained death. In this context, ambulatory monitoring allows the collection of biomedical data about the patients\u2019 health, thus gaining more knowledge about the physiological state and daily activities of each patient in a more personalized manner. For this reason, this article proposes a novel monitoring system composed of different sensors capable of synchronously recording electrocardiogram (ECG), photoplethysmogram (PPG), and ear electroencephalogram (EEG) signals and storing them for further processing and analysis in a microSD card. This system can be used in a static and\/or ambulatory way, providing information about the health state through features extracted from the ear EEG signal and the calculation of the heart rate variability (HRV) and pulse travel time (PTT). The different applied processing techniques to improve the quality of these signals are described in this work. A novel algorithm used to compute HRV and PTT robustly and accurately in ambulatory settings is also described. The developed device has also been validated and compared with other commercial systems obtaining similar results. In this way, based on the quality of the obtained signals and the low variability of the computed parameters, even in ambulatory conditions, the developed device can potentially serve as a support tool for clinical decision-taking stages.<\/jats:p>","DOI":"10.3390\/s22082900","type":"journal-article","created":{"date-parts":[[2022,4,10]],"date-time":"2022-04-10T06:02:54Z","timestamp":1649570574000},"page":"2900","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Validation of Continuous Monitoring System for Epileptic Users in Outpatient Settings"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0531-575X","authenticated-orcid":false,"given":"David","family":"Zambrana-Vinaroz","sequence":"first","affiliation":[{"name":"Neuroengineering Biomedical Research Group, Miguel Hern\u00e1ndez University of Elche, 03202 Elche, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7902-1979","authenticated-orcid":false,"given":"Jose Maria","family":"Vicente-Samper","sequence":"additional","affiliation":[{"name":"Neuroengineering Biomedical Research Group, Miguel Hern\u00e1ndez University of Elche, 03202 Elche, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3890-6225","authenticated-orcid":false,"given":"Jose Maria","family":"Sabater-Navarro","sequence":"additional","affiliation":[{"name":"Neuroengineering Biomedical Research Group, Miguel Hern\u00e1ndez University of Elche, 03202 Elche, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1687","DOI":"10.1111\/epi.13201","article-title":"Epilepsy priorities in Europe: A report of the ILAE-IBE, Epilepsy Advocacy Europe Task Force","volume":"56","author":"Baulac","year":"2015","journal-title":"Epilepsia"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.1016\/j.jacc.2020.01.046","article-title":"Wearable Devices for Ambulatory Cardiac Monitoring: JACC State-of-the-Art Review","volume":"75","author":"Sana","year":"2020","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1161\/CIRCULATIONAHA.116.025282","article-title":"Telemedicine helps cardiologists extend their reach","volume":"134","author":"Kuehn","year":"2016","journal-title":"Circulation"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Li, H., and Boulanger, P. (2020). A Survey of Heart Anomaly Detection Using Ambulatory Electrocardiogram (ECG). Sensors, 20.","DOI":"10.3390\/s20051461"},{"key":"ref_5","unstructured":"Rubio, P., Hampel, K., and Giner, P. (2020). Grafoelementos, artifactos e informe del EEG. Gu\u00eda pr\u00e1ctica de Epilepsia de la Comunidad Valenciana, Sociedad Valenciana de Neurolog\u00eda. [2nd ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.1016\/j.jemermed.2012.02.024","article-title":"Electrocardiographic Electrode Misplacement, Misconnection, and Artifact","volume":"43","author":"Harrigan","year":"2012","journal-title":"J. Emerg. Med."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Serhani, M.A., El Kassabi, H.T., Ismail, H., and Nujum Navaz, A. (2020). ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges. Sensors, 20.","DOI":"10.3390\/s20061796"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kaur, J., and Kaur, A. (2015, January 19\u201320). A review on analysis of EEG signals. Proceedings of the International Conference on Advances in Computer Engineering and Applications, Ghaziabad, India.","DOI":"10.1109\/ICACEA.2015.7164844"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Karpiel, I., Kurasz, Z., Kurasz, R., and Duch, K. (2021). The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects. Sensors, 21.","DOI":"10.3390\/s21227711"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"McDermott, E.J., Raggam, P., Kirsch, S., Belardinelli, P., Ziemann, U., and Zrenner, C. (2022). Artifacts in EEG-Based BCI Therapies: Friend or Foe?. Sensors, 22.","DOI":"10.1101\/2021.10.27.466131"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"53","DOI":"10.2344\/0003-3006(2006)53[53:FOEI]2.0.CO;2","article-title":"Fundamentals of Electrocardiography Interpretation","volume":"53","author":"Becker","year":"2006","journal-title":"Anesthesia Prog."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"808451","DOI":"10.3389\/fphys.2021.808451","article-title":"Photoplethysmogram Analysis and Applications: An Integrative Review","volume":"12","author":"Park","year":"2022","journal-title":"Front. Physiol."},{"key":"ref_13","first-page":"195","article-title":"A review on wearable photoplethysmography sensors and their potential future applications in health care","volume":"4","author":"Castaneda","year":"2018","journal-title":"Int. J. Biosens. Bioelectron"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"\u0160umak, B., Brdnik, S., and Pu\u0161nik, M. (2020). Sensors and Artificial Intelligence Methods and Algorithms for Human\u2013Computer Intelligent Interaction: A Systematic Mapping Study. Sensors, 22.","DOI":"10.3390\/s22010020"},{"key":"ref_15","first-page":"8875426","article-title":"EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities. Comput","volume":"2020","author":"Suhaimi","year":"2020","journal-title":"Intell. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Brambilla, C., Pirovano, I., Mira, R.M., Rizzo, G., Scano, A., and Mastropietro, A. (2021). Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review. Sensors, 21.","DOI":"10.3390\/s21217014"},{"key":"ref_17","unstructured":"Cincotti, F., Pichiorri, F., Aric\u00f2, P., Aloise, F., Leotta, F., de Vico Fallani, F., Mill\u00e1n, J.D.R., Molinari, M., and Mattia, D. (September, January 28). EEG-based Brain-Computer Interface to support post-stroke motor rehabilitation of the upper limb. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CS, USA."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Nafea, M., Hisham, A.B., Abdul-Kadir, N.A., and Harun, F.K.C. (2018, January 24\u201326). Brainwave-Controlled System for Smart Home Applications. Proceedings of the 2nd International Conference on BioSignal Analysis, Processing and Systems (ICBAPS), Kuching, Malaysia.","DOI":"10.1109\/ICBAPS.2018.8527397"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.robot.2014.11.015","article-title":"Brainwave based user identification system: A pilot study in robotics environment","volume":"65","author":"Kumari","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Katona, J., Ujbanyi, T., Sziladi, G., and Kovari, A. (2016, January 16\u201318). Speed control of Festo Robotino mobile robot using NeuroSky MindWave EEG headset based brain-computer interface. Proceedings of the 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Wroclaw, Poland.","DOI":"10.1109\/CogInfoCom.2016.7804557"},{"key":"ref_21","first-page":"225","article-title":"The Evaluation of BCI and PEBL-based Attention Tests","volume":"15","author":"Katona","year":"2018","journal-title":"Acta Polytech. Hung."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Katona, J., Ujbanyi, T., Sziladi, G., and Kovari, A. (2017, January 11\u201314). Examine the effect of different web-based media on human brain waves. Proceedings of the 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Debrecen, Hungary.","DOI":"10.1109\/CogInfoCom.2017.8268280"},{"key":"ref_23","unstructured":"Kasprowski, P., Harezlak, K., and Niezabitowski, M. (June, January 29). Eye movement tracking as a new promising modality for human computer interaction. Proceedings of the 17th International Carpathian Control Conference (ICCC), High Tatras, Slovakia."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"193","DOI":"10.12700\/APH.18.1.2021.1.12","article-title":"Analyse the Readability of LINQ Code using an Eye-Tracking-based Evaluation","volume":"18","author":"Katona","year":"2021","journal-title":"Acta Polytech. Hung."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Katona, J. (2022). Measuring Cognition Load Using Eye-Tracking Parameters Based on Algorithm Description Tools. Sensors, 22.","DOI":"10.3390\/s22030912"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"ii2","DOI":"10.1136\/jnnp.2005.069245","article-title":"EEG in the diagnosis, classification, and management of patients with epilepsy","volume":"76","author":"Smith","year":"2005","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"95","DOI":"10.3389\/fninf.2018.00095","article-title":"Epileptic Seizure Detection Based on EEG Signals and CNN","volume":"12","author":"Zhou","year":"2018","journal-title":"Front. Neuroinform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1007\/s10548-020-00793-2","article-title":"The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling","volume":"33","author":"Meiser","year":"2020","journal-title":"Brain Topogr."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Athavipach, C., Pan-Ngum, S., and Israsena, P. (2019). A Wearable In-Ear EEG Device for Emotion Monitoring. Sensors, 19.","DOI":"10.3390\/s19184014"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3389\/fnhum.2017.00163","article-title":"Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG","volume":"11","author":"Bleichner","year":"2017","journal-title":"Front. Hum. Neurosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2454","DOI":"10.1016\/j.clinph.2017.09.115","article-title":"Ear-EEG detects ictal and interictal abnormalities in focal and gener-alized epilepsy\u2014A comparison with scalp EEG monitoring","volume":"128","author":"Zibrandtsen","year":"2017","journal-title":"Clin. Neurophysiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"204","DOI":"10.4330\/wjc.v7.i4.204","article-title":"Autonomic and endocrine control of cardiovascular function","volume":"7","author":"Gordan","year":"2015","journal-title":"World J. Cardiol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.yebeh.2010.06.011","article-title":"RMSSD, a measure of vagus-mediated heart rate variability, is associated with risk factors for SUDEP: The SUDEP-7 Inventory","volume":"19","author":"DeGiorgio","year":"2010","journal-title":"Epilepsy Behav."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"193","DOI":"10.15420\/aer.2018.27.2","article-title":"Heart Rate Variability: An Old Metric with New Meaning in the Era of using mHealth Technologies for Health and Exercise Training Guidance. Part One: Physiology and Methods","volume":"7","author":"Singh","year":"2018","journal-title":"Arrhythm. Electrophysiol. Rev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3","DOI":"10.4149\/BLL_2017_001","article-title":"Heart rate variability as a biomarker for epilepsy seizure prediction","volume":"118","author":"Moridani","year":"2017","journal-title":"Bratisl. Med. J."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1372","DOI":"10.1111\/epi.14438","article-title":"Heart rate variability in epilepsy: A potential biomarker of sudden unexpected death in epilepsy risk","volume":"59","author":"Myers","year":"2018","journal-title":"Epilepsia"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"16373","DOI":"10.1038\/s41598-020-73143-8","article-title":"Conventional pulse transit times as markers of blood pressure changes in humans","volume":"10","author":"Block","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1136\/thx.54.5.452","article-title":"Pulse transit time: An appraisal of potential clinical applications","volume":"54","author":"Smith","year":"1999","journal-title":"Thorax"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"501","DOI":"10.3389\/fneur.2019.00501","article-title":"Blood Pressure in Seizures and Epilepsy","volume":"10","author":"Nass","year":"2019","journal-title":"Front. Neurol."},{"key":"ref_40","unstructured":"(2022, March 30). Post-ictal Physiology: Adding Blood Pressure to the Equation. Available online: https:\/\/www.epilepsy.com\/article\/2016\/12\/post-ictal-physiology-adding-blood-pressure-equation."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Singh, A., Hussain, A.A., Lal, S., and Guesgen, H.W. (2021). A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface. Sensors, 21.","DOI":"10.3390\/s21062173"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.measurement.2018.01.024","article-title":"Complex networks approach for depth of anesthesia assessment","volume":"119","author":"Diykh","year":"2018","journal-title":"Measurement"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Covantes-Osuna, C., L\u00f3pez, J.B., Paredes, O., V\u00e9lez-P\u00e9rez, H., and Romo-V\u00e1zquez, R. (2021). Multilayer Network Approach in EEG Motor Imagery with an Adaptive Threshold. Sensors, 21.","DOI":"10.3390\/s21248305"},{"key":"ref_44","unstructured":"(2022, March 30). Apple, Why Apple Watch. Available online: https:\/\/www.apple.com\/watch\/why-apple-watch\/."},{"key":"ref_45","unstructured":"(2022, March 30). iRHYTHM Technologies, Uninterrumpled Ambulatory Cardiac Monitoring. Available online: https:\/\/www.irhythmtech.com\/."},{"key":"ref_46","unstructured":"Integrated, M. (2022, March 30). MAX-ECGMONITOR Wearable ECG and Heart Monitor Evaluation and Development Platform. Available online: https:\/\/www.maximintegrated.com\/en\/products\/interface\/sensor-interface\/MAX-ECGMONITOR.html."},{"key":"ref_47","unstructured":"Medtronic (2022, March 30). Zephyr Performance Systems. Available online: https:\/\/www.zephyranywhere.com."},{"key":"ref_48","unstructured":"(2022, March 30). Fitbit, Advanced Fitness + Health Tracker. Available online: https:\/\/www.fitbit.com\/global\/us\/products\/trackers\/charge5."},{"key":"ref_49","unstructured":"(2022, March 30). Cosinuss, \u00abcosinuss One\u2014Performance Monitoring. Available online: https:\/\/www.cosinuss.com\/en\/products\/data-acquisition\/in-ear-sensors\/one\/."},{"key":"ref_50","unstructured":"Medtronic, Nellcor\u2122 (2022, March 30). Portable SpO\u2082 Patient Monitoring System. Available online: https:\/\/www.medtronic.com\/covidien\/en-us\/products\/pulse-oximetry\/nellcor-portable-spo2-patient-monitoring-system.html."},{"key":"ref_51","unstructured":"(2022, March 30). Oura Health, Accurate Health Information Accesible to Everyone. Available online: https:\/\/ouraring.com\/."},{"key":"ref_52","unstructured":"Emotiv (2022, March 30). Epoc Flex\u201432-Channel Wireless EEG Device. Available online: https:\/\/www.emotiv.com\/epoc-flex\/."},{"key":"ref_53","unstructured":"NeuroSky (2022, March 30). MindWave. Available online: https:\/\/store.neurosky.com\/pages\/mindwave."},{"key":"ref_54","unstructured":"Tmsi (2022, March 30). EEG Headcaps. Available online: https:\/\/www.tmsi.com\/products\/eeg-headcaps\/."},{"key":"ref_55","unstructured":"MJN (2022, March 30). Seras. Available online: https:\/\/mjn.cat\/."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Masihi, S., Panahi, M., Maddipatla, D., Hanson, A.J., Fenech, S., Bonek, L., Sapoznik, N., Fleming, P.D., Bazuin, B.J., and Atashbar, M.Z. (2021). Development of a Flexible Wireless ECG Monitoring Device with Dry Fabric Electrodes for Wearable Applications. IEEE Sensors J.","DOI":"10.1109\/JSEN.2021.3116215"},{"key":"ref_57","unstructured":"Kim, B.H., Jo, S., and Choi, S. (2021). ALIS: Learning Affective Causality Behind Daily Activities from a Wearable Life-Log System. IEEE Trans. Cybern., 1\u201313."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Juez, J., Henao, D., Segura, F., Gomez, R., Le Van Quyen, M., and Valderrama, M. (2021, January 13\u201315). Development of a wearable system with In-Ear EEG electrodes for the monitoring of brain activities: An application to epilepsy. Proceedings of the IEEE 2nd International Congress of Biomedical Engineering and Bioengineering (CI-IB&BI), Bogota, Colombia.","DOI":"10.1109\/CI-IBBI54220.2021.9626123"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Yamakawa, T., Miyajima, M., Fujiwara, K., Kano, M., Suzuki, Y., Watanabe, Y., Watanabe, S., Hoshida, T., Inaji, M., and Maehara, T. (2020). Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability. Sensors, 20.","DOI":"10.3390\/s20143987"},{"key":"ref_60","unstructured":"(2022, March 30). OpenBCI. Available online: www.openbci.com."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"43","DOI":"10.9781\/ijimai.2019.06.004","article-title":"A User-centered Smartphone Application for Wireless EEG and its Role in Epilepsy","volume":"5","author":"Ahufinger","year":"2019","journal-title":"IJIMAI"},{"key":"ref_62","first-page":"0345","article-title":"A feasibility study of a complete low-cost consumer-grade brain-computer interface system","volume":"6","author":"Peterson","year":"2020","journal-title":"Heliyon"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Rashid, U., Niazi, I.K., Signal, N., and Taylor, D. (2018). An EEG Experimental Study Evaluating the Performance of Texas Instruments ADS1299. Sensors, 18.","DOI":"10.3390\/s18113721"},{"key":"ref_64","unstructured":"(2022, March 30). MAX86150 Datasheet. Available online: https:\/\/datasheets.maximintegrated.com\/en\/ds\/MAX86150.pdf."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1109\/TBME.1973.324231","article-title":"A Spectral Analysis of the Normal Resting Electrocardiogram","volume":"20","author":"Golden","year":"1973","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_66","first-page":"400","article-title":"Bioharness(\u2122) multivariable monitoring device: Part I: Validity","volume":"11","author":"Johnstone","year":"2012","journal-title":"J. Sports Sci. Med."},{"key":"ref_67","first-page":"409","article-title":"Bioharness(\u2122) Multivariable Monitoring Device: Part. II: Reliability","volume":"11","author":"Johnstone","year":"2012","journal-title":"J. Sports Sci. Med."},{"key":"ref_68","unstructured":"(2022, March 30). e-Health Sensor Platform V1.0 for Arduino and Raspberry Pi [Biometric\/Medical Applications]. E-Health\u2014Sensors\u2014Shop. Available online: cooking-hacks.com."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Biswas, B.C., and Bhalerao, S.V. (2015, January 2\u20134). A real time based wireless wearable EEG device for epilepsy seizure control. Proceedings of the International Conference on Communications and Signal Processing (ICCSP), Chengdu, China.","DOI":"10.1109\/ICCSP.2015.7322758"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"425","DOI":"10.3389\/fnhum.2019.00425","article-title":"Possible Effect of Binaural Beat Combined with Autonomous Sensory Meridian Response for Inducing Sleep","volume":"13","author":"Lee","year":"2019","journal-title":"Front. Hum. Neurosci."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Zambrana-Vinaroz, D., Vicente-Samper, J.M., Juan, C.G., Esteve-Sala, V., and Sabater-Navarro, J.M. (2019). Non-Invasive Device for Blood Pressure Wave Acquisition by Means of Mechanical Transducer. Sensors, 19.","DOI":"10.3390\/s19194311"},{"key":"ref_72","unstructured":"(2022, March 30). Wavelet Toolbox (Matlab). Available online: https:\/\/es.mathworks.com\/products\/wavelet.html."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.jneumeth.2006.05.033","article-title":"Recovering EEG brain signals: Artifact suppression with wavelet enhanced independent component analysis","volume":"158","author":"Castellanos","year":"2006","journal-title":"J. Neurosci. Methods"},{"key":"ref_74","unstructured":"(2022, March 30). Autoregressive Power Spectral Density Estimate\u2014Burg\u2019s Method. Available online: https:\/\/es.mathworks.com\/help\/signal\/ref\/pburg.html."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"2828","DOI":"10.1109\/TBME.2012.2211356","article-title":"A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats","volume":"59","author":"Citi","year":"2012","journal-title":"IEEE Trans Biomed. Eng."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1080\/03091902.2019.1640306","article-title":"A robust algorithm for heart rate variability time series artefact correction using novel beat classification","volume":"43","author":"Lipponen","year":"2019","journal-title":"J. Med. Eng. Technol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1023\/A:1007414906294","article-title":"Detection of dicrotic notch in arterial pressure signals","volume":"13","author":"Hoeksel","year":"1997","journal-title":"J. Clin. Monit."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Jachymek, M., Jachymek, M.T., Kiedrowicz, R.M., Ka\u017amierczak, J., P\u0142o\u0144ska-Go\u015bciniak, E., and Peregud-Pogorzelska, M. (2022). Wristbands in Home-Based Rehabilitation\u2014Validation of Heart Rate Measurement. Sensors, 22.","DOI":"10.3390\/s22010060"},{"key":"ref_79","first-page":"57","article-title":"La Hiperventilaci\u00f3n y el Trastorno de Angustia a la Luz de un Marco Cognitivo","volume":"20","author":"Wood","year":"2021","journal-title":"Cl\u00edn. Salud"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2900\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:51:08Z","timestamp":1760136668000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/8\/2900"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,9]]},"references-count":79,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22082900"],"URL":"https:\/\/doi.org\/10.3390\/s22082900","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,9]]}}}