{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:51:19Z","timestamp":1780354279644,"version":"3.54.1"},"reference-count":59,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2019,8,8]],"date-time":"2019-08-08T00:00:00Z","timestamp":1565222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["CRDPJ 533817 - 18"],"award-info":[{"award-number":["CRDPJ 533817 - 18"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG\u2013GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36\u2013140 bpm. The correlation between the two measurements had r2 coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.<\/jats:p>","DOI":"10.3390\/s19163472","type":"journal-article","created":{"date-parts":[[2019,8,8]],"date-time":"2019-08-08T11:05:32Z","timestamp":1565262332000},"page":"3472","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":76,"title":["Real-Time Cardiac Beat Detection and Heart Rate Monitoring from Combined Seismocardiography and Gyrocardiography"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7922-7475","authenticated-orcid":false,"given":"Yannick","family":"D\u2019Mello","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Skoric","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9144-5739","authenticated-orcid":false,"given":"Shicheng","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip J. R.","family":"Roche","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"Lortie","sequence":"additional","affiliation":[{"name":"MacDonald, Dettwiler and Associates Corporation, Ottawa, ON K2K 1Y5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephane","family":"Gagnon","sequence":"additional","affiliation":[{"name":"MacDonald, Dettwiler and Associates Corporation, Ottawa, ON K2K 1Y5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David V.","family":"Plant","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e67","DOI":"10.1161\/CIR.0000000000000558","article-title":"Heart disease and stroke statistics\u20142018 update: A report from the American Heart Association","volume":"137","author":"Benjamin","year":"2018","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1093\/eurheartj\/ehq030","article-title":"Novel therapeutic concepts the epidemic of cardiovascular disease in the developing world: Global implications","volume":"31","author":"Gersh","year":"2010","journal-title":"Eur. Heart J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compbiomed.2014.08.014","article-title":"Heart monitoring systems\u2014A review","volume":"54","author":"Jain","year":"2014","journal-title":"Comput. Biol. Med."},{"key":"ref_4","unstructured":"Bloom, D.E., Cafiero, E., Jan\u00e9-Llopis, E., Abrahams-Gessel, S., Bloom, L.R., Fathima, S., Feigl, A.B., Gaziano, T., Mowafi, M., and Pandya, A. (2019, August 06). The Global Economic Burden of Noncommunicable Diseases. Available online: http:\/\/www3.weforum.org\/docs\/WEF_Harvard_HE_GlobalEconomicBurdenNonCommunicableDiseases_2011.pdf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/0300-9572(94)90096-5","article-title":"Developing strategies to prevent inhospital cardiac arrest: Analyzing responses of physicians and nurses in the hours before the event","volume":"28","author":"Franklin","year":"1994","journal-title":"Resuscitation"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1037\/0033-2909.96.3.435","article-title":"Acute psychophysiologic reactivity and risk of cardiovascular disease: A review and methodologic critique","volume":"96","author":"Krantz","year":"1984","journal-title":"Psychol. Bull."},{"key":"ref_7","unstructured":"MacIntosh, E., Rajakulendran, N., Khayat, Z., and Wise, A. (2014). Transforming Health: Shifting from Reactive to Proactive and Predictive Care, MaRS Discovery District."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1197\/jamia.M2270","article-title":"Systematic review of home telemonitoring for chronic diseases: The evidence base","volume":"14","author":"Jaana","year":"2007","journal-title":"J. Am. Med Inform. Assoc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.knosys.2017.06.003","article-title":"Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network","volume":"132","author":"Acharya","year":"2017","journal-title":"Knowl. Based Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2236","DOI":"10.1016\/S0140-6736(18)30994-2","article-title":"Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016","volume":"391","author":"Fullman","year":"2018","journal-title":"Lancet"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1093\/qjmed\/94.10.521","article-title":"Validation of a modified Early Warning Score in medical admissions","volume":"94","author":"Subbe","year":"2001","journal-title":"QJM"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Weng, S.F., Reps, J., Kai, J., Garibaldi, J.M., and Qureshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data?. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0174944"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"H151","DOI":"10.1152\/ajpheart.1985.248.1.H151","article-title":"Assessment of autonomic function in humans by heart rate spectral analysis","volume":"248","author":"Pomeranz","year":"1985","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1007\/s11517-005-0008-y","article-title":"A computational system to optimise noise rejection in photoplethysmography signals during motion or poor perfusion states","volume":"44","author":"Foo","year":"2006","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1007\/BF02456747","article-title":"Electrode studies for the long-term ambulatory ECG","volume":"23","author":"Thakor","year":"1985","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/51.32403","article-title":"Fundamentals of impedance cardiography","volume":"8","author":"Patterson","year":"1989","journal-title":"IEEE Eng. Med. Biol. Mag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1109\/TITB.2012.2198071","article-title":"A system for seismocardiography-based identification of quiescent heart phases: Implications for cardiac imaging","volume":"16","author":"Wick","year":"2012","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1109\/JBHI.2014.2361732","article-title":"Ballistocardiography and seismocardiography: A review of recent advances","volume":"19","author":"Inan","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"McGee, S. (2012). Evidence-Based Physical Diagnosis E-Book, Elsevier Health Sciences.","DOI":"10.1016\/B978-1-4377-2207-9.00001-X"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Golemati, S., and Nikita, K.S. (2019). Cardiac Mechanical Signals. Cardiovascular Computing\u2014Methodologies and Clinical Applications, Springer.","DOI":"10.1007\/978-981-10-5092-3"},{"key":"ref_21","first-page":"55","article-title":"Seismocardiography\u2014A new method in the study of functional conditions of the heart","volume":"33","author":"Bozhenko","year":"1961","journal-title":"Ter. Arkhiv"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Tadi, M.J., Lehtonen, E., Pank\u00e4\u00e4l\u00e4, M., Saraste, A., Vasankari, T., Ter\u00e1s, M., and Koivisto, T. (2016, January 17\u201320). Gyrocardiography: A new non-invasive approach in the study of mechanical motions of the heart. Concept, method and initial observations. Proceedings of the 2016 IEEE 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA.","DOI":"10.1109\/EMBC.2016.7591126"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1378\/chest.100.4.991","article-title":"Seismocardiography for monitoring changes in left ventricular function during ischemia","volume":"100","author":"Salerno","year":"1991","journal-title":"Chest"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6823","DOI":"10.1038\/s41598-017-07248-y","article-title":"Gyrocardiography: A new non-invasive monitoring method for the assessment of cardiac mechanics and the estimation of hemodynamic variables","volume":"7","author":"Tadi","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1159\/000470156","article-title":"Relationship between seismocardiogram and echocardiogram for events in the cardiac cycle","volume":"8","author":"Crow","year":"1994","journal-title":"Am. J. Noninvasive Cardiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"64","DOI":"10.3390\/vibration2010005","article-title":"Recent Advances in Seismocardiography","volume":"2","author":"Taebi","year":"2019","journal-title":"Vibration"},{"key":"ref_27","unstructured":"Migeotte, P.-F., Mucci, V., Deli\u00e8re, Q., Lejeune, L., and van de Borne, P. (April, January 31). Multi-dimensional kineticardiography a new approach for wearable cardiac monitoring through body acceleration recordings. Proceedings of the XIV Mediterranean Conference on Medical and Biological Engineering and Computing, Paphos, Cyprus."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1109\/JBHI.2017.2764798","article-title":"Combined Seismo-and Gyro-Cardiography: A More Comprehensive Evaluation of Heart-Induced Chest Vibrations","volume":"22","author":"Yang","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1109\/TBME.2018.2856700","article-title":"An Independent Component Analysis Approach to Motion Noise Cancellation of Cardio-Mechanical Signals","volume":"66","author":"Yang","year":"2018","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lee, H., Lee, H., and Whang, M. (2018). An Enhanced Method to Estimate Heart Rate from Seismocardiography via Ensemble Averaging of Body Movements at Six Degrees of Freedom. Sensors, 18.","DOI":"10.3390\/s18010238"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lee, H., and Whang, M. (2018). Heart Rate Estimated from Body Movements at Six Degrees of Freedom by Convolutional Neural Networks. Sensors, 18.","DOI":"10.3390\/s18051392"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1109\/JSEN.2017.2663420","article-title":"Utilizing gyroscopes towards the automatic annotation of seismocardiograms","volume":"17","author":"Yang","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5127","DOI":"10.1109\/JSEN.2019.2903449","article-title":"Autocorrelated Differential Algorithm for Real-time Seismocardiography Analysis","volume":"19","author":"Skoric","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Landreani, F., Morri, M., Martin-Yebra, A., Casellato, C., Pavan, E., Frigo, C., and Caiani, E.G. (2017, January 22\u201324). Ultra-short-term heart rate variability analysis on accelerometric signals from mobile phone. Proceedings of the 6th IEEE International Conference on E-Health and Bioengineering (EHB), Sinaia, Romania.","DOI":"10.1109\/EHB.2017.7995406"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"9344","DOI":"10.1038\/s41598-018-27683-9","article-title":"Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography","volume":"8","author":"Iftikhar","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/JBHI.2017.2688473","article-title":"Atrial fibrillation detection via accelerometer and gyroscope of a smartphone","volume":"22","author":"Lahdenoja","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1885","DOI":"10.1088\/0967-3334\/37\/11\/1885","article-title":"A real-time approach for heart rate monitoring using a Hilbert transform in seismocardiograms","volume":"37","author":"Tadi","year":"2016","journal-title":"Physiol. Meas."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2361","DOI":"10.1109\/TBME.2017.2648741","article-title":"A hidden markov model for seismocardiography","volume":"64","author":"Skog","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1701","DOI":"10.1109\/TBME.2016.2616382","article-title":"Automatic and Robust Delineation of the Fiducial Points of the Seismocardiogram Signal for Noninvasive Estimation of Cardiac Time Intervals","volume":"64","author":"Tavakolian","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_40","first-page":"1031","article-title":"Automatic Detection of Aortic Valve Opening using Seismocardiography in Healthy Individuals","volume":"23","author":"Choudhary","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.1088\/0967-3334\/37\/9\/1588","article-title":"Accurate and consistent automatic seismocardiogram annotation without concurrent ECG","volume":"37","author":"Laurin","year":"2016","journal-title":"Physiol. Meas."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Malcangi, M., Quan, H., Vaini, E., Lombardi, P., and Di Rienzo, M. (2017, January 25\u201327). Applying the EFuNN Evolving Paradigm to the Recognition of Artefactual Beats in Continuous Seismocardiogram Recordings. Proceedings of the International Conference on Engineering Applications of Neural Networks, Athens, Greece.","DOI":"10.1007\/978-3-319-65172-9_22"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1428","DOI":"10.1109\/JBHI.2014.2360156","article-title":"Automatic annotation of seismocardiogram with high-frequency precordial accelerations","volume":"19","author":"Tavakolian","year":"2015","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1109\/TBCAS.2015.2405480","article-title":"A wearable patch to enable long-term monitoring of environmental, activity and hemodynamics variables","volume":"10","author":"Etemadi","year":"2016","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15634","DOI":"10.1038\/s41598-017-15829-0","article-title":"An algorithm for the beat-to-beat assessment of cardiac mechanics during sleep on Earth and in microgravity from the seismocardiogram","volume":"7","author":"Vaini","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Sahoo, P.K., Thakkar, H.K., and Lee, M.-Y. (2017). A cardiac early warning system with multi channel SCG and ECG monitoring for mobile health. Sensors, 17.","DOI":"10.3390\/s17040711"},{"key":"ref_47","unstructured":"Tadi, M.J., Koivisto, T., P\u00e4nk\u00e4\u00e4l\u00e4, M., Paasio, A., Knuutila, T., Ter\u00e4s, M., and H\u00e4nninen, P. (2014, January 24\u201326). A new algorithm for segmentation of cardiac quiescent phases and cardiac time intervals using seismocardiography. Proceedings of the Sixth International Conference on Graphic and Image Processing (ICGIP 2014), Beijing, China."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1109\/TBME.2016.2600945","article-title":"Quantifying and Reducing Motion Artifacts in Wearable Seismocardiogram Measurements During Walking to Assess Left Ventricular Health","volume":"64","author":"Javaid","year":"2017","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_49","unstructured":"(2019, June 25). MPU-9250|TDK. Available online: https:\/\/www.invensense.com\/products\/motion-tracking\/9-axis\/mpu-9250\/."},{"key":"ref_50","unstructured":"(2019, June 25). SparkFun Single Lead Heart Rate Monitor-AD8232. Available online: https:\/\/www.sparkfun.com\/products\/12650."},{"key":"ref_51","unstructured":"(2019, June 25). Arduino Leonardo. Available online: https:\/\/www.arduino.cc\/en\/Main\/Arduino_BoardLeonardo."},{"key":"ref_52","unstructured":"Zanetti, J.M., and Salerno, D.M. (1991, January 12\u201314). Seismocardiography: A technique for recording precordial acceleration. Proceedings of the Computer-Based Medical Systems-Proceedings of the Fourth Annual IEEE Symposium, Baltimore, MD, USA."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/0002-8703(46)90791-0","article-title":"On Einthoven\u2019s triangle, the theory of unipolar electrocardiographic leads, and the interpretation of the precordial electrocardiogram","volume":"32","author":"Wilson","year":"1946","journal-title":"Am Heart J."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Ozemek, C., Cochran, H.L., Strath, S.J., Byun, W., and Kaminsky, L.A. (2013). Estimating relative intensity using individualized accelerometer cutpoints: The importance of fitness level. BMC Med. Res. Methodol., 13.","DOI":"10.1186\/1471-2288-13-53"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Tadi, M.J., Lehtonen, E., Koivisto, T., P\u00e4nk\u00e4\u00e4l\u00e4, M., Paasio, A., and Ter\u00e4s, M. (2015, January 7\u20139). Seismocardiography: Toward heart rate variability (HRV) estimation. Proceedings of the 2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Torino, Italy.","DOI":"10.1109\/MeMeA.2015.7145210"},{"key":"ref_56","unstructured":"AAMI (2002). Cardiac monitors, heart rate meters, and alarms. American National Standard (ANSI\/AAMI EC13: 2002), AAMI."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/TBME.1985.325532","article-title":"A real-time QRS detection algorithm","volume":"32","author":"Pan","year":"1985","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"3805","DOI":"10.1109\/JSEN.2017.2701349","article-title":"Automatic detection of seismocardiogram sensor misplacement for robust pre-ejection period estimation in unsupervised settings","volume":"17","author":"Ashouri","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1109\/JBHI.2016.2620496","article-title":"Identification of location specific feature points in a cardiac cycle using a novel seismocardiogram spectrum system","volume":"22","author":"Lin","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/16\/3472\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:09:44Z","timestamp":1760188184000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/16\/3472"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,8]]},"references-count":59,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["s19163472"],"URL":"https:\/\/doi.org\/10.3390\/s19163472","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,8]]}}}