{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T02:15:44Z","timestamp":1770776144445,"version":"3.50.0"},"reference-count":86,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T00:00:00Z","timestamp":1646870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004569","name":"Ministry of Science and Higher Education","doi-asserted-by":"publisher","award":["030\/RID\/2018\/19"],"award-info":[{"award-number":["030\/RID\/2018\/19"]}],"id":[{"id":"10.13039\/501100004569","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Osteoarthritis (OA) is a chronic, progressive disease which has over 300 million cases each year. Some of the main symptoms of OA are pain, restriction of joint motion and stiffness of the joint. Early diagnosis and treatment can prolong painless joint function. Vibroarthrography (VAG) is a cheap, reproducible, non-invasive and easy-to-use tool which can be implemented in the diagnostic route. The aim of this study was to establish diagnostic accuracy and to identify the most accurate signal processing method for the detection of OA in knee joints. In this study, we have enrolled a total of 67 patients, 34 in a study group and 33 in a control group. All patients in the study group were referred for surgical treatment due to intraarticular lesions, and the control group consisted of healthy individuals without knee symptoms. Cartilage status was assessed during surgery according to the International Cartilage Repair Society (ICRS) and vibroarthrography was performed one day prior to surgery in the study group. Vibroarthrography was performed in an open and closed kinematic chain for the involved knees in the study and control group. Signals were acquired by two sensors placed on the medial and lateral joint line. Using the neighbourhood component analysis (NCA) algorithm, the selection of optimal signal measures was performed. Classification using artificial neural networks was performed for three variants: I\u2014open kinetic chain, II\u2014closed kinetic chain, and III\u2014open and closed kinetic chain. Vibroarthrography showed high diagnostic accuracy in determining healthy cartilage from cartilage lesions, and the number of repetitions during examination can be reduced only to closed kinematic chain.<\/jats:p>","DOI":"10.3390\/s22062176","type":"journal-article","created":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T20:19:10Z","timestamp":1646943550000},"page":"2176","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Diagnostics of Articular Cartilage Damage Based on Generated Acoustic Signals Using ANN\u2014Part I: Femoral-Tibial Joint"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4063-8503","authenticated-orcid":false,"given":"Robert","family":"Karpi\u0144ski","sequence":"first","affiliation":[{"name":"Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7137-7145","authenticated-orcid":false,"given":"Przemys\u0142aw","family":"Krakowski","sequence":"additional","affiliation":[{"name":"Department of Trauma Surgery and Emergency Medicine, Medical University of Lublin, Staszica 11, 20-081 Lublin, Poland"},{"name":"Orthopaedic Department, \u0141\u0119czna Hospital, Krasnystawska 52 str, 21-010 \u0141\u0119czna, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4658-4569","authenticated-orcid":false,"given":"J\u00f3zef","family":"Jonak","sequence":"additional","affiliation":[{"name":"Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Machrowska","sequence":"additional","affiliation":[{"name":"Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcin","family":"Maciejewski","sequence":"additional","affiliation":[{"name":"Department of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Nogalski","sequence":"additional","affiliation":[{"name":"Department of Trauma Surgery and Emergency Medicine, Medical University of Lublin, Staszica 11, 20-081 Lublin, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1745","DOI":"10.1016\/S0140-6736(19)30417-9","article-title":"Osteoarthritis","volume":"393","author":"Hunter","year":"2019","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Krakowski, P., Nogalski, A., Jurkiewicz, A., Karpi\u0144ski, R., Maciejewski, R., and Jonak, J. (2019). Comparison of Diagnostic Accuracy of Physical Examination and MRI in the Most Common Knee Injuries. Appl. Sci., 9.","DOI":"10.3390\/app9194102"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.joca.2011.02.008","article-title":"Natural History of Cartilage Damage and Osteoarthritis Progression on Magnetic Resonance Imaging in a Population-Based Cohort with Knee Pain","volume":"19","author":"Cibere","year":"2011","journal-title":"Osteoarthr. Cartil."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"100587","DOI":"10.1016\/j.eclinm.2020.100587","article-title":"Global, Regional Prevalence, Incidence and Risk Factors of Knee Osteoarthritis in Population-Based Studies","volume":"29\u201330","author":"Cui","year":"2020","journal-title":"EClinicalMedicine"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1038\/nrrheum.2014.44","article-title":"The Individual and Socioeconomic Impact of Osteoarthritis","volume":"10","author":"Hunter","year":"2014","journal-title":"Nat. Rev. Rheumatol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1097\/00002281-200203000-00002","article-title":"An Update on the Relationship between Occupational Factors and Osteoarthritis of the Hip and Knee","volume":"14","author":"Schouten","year":"2002","journal-title":"Curr. Opin. Rheumatol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.1016\/j.joca.2015.03.020","article-title":"Socio-Economic Status and the Risk of Developing Hand, Hip or Knee Osteoarthritis: A Region-Wide Ecological Study","volume":"23","author":"Reyes","year":"2015","journal-title":"Osteoarthr. Cartil."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.joca.2014.11.011","article-title":"Increased Risk for Radiographic Osteoarthritis Features in Young Active Athletes: A Cross-Sectional Matched Case\u2013Control Study","volume":"23","author":"Roemer","year":"2015","journal-title":"Osteoarthr. Cartil."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2974","DOI":"10.1002\/art.30498","article-title":"Incidence of Physician-Diagnosed Osteoarthritis among Active Duty United States Military Service Members","volume":"63","author":"Cameron","year":"2011","journal-title":"Arthritis Rheumatol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.joca.2010.01.013","article-title":"OARSI Recommendations for the Management of Hip and Knee Osteoarthritis","volume":"18","author":"Zhang","year":"2010","journal-title":"Osteoarthr. Cartil."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.joca.2014.01.003","article-title":"OARSI Guidelines for the Non-Surgical Management of Knee Osteoarthritis","volume":"22","author":"McAlindon","year":"2014","journal-title":"Osteoarthr. Cartil."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Krakowski, P., Karpi\u0144ski, R., Maciejewski, R., Jonak, J., and Jurkiewicz, A. (2020). Short-Term Effects of Arthroscopic Microfracturation of Knee Chondral Defects in Osteoarthritis. Appl. Sci., 10.","DOI":"10.3390\/app10238312"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Romero, E.A., Gonz\u00e1lez-Zamorano, Y., Arribas-Romano, A., Mart\u00ednez-Pozas, O., Fern\u00e1ndez Espinar, E., Pedersini, P., Villafa\u00f1e, J.H., Alonso P\u00e9rez, J.L., and Fern\u00e1ndez-Carnero, J. (2021). Efficacy of Manual Therapy on Facilitatory Nociception and Endogenous Pain Modulation in Older Adults with Knee Osteoarthritis: A Case Series. Appl. Sci., 11.","DOI":"10.3390\/app11041895"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1302\/0301-620X.89B11.19783","article-title":"A 15-Year Follow-up Study of 4606 Primary Total Knee Replacements","volume":"89-B","author":"Roberts","year":"2007","journal-title":"J. Bone Jt. Surg. Br. Vol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3368","DOI":"10.1016\/j.arth.2017.05.052","article-title":"Total Knee Replacement in Young Patients: Survival and Causes of Revision in a Registry Population","volume":"32","author":"Castagnini","year":"2017","journal-title":"J. Arthroplast."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/S0140-6736(14)60802-3","article-title":"Osteoarthritis","volume":"386","author":"Palmer","year":"2015","journal-title":"Lancet"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"19558","DOI":"10.1038\/s41598-021-98945-2","article-title":"Acoustic Emissions and Kinematic Instability of the Osteoarthritic Knee Joint: Comparison with Radiographic Findings","volume":"11","author":"Nevalainen","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1016\/j.joca.2017.08.009","article-title":"Knee Osteoarthritis Phenotypes and Their Relevance for Outcomes: A Systematic Review","volume":"25","author":"Deveza","year":"2017","journal-title":"Osteoarthr. Cartil."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1136\/ard.16.4.494","article-title":"Radiological Assessment of Osteo-Arthrosis","volume":"16","author":"Kellgren","year":"1957","journal-title":"Ann. Rheum. Dis."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1884","DOI":"10.1136\/ard.2011.155119","article-title":"Defining Radiographic Incidence and Progression of Knee Osteoarthritis: Suggested Modifications of the Kellgren and Lawrence Scale","volume":"70","author":"Felson","year":"2011","journal-title":"Ann. Rheum. Dis."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1016\/j.joca.2014.06.020","article-title":"An Ultrasound Score for Knee Osteoarthritis: A Cross-Sectional Validation Study","volume":"22","author":"Riecke","year":"2014","journal-title":"Osteoarthr. Cartil."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.arthro.2006.11.015","article-title":"Knee Chondral Lesions: Incidence and Correlation Between Arthroscopic and Magnetic Resonance Findings","volume":"23","author":"Figueroa","year":"2007","journal-title":"Arthrosc. J. Arthrosc. Relat. Surg."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.2214\/ajr.172.4.10587150","article-title":"Accuracy of T2-Weighted Fast Spin-Echo MR Imaging with Fat Saturation in Detecting Cartilage Defects in the Knee: Comparison with Arthroscopy in 130 Patients","volume":"172","author":"Bredella","year":"1999","journal-title":"Am. J. Roentgenol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Krakowski, P., Karpi\u0144ski, R., Jojczuk, M., Nogalska, A., and Jonak, J. (2021). Knee MRI Underestimates the Grade of Cartilage Lesions. Appl. Sci., 11.","DOI":"10.3390\/app11041552"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s11547-015-0606-1","article-title":"Appropriateness of Knee MRI Prescriptions: Clinical, Economic and Technical Issues","volume":"121","author":"Solivetti","year":"2016","journal-title":"La Radiol. Med."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Schl\u00fcter, D.K., Spain, L., Quan, W., Southworth, H., Platt, N., Mercer, J., Shark, L.-K., Waterton, J.C., Bowes, M., and Diggle, P.J. (2019). Use of Acoustic Emission to Identify Novel Candidate Biomarkers for Knee Osteoarthritis (OA). PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0223711"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1136\/ard.2009.112599","article-title":"Analysis of High Frequency Acoustic Emission Signals as a New Approach for Assessing Knee Osteoarthritis","volume":"69","author":"Prior","year":"2010","journal-title":"Ann. Rheum. Dis."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"012009","DOI":"10.1088\/1742-6596\/2130\/1\/012009","article-title":"Estimation of Differences in Selected Indices of Vibroacoustic Signals between Healthy and Osteoarthritic Patellofemoral Joints as a Potential Non-Invasive Diagnostic Tool","volume":"2130","author":"Krakowski","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"012010","DOI":"10.1088\/1742-6596\/2130\/1\/012010","article-title":"Analysis of Differences in Vibroacoustic Signals between Healthy and Osteoarthritic Knees Using EMD Algorithm and Statistical Analysis","volume":"2130","author":"Krakowski","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1056\/NEJM190201161460304","article-title":"Auscultation of the Knee Joint","volume":"146","author":"Blodgett","year":"1902","journal-title":"Boston Med. Surg. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1615\/CritRevPhysRehabilMed.2016017185","article-title":"A Review of Engineering Aspects of Vibroarthography of the Knee Joint","volume":"28","author":"Andersen","year":"2016","journal-title":"Crit. Rev. Phys. Rehabil. Med."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Sarillee, M., Hariharan, M., Anas, M.N., Omar, M.I., Aishah, M.N., and Oung, Q.W. (2014, January 28\u201330). Assessment of Knee Joint Abnormality Using Acoustic Emission Sensors. Proceedings of the 2014 IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2014), Penang, Malaysia.","DOI":"10.1109\/ICCSCE.2014.7072748"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1016\/j.medengphy.2009.06.007","article-title":"Exploratory Study of a Non-Invasive Method Based on Acoustic Emission for Assessing the Dynamic Integrity of Knee Joints","volume":"31","author":"Mascaro","year":"2009","journal-title":"Med. Eng. Phys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.medengphy.2019.01.002","article-title":"Detection of Osteoarthritis Using Acoustic Emission Analysis","volume":"65","author":"Kiselev","year":"2019","journal-title":"Med. Eng. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"36","DOI":"10.35784\/acs-2019-03","article-title":"Application of Acoustic Signal Processing Methods in Detecting Differences between Open and Closed Kinematic Chain Movement for the Knee Joint","volume":"15","author":"Machrowska","year":"2019","journal-title":"Appl. Comput. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Shark, L.-K., Chen, H., Quan, W., and Goodacre, J. (2016, January 16\u201320). Acoustic Emission and Angular Movement Variations from Early Adulthood Healthy Knees to Late Adulthood Osteoarthritic Knees. Proceedings of the 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA.","DOI":"10.1109\/EMBC.2016.7591209"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"B\u0105czkowicz, D., and Majorczyk, E. (2014). Joint Motion Quality in Vibroacoustic Signal Analysis for Patients with Patellofemoral Joint Disorders. BMC Musculoskelet. Disord., 15.","DOI":"10.1186\/1471-2474-15-426"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"\u0141ysiak, A., Fro\u0144, A., B\u0105czkowicz, D., and Szmajda, M. (2020). Vibroarthrographic Signal Spectral Features in 5-Class Knee Joint Classification. Sensors, 20.","DOI":"10.3390\/s20175015"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.bspc.2009.03.008","article-title":"Screening of Knee-Joint Vibroarthrographic Signals Using Probability Density Functions Estimated with Parzen Windows","volume":"5","author":"Rangayyan","year":"2010","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Rangayyan, R.M., and Yunfeng, W. (2008, January 20\u201325). Modeling and Classification of Knee-Joint Vibroarthrographic Signals Using Probability Density Functions Estimated with Parzen Windows. Proceedings of the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada.","DOI":"10.1109\/IEMBS.2008.4649607"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"117","DOI":"10.3233\/BMR-2012-0319","article-title":"Vibroarthrography in Patients with Knee Arthropathy","volume":"25","author":"Tanaka","year":"2012","journal-title":"BMR"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1002\/bjs.18002911612","article-title":"The Semilunar Cartilages","volume":"29","author":"McMurray","year":"1942","journal-title":"Br. J. Surg."},{"key":"ref_43","first-page":"78","article-title":"The Diagnosis of Meniscus Injuries; Some New Clinical Methods","volume":"29","author":"Apley","year":"1947","journal-title":"J. Bone Jt. Surg. Am."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"955","DOI":"10.2106\/JBJS.D.02338","article-title":"Diagnostic Accuracy of a New Clinical Test (the Thessaly Test) for Early Detection of Meniscal Tears","volume":"87","author":"Karachalios","year":"2005","journal-title":"J. Bone Jt. Surg."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1177\/036354657600400206","article-title":"Clinical I Diagnosis of Anterior Cruciate Ligament Instability in the Athlete","volume":"4","author":"Torg","year":"1976","journal-title":"Am. J. Sports Med."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1177\/036354659202000122","article-title":"How New Is the Lachman Test?","volume":"20","author":"Paessler","year":"1992","journal-title":"Am. J. Sports Med."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1097\/00003086-198003000-00008","article-title":"The Lateral Pivot Shift: A Symptom and Sign of Anterior Cruciate Ligament Insufficiency","volume":"147","author":"Galway","year":"1980","journal-title":"Clin. Orthop. Relat. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2794","DOI":"10.1007\/s00167-014-3490-7","article-title":"The \u201cLever Sign\u201d: A New Clinical Test for the Diagnosis of Anterior Cruciate Ligament Rupture","volume":"24","author":"Lelli","year":"2016","journal-title":"Knee Surg. Sports Traumatol. Arthrosc."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1177\/03635465030310012601","article-title":"Reproducibility and Reliability of the Outerbridge Classification for Grading Chondral Lesions of the Knee Arthroscopically","volume":"31","author":"Cameron","year":"2003","journal-title":"Am. J. Sports Med."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"58","DOI":"10.2106\/00004623-200300002-00008","article-title":"Evaluation of Cartilage Injuries and Repair","volume":"85-A","author":"Brittberg","year":"2003","journal-title":"J. Bone Jt. Surg. Am."},{"key":"ref_51","unstructured":"(2022, February 16). Contact Microphone CM-01B, Technical Data Sheet. Available online: https:\/\/www.te.com\/commerce\/DocumentDelivery\/DDEController."},{"key":"ref_52","unstructured":"Bourns\u00ae Encoders (2022, February 16). Technical Data Sheet. Available online: https:\/\/www.bourns.com\/docs\/technical-documents\/technical-library\/sensors-controls\/publications\/Bourns_SC1180_Encoder_SF_Broch.pdf."},{"key":"ref_53","unstructured":"(2022, February 05). ADUM4160 Datasheet and Product Info|Analog Devices. Available online: https:\/\/www.analog.com\/en\/products\/adum4160.html."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.inffus.2021.07.001","article-title":"Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects","volume":"76","author":"Wang","year":"2021","journal-title":"Inf. Fusion"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Ranjbaran, M., Jalaleddini, K., Lopez, D.G., Kearney, R.E., and Galiana, H.L. (2013, January 3\u20137). Analysis and Modeling of Noise in Biomedical Systems. Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan.","DOI":"10.1109\/EMBC.2013.6609671"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"102337","DOI":"10.1016\/j.bspc.2020.102337","article-title":"EEG Signal Denoising Using Hybrid Approach of Variational Mode Decomposition and Wavelets for Depression","volume":"65","author":"Kaur","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Hung, C.-C., and Wang, S.-H. (2022). Introduction to Biomedical Signals and Their Applications. Ultra-Low-Voltage Frequency Synthesizer and Successive-Approximation Analog-to-Digital Converter for Biomedical Applications, Springer International Publishing. Analog Circuits and Signal Processing.","DOI":"10.1007\/978-3-030-88845-9"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Wu, Y. (2015). Knee Joint Vibroarthrographic Signal Processing and Analysis, Springer.","DOI":"10.1007\/978-3-662-44284-5"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1098\/rspa.1998.0193","article-title":"The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis","volume":"454","author":"Huang","year":"1998","journal-title":"Proc. R. Soc. London. Ser. A Math. Phys. Eng. Sci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1016\/j.ymssp.2010.03.003","article-title":"Performance Enhancement of Ensemble Empirical Mode Decomposition","volume":"24","author":"Zhang","year":"2010","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.sigpro.2013.09.013","article-title":"Partly Ensemble Empirical Mode Decomposition: An Improved Noise-Assisted Method for Eliminating Mode Mixing","volume":"96","author":"Zheng","year":"2014","journal-title":"Signal Process."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S1793536909000047","article-title":"Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method","volume":"1","author":"Wu","year":"2009","journal-title":"Adv. Adapt. Data Anal."},{"key":"ref_63","unstructured":"Stanik, Z., Instytut Technologii Eksploatacji, and Wydawnictwo (2013). Diagnozowanie Lozysk Tocznych Pojazd\u00f3w Samochodowych Metodami Wibroakustycznymi, Wydawnictwo Naukowe Instytutu Technologii Eksploatacji\u2014Panstwowego Instytutu Badawczego."},{"key":"ref_64","first-page":"7","article-title":"Diagnostyka Wibroakustyczna Maszyn-Historia, Stan Obecny, Perspektywy Rozwoju","volume":"3","author":"Cempel","year":"2005","journal-title":"Probl. Eksploat."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1016\/j.asoc.2015.02.015","article-title":"Early Fault Detection in Gearboxes Based on Support Vector Machines and Multilayer Perceptron with a Continuous Wavelet Transform","volume":"30","author":"Jonak","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_66","first-page":"175","article-title":"Application of Vibration Signal in the Diagnosis of IC Engine Valve Clearance","volume":"17","author":"Caban","year":"2015","journal-title":"J. Vibroeng."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"108070","DOI":"10.1016\/j.apacoust.2021.108070","article-title":"Fault Diagnosis of Angle Grinders and Electric Impact Drills Using Acoustic Signals","volume":"179","author":"Glowacz","year":"2021","journal-title":"Appl. Acoust."},{"key":"ref_68","first-page":"14","article-title":"Application of the Vibration Signal in the Diagnosis of the Valve Clearance of an Internal Combustion Engine","volume":"3","author":"Caban","year":"2014","journal-title":"Vibroeng. Procedia"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Ve\u010de\u0159, P., Kreidl, M., and \u0160m\u00edd, R. (2005). Condition Indicators for Gearbox Condition Monitoring Systems. Acta Polytech., 45.","DOI":"10.14311\/782"},{"key":"ref_70","first-page":"513","article-title":"Neighbourhood Components Analysis","volume":"17","author":"Goldberger","year":"2004","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"161","DOI":"10.4304\/jcp.7.1.161-168","article-title":"Neighborhood Component Feature Selection for High-Dimensional Data","volume":"7","author":"Yang","year":"2012","journal-title":"J. Comput."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.eswa.2018.06.031","article-title":"Classification of Focal and Non-Focal EEG Signals Using Neighborhood Component Analysis and Machine Learning Algorithms","volume":"113","author":"Raghu","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3138","DOI":"10.1016\/j.neucom.2009.03.017","article-title":"Neural Network Adaptation Process Effectiveness Dependent of Constant Training Data Availability","volume":"72","author":"Tadeusiewicz","year":"2009","journal-title":"Neurocomputing"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Rogala, M., Gajewski, J., and G\u00f3recki, M. (2021). Study on the Effect of Geometrical Parameters of a Hexagonal Trigger on Energy Absorber Performance Using ANN. Materials, 14.","DOI":"10.3390\/ma14205981"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"93","DOI":"10.12913\/22998624\/120989","article-title":"Neural Networks in Crashworthiness Analysis of Thin-Walled Profile with Foam Filling","volume":"14","author":"Rogala","year":"2020","journal-title":"Adv. Sci. Technol. Res. J."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Camacho Olmedo, M.T., Paegelow, M., Mas, J.-F., and Escobar, F. (2018). Multilayer Perceptron (MLP). Geomatic Approaches for Modeling Land Change Scenarios, Springer International Publishing.","DOI":"10.1007\/978-3-319-60801-3"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"012026","DOI":"10.1088\/1742-6596\/1736\/1\/012026","article-title":"Crushing Analysis of Energy Absorbing Materials Using Artificial Neural Networks","volume":"1736","author":"Rogala","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_78","first-page":"855","article-title":"Use of multilayer perception artificial neutral networks for the prediction of the probability of malignancy in adnexal tumors","volume":"74","author":"Czekierdowski","year":"2003","journal-title":"Ginekol. Pol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.ijgo.2005.01.034","article-title":"Artificial Neural Network Computer Prediction of Ovarian Malignancy in Women with Adnexal Masses","volume":"89","author":"Szpurek","year":"2005","journal-title":"Int. J. Gynecol. Obstet."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"012028","DOI":"10.1088\/1742-6596\/1736\/1\/012028","article-title":"Evaluation of the Diagnostic Accuracy of MRI in Detection of Knee Cartilage Lesions Using Receiver Operating Characteristic Curves","volume":"1736","author":"Krakowski","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"012027","DOI":"10.1088\/1742-6596\/1736\/1\/012027","article-title":"Evaluation of Diagnostic Accuracy of Physical Examination and MRI for Ligament and Meniscus Injuries","volume":"1736","author":"Krakowski","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"4065","DOI":"10.1016\/j.jbiomech.2016.10.038","article-title":"Acoustic Emission in Orthopaedics: A State of the Art Review","volume":"49","author":"Kapur","year":"2016","journal-title":"J. Biomech."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/s10439-019-02333-x","article-title":"Acoustic Emissions as a Non-Invasive Biomarker of the Structural Health of the Knee","volume":"48","author":"Whittingslow","year":"2020","journal-title":"Ann. Biomed. Eng."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1109\/10.844228","article-title":"Adaptive Time-Frequency Analysis of Knee Joint Vibroarthrographic Signals for Noninvasive Screening of Articular Cartilage Pathology","volume":"47","author":"Krishnan","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.bspc.2012.05.004","article-title":"Fractal Analysis of Knee-Joint Vibroarthrographic Signals via Power Spectral Analysis","volume":"8","author":"Rangayyan","year":"2013","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1109\/TBME.2005.869787","article-title":"Modified Local Discriminant Bases Algorithm and Its Application in Analysis of Human Knee Joint Vibration Signals","volume":"53","author":"Umapathy","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/6\/2176\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:34:34Z","timestamp":1760135674000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/6\/2176"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,10]]},"references-count":86,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["s22062176"],"URL":"https:\/\/doi.org\/10.3390\/s22062176","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,10]]}}}