APPLICATION OF ACOUSTIC SIGNAL PROCESSING METHODS IN DETECTING DIFFERENCES BETWEEN OPEN AND CLOSED KINEMATIC CHAIN MOVEMENT FOR THE KNEE JOINT
Robert KARPIŃSKI
r.karpinski@pollub.pl* Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin (Poland)
Anna MACHROWSKA
Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin (Poland)
Marcin MACIEJEWSKI
Institute of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin (Poland)
Abstract
The paper presents results of preliminary research of analysis of signals recorded for open and closed kinematic chain in one volunteer with chondromalacia in both knees. The preliminary research was conducted in order to establish the accuracy of the proposed method and will be used for formulating further research areas. The aim of the paper is to show how FFT, recurrence plots and recurrence quantification analysis (RQA) can help in bioacoustic signals analysis.
Keywords:
knee joint, kinetic chain, signals, articular cartilageReferences
Adouni, M., & Shirazi-Adl, A. (2009). Knee joint biomechanics in closed-kinetic-chain exercises. Computer Methods in Biomechanics and Biomedical Engineering, 12(6), 661–670. https://doi.org/10.1080/10255840902828375
DOI: https://doi.org/10.1080/10255840902828375
Google Scholar
Bączkowicz, D., Kręcisz, K., & Borysiuk, Z. (2019). Analysis of patellofemoral arthrokinematic motion quality in open and closed kinetic chains using vibroarthrography. BMC Musculoskeletal Disorders, 20(1). https://doi.org/10.1186/s12891-019-2429-z
DOI: https://doi.org/10.1186/s12891-019-2429-z
Google Scholar
Bączkowicz, D., & Majorczyk, E. (2014). Joint motion quality in vibroacoustic signal analysis for patients with patellofemoral joint disorders. BMC Musculoskeletal Disorders, 15, 426. https://doi.org/10.1186/1471-2474-15-426
DOI: https://doi.org/10.1186/1471-2474-15-426
Google Scholar
Brinckmann, P., Hoefert, H., & Jongen, H. T. (1981). Sex differences in the skeletal geometry of the human pelvis and hip joint. Journal of Biomechanics, 14(6), 427–430. https://doi.org/10.1016/0021-9290(81)90060-9
DOI: https://doi.org/10.1016/0021-9290(81)90060-9
Google Scholar
Chen, Y., & Yang, H. (2012). Multiscale recurrence analysis of long-term nonlinear and nonstationary time series. Chaos, Solitons & Fractals, 45(7), 978–987. https://doi.org/10.1016/j.chaos.2012.03.013
DOI: https://doi.org/10.1016/j.chaos.2012.03.013
Google Scholar
Choi, D., Ahn, S., Ryu, J., Nagao, M., & Kim, Y. (2018). Knee Acoustic Emission Characteristics of the Healthy and the Patients with Osteoarthritis Using Piezoelectric Sensor. Sensors and Materials, 30(8), 1629. https://doi.org/10.18494/SAM.2018.1877
DOI: https://doi.org/10.18494/SAM.2018.1877
Google Scholar
Gilsanz, V., Boechat, M. I., Gilsanz, R., Loro, M. L., Roe, T. F., & Goodman, W. G. (1994). Gender differences in vertebral sizes in adults: biomechanical implications. Radiology, 190(3), 678–682. https://doi.org/10.1148/radiology.190.3.8115610
DOI: https://doi.org/10.1148/radiology.190.3.8115610
Google Scholar
Goodacre, J., Schlueter, D. K., Shark, L.-K., Spain, L., Platt, N., Platt, N., Mercer, J., Waterton, J. C., Bowes, M., Dixon, M., & Huddleston, J. (2018). Identifying Novel Acoustic Emission Biomarkers for Use in Knee Osteoarthritis Clinical Trials. Rheumatology, 57(suppl_3), key075.321. https://doi.org/10.1093/rheumatology/key075.321
DOI: https://doi.org/10.1093/rheumatology/key075.321
Google Scholar
Karpiński, R., Jaworski, Ł., Jonak, J., & Krakowski, P. (2019). Stress distribution in the knee joint in relation to tibiofemoral angle using the finite element method. MATEC Web of Conferences, 252, 07007. doi:10.1051/matecconf/201925207007
DOI: https://doi.org/10.1051/matecconf/201925207007
Google Scholar
Kim, K. S., Seo, J. H., Kang, J. U., & Song, C. G. (2009). An enhanced algorithm for knee joint sound classification using feature extraction based on time-frequency analysis. Computer Methods and Programs in Biomedicine, 94(2), 198–206. https://doi.org/10.1016/j.cmpb.2008.12.012
DOI: https://doi.org/10.1016/j.cmpb.2008.12.012
Google Scholar
Krakowski, P., Gerkowicz, A., Pietrzak, A., Krasowska, D., Jurkiewicz, A., Gorzelak, M., & Schwartz, R. A. (2018). Psoriatic arthritis – new perspectives. Archives of Medical Science. https://doi.org/10.5114/aoms.2018.77725
DOI: https://doi.org/10.5114/aoms.2018.77725
Google Scholar
Kręcisz, K., & Bączkowicz, D. (2018). Analysis and multiclass classification of pathological knee joints using vibroarthrographic signals. Computer Methods and Programs in Biomedicine, 154, 37–44. https://doi.org/10.1016/j.cmpb.2017.10.027
DOI: https://doi.org/10.1016/j.cmpb.2017.10.027
Google Scholar
Litak, G., Gajewski, J., Syta, A., & Jonak, J. (2008). Quantitative estimation of the tool wear effects in a ripping head by recurrence plots. Journal of Theoretical and Applied Mechanics, 46(3), 521–530.
Google Scholar
Litak, G., Syta, A., Gajewski, J., & Jonak, J. (2010). Detecting and identifying non-stationary courses in the ripping head power consumption by recurrence plots. Meccanica, 45(4), 603–608. https://doi.org/10.1007/s11012-009-9265-4
DOI: https://doi.org/10.1007/s11012-009-9265-4
Google Scholar
Litak, G., Syta, A., & Rusinek, R. (2011). Dynamical changes during composite milling: recurrence and multiscale entropy analysis. The International Journal of Advanced Manufacturing Technology, 56(5), 445–453. https://doi.org/10.1007/s00170-011-3195-8
DOI: https://doi.org/10.1007/s00170-011-3195-8
Google Scholar
Maciejewski, M., Dzierżak, R., Surtel, W., & Saran, T. (2016). Human ECG indicators for fast screening and evaluation. In R. S. Romaniuk (Ed.) (1003131). Presented at the Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, Wilga, Poland. https://doi.org/10.1117/12.2249149
DOI: https://doi.org/10.1117/12.2249149
Google Scholar
Maciejewski, M., Surtel, W., & Dzida, G. (2015). Human ECG signal parameters estimation during controlled physical activity. In R. S. Romaniuk (Ed.) (96621P). Presented at the XXXVI Symposium on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments, Wilga, Poland. https://doi.org/10.1117/12.2205811
DOI: https://doi.org/10.1117/12.2205811
Google Scholar
Maciejewski, M., Surtel, W., Wójcik, W., Masiak, J., Dzida, G., & Horoch, A. (2014). Telemedical systems for home monitoring of patients with chronic conditions in rural environment. Annals of Agricultural and Environmental Medicine, 21(1), 167–173.
Google Scholar
Marras, W. S., Jorgensen, M. J., Granata, K. P., & Wiand, B. (2001). Female and male trunk geometry: size and prediction of the spine loading trunk muscles derived from MRI.
Google Scholar
Clinical Biomechanics, 16(1), 38–46. https://doi.org/10.1016/S0268-0033(00)00046-2
DOI: https://doi.org/10.1016/S0268-0033(00)00046-2
Google Scholar
Marwan, N., Carmenromano, M., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5–6), 237–329. https://doi.org/10.1016/j.physrep.2006.11.001
DOI: https://doi.org/10.1016/j.physrep.2006.11.001
Google Scholar
Rangayyan, R. M., Oloumi, F., Wu, Y., & Cai, S. (2013). Fractal analysis of knee-joint vibroarthrographic signals via power spectral analysis. Biomedical Signal Processing and Control, 8(1), 23–29. https://doi.org/10.1016/j.bspc.2012.05.004
DOI: https://doi.org/10.1016/j.bspc.2012.05.004
Google Scholar
Shannon, C. E. (1948). A Mathematical Theory of Communication. Reprinted with corrections from The Bell System Technical Journal, 27, 379–423, 623–656.
DOI: https://doi.org/10.1002/j.1538-7305.1948.tb00917.x
Google Scholar
Shark, L.-K., Chen, H., & Goodacre, J. (2010). Knee Acoustic Emission: A Clue to Joint Ageing and Failure. Rheumatology, 49, I79–I79.
Google Scholar
Shark, L.-K., Chen, H., & Goodacre, J. (2011). Knee acoustic emission: A potential biomarker for quantitative assessment of joint ageing and degeneration. Medical Engineering & Physics, 33(5), 534–545. https://doi.org/10.1016/j.medengphy.2010.12.009
DOI: https://doi.org/10.1016/j.medengphy.2010.12.009
Google Scholar
Syta, A., Jonak, J., Jedliński, Ł., & Litak, G. (2012). Failure Diagnosis of a Gear Box by Recurrences. Journal of Vibration and Acoustics, 134(4), 041006. https://doi.org/10.1115/1.4005846
DOI: https://doi.org/10.1115/1.4005846
Google Scholar
Takens, F. (1981). Detecting strange attractors in turbulence. In D. Rand & L.-S. Young (Eds.), Dynamical Systems and Turbulence, Warwick 1980 (898, pp. 366–381). Berlin, Heidelberg: Springer. https://doi.org/10.1007/BFb0091924
DOI: https://doi.org/10.1007/BFb0091924
Google Scholar
Tool box of recurrence plot and recurrence quantification analysis – File Exchange – MATLAB Central. (2019, March 13). Retrieved from https://www.mathworks.com/matlabcentral/fileexchange/58246-tool-box-of-recurrence-plot-and-recurrence-quantification-analysis
Google Scholar
Wiens, A. D., Prahalad, S., & Inan, O. T. (2016). VibroCV: A computer vision-based vibroarthrography platform with possible application to Juvenile idiopathic arthritis. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 4431–4434). IEEE. https://doi.org/10.1109/EMBC.2016.7591710
DOI: https://doi.org/10.1109/EMBC.2016.7591710
Google Scholar
Wu, Y., Chen, P., Luo, X., Huang, H., Liao, L., Yao, Y., Wu, M., & Rangayyan, R. M. (2016). Quantification of knee vibroarthrographic signal irregularity associated with patellofemoral joint cartilage pathology based on entropy and envelope amplitude measures. Computer Methods and Programs in Biomedicine, 130, 1–12. https://doi.org/10.1016/j.cmpb.2016.03.021
DOI: https://doi.org/10.1016/j.cmpb.2016.03.021
Google Scholar
Yang, H. (2011). Multiscale Recurrence Quantification Analysis of Spatial Cardiac Vectorcardiogram Signals. IEEE Transactions on Biomedical Engineering, 58(2), 339–347. https://doi.org/10.1109/TBME.2010.2063704
DOI: https://doi.org/10.1109/TBME.2010.2063704
Google Scholar
Zubrzycki, J., Karpiński, R., & Górniak, B. (2016). Computer aided design and structural analysis of the endoprosthesis of the knee joint. Applied Computer Science, 12(2), 84–95.
Google Scholar
Authors
Robert KARPIŃSKIr.karpinski@pollub.pl
* Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin Poland
Authors
Anna MACHROWSKADepartment of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin Poland
Authors
Marcin MACIEJEWSKI Institute of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin Poland
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