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Application of acoustic signal processing methods in detecting differences between open and closed kinematic chain movement for the knee joint

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Języki publikacji
EN
Abstrakty
EN
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.
Rocznik
Strony
36--48
Opis fizyczny
Bibliogr. 31 poz., fig., tab.
Twórcy
  • Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
  • Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
  • Institute of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
Bibliografia
  • [1] 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. doi:10.1080/10255840902828375
  • [2] 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). doi:10.1186/s12891-019-2429-z
  • [3] Bączkowicz, D., & Majorczyk, E. (2014). Joint motion quality in vibroacoustic signal analysis for patients with patellofemoral joint disorders. BMC Musculoskeletal Disorders, 15, 426. doi:10.1186/1471-2474-15-426
  • [4] 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. doi:10.1016/0021-9290(81)90060-9
  • [5] Chen, Y., & Yang, H. (2012). Multiscale recurrence analysis of long-term nonlinear and nonstationary time series. Chaos, Solitons & Fractals, 45(7), 978–987. doi:10.1016/j.chaos.2012.03.013
  • [6] 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. doi:10.18494/SAM.2018.1877
  • [7] 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. doi:10.1148/radiology.190.3.8115610
  • [8] 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. doi:10.1093/rheumatology/key075.321
  • [9] 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
  • [10] 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. doi:10.1016/j.cmpb.2008.12.012
  • [11] 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
  • [12] 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. doi:10.1016/j.cmpb.2017.10.027
  • [13] 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.
  • [14] 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. doi:10.1007/s11012-009-9265-4
  • [15] 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. doi:10.1007/s00170-011-3195-8
  • [16] 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. doi:10.1117/12.2249149
  • [17] 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. doi:10.1117/12.2205811
  • [18] 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.
  • [19] 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. Clinical Biomechanics, 16(1), 38–46. doi:10.1016/S0268-0033(00)00046-2
  • [20] Marwan, N., Carmenromano, M., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5–6), 237–329. doi:10.1016/j.physrep.2006.11.001
  • [21] 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. doi:10.1016/j.bspc.2012.05.004
  • [22] Shannon, C. E. (1948). A Mathematical Theory of Communication. Reprinted with corrections from The Bell System Technical Journal, 27, 379–423, 623–656.
  • [23] Shark, L.-K., Chen, H., & Goodacre, J. (2010). Knee Acoustic Emission: A Clue to Joint Ageing and Failure. Rheumatology, 49, I79–I79.
  • [24] 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. doi:10.1016/j.medengphy.2010.12.009
  • [25] 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. doi:10.1115/1.4005846
  • [26] 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. doi:10.1007/BFb0091924
  • [27] 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
  • [28] Wiens, A. D., Prahalad, S., & Inan, O. T. (2016). VibroCV: A computer vision-based vibroar-thrography 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
  • [29] 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. doi:10.1016/j.cmpb.2016.03.021
  • [30] Yang, H. (2011). Multiscale Recurrence Quantification Analysis of Spatial Cardiac Vector-cardiogram Signals. IEEE Transactions on Biomedical Engineering, 58(2), 339–347. doi:10.1109/TBME.2010.2063704
  • [31] 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.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2a2ddb8c-96f9-4f3e-97a4-a73196b5971d
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