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Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions

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Abstract

Externally detected vibroarthrographic (VAG) signals bear diagnostic information related to the roughness, softening, breakdown, or the state of lubrication of the articular cartilage surfaces of the knee joint. Analysis of VAG signals could provide quantitative indices for noninvasive diagnosis of articular cartilage breakdown and staging of osteoarthritis. We propose the use of statistical parameters of VAG signals, including the form factor involving the variance of the signal and its derivatives, skewness, kurtosis, and entropy, to classify VAG signals as normal or abnormal. With a database of 89 VAG signals, screening efficiency of up to 0.82 was achieved, in terms of the area under the receiver operating characteristics curve, using a neural network classifier based on radial basis functions.

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References

  1. Barr DA, Long L, Kernohan WG, Mollan RAB (1994) Continuous passive motion in computer assisted auscultation of the knee. Comput Meth Prog Biomed 43:159–169

    Article  Google Scholar 

  2. Beverland DE, Kernohan WG, Mollan RAB (1985) Analysis of physiological patello-femoral crepitus. In: Byford GH (ed) Technology in health care. Biological Engineering Society, London, pp 137–138

  3. Beverland DE, Kernohan WG, Mollan RAB (1985) Problems in the analysis of vibration emission from the patello-femoral joint. Med Bio Eng Comput 23(Suppl 2):1253–1254

    Google Scholar 

  4. Beverland DE, Kernohan WG, Mollan RAB (1985) What is physiological patello-femoral crepitus? Med Bio Eng Comput 23(Suppl 2):1249–1250

    Google Scholar 

  5. Beverland DE, McCoy GF, Kernohan WG, Mollan RAB (1986) What is patellofemoral crepitus? J Bone Joint Surg 68-B:496

    Google Scholar 

  6. Binnie CD, Batchelor BG, Bowring PA, Darby CE, Herber L, Lloyd DSL, Smith DM, Smith GF, Smith M (1978) Computer-assisted interpretation of clinical EEGs. Electroencephal Clin Neurophysiol 44:575–585

    Article  Google Scholar 

  7. Binnie CD, Batchelor BG, Gainsborough AJ, Lloyd DSL, Smith DM, Smith GF (1979) Visual and computer-assisted assessment of the EEG in epilepsy of late onset. Electroencephal Clin Neurophysiol 47:102–107

    Article  Google Scholar 

  8. Bircher E (1913) Zur diagnose der meniscusluxation und des meniscusabrisses. Zentralbl f Chir 40:1852–1857

    Google Scholar 

  9. Blodgett WE (1902) Auscultation of the knee joint. Boston Med Surg J 146(3):63–66

    Google Scholar 

  10. Chen S, Cowan CFN, Grant PM (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Net 2(2):302–309

    Article  Google Scholar 

  11. Chu ML, Gradisar IA, Mostardi R (1978) A noninvasive electroacoustical evaluation technique of cartilage damage in pathological knee joints. Med Bio Eng Comput 16:437–442

    Article  Google Scholar 

  12. Chu ML, Gradisar IA, Railey MR, Bowling GF (1976) Detection of knee joint diseases using acoustical pattern recognition technique. J Biomech 9:111–114

    Article  Google Scholar 

  13. Chu ML, Gradisar IA, Railey MR, Bowling GF (1976) An electro-acoustical technique for the detection of knee joint noise. Med Res Eng 12(1):18–20

    Google Scholar 

  14. Chu ML, Gradisar IA, Zavodney LD (1978) Possible clinical application of a noninvasive monitoring technique of cartilage damage in pathological knee joints. J Clin Eng 3(1):19–27

    Google Scholar 

  15. Cooper R, Osselton JW, Shaw JC (1980) EEG technology, 3rd edn. Butterworths, London

    Google Scholar 

  16. Duda RO, Hart PE (1973) Pattern classification and scene analysis. Wiley, New York

    MATH  Google Scholar 

  17. Erb KH (1933) Über die möglichkeit der registrierung von gelenkgeräuschen. Deutsche Ztschr f Chir 241:237–245

    Google Scholar 

  18. Fischer H, Johnson EW (1960) Analysis of sounds from normal and pathologic knee joints. In: Proc 3rd intl congr phys med, pp 50–57

  19. Frank CB, Rangayyan RM, Bell GD (1990) Analysis of knee sound signals for non-invasive diagnosis of cartilage pathology. IEEE Eng Med Biol Mag 9(1):65–68

    Article  Google Scholar 

  20. Haykin S (2002) Neural networks: a comprehensive foundation, 2nd edn. Prentice-Hall PTR, Englewood Cliffs

    Google Scholar 

  21. Hjorth B (1970) EEG analysis based on time domain properties. Electroencephal Clin Neurophysiol 29:306–310

    Article  Google Scholar 

  22. Hjorth B (1973) The physical significance of time domain descriptors in EEG analysis. Electroencephal Clin Neurophysiol 34:321–325

    Article  Google Scholar 

  23. Hjorth B (1975) Time domain descriptors and their relation to a particular model for generation of EEG activity. In: Dolce G, Künkel H (eds) CEAN: computerised EEG analysis, Gustav Fischer, Stuttgart, pp 3–8

  24. Inoue J, Nagata Y, Suzuki K (1986) Measurement of knee joint sounds by microphone. Sangyo Ika Daigaku Zasshi 8(3):307–316

    Google Scholar 

  25. Jackson RW, Abe I (1972) The role of arthroscopy in the management of disorders of the knee: An analysis of 200 consecutive examinations. J Bone Joint Surg 54-B:310–322

    Google Scholar 

  26. Jiang CC, Lee JH, Yuan TT (2000) Vibration arthrometry in the patients with failed total knee replacement. IEEE Trans Biomed Eng 47(2):218–227

    Article  Google Scholar 

  27. Jiang CC, Liu YJ, Hang YS (1995) Vibration arthrometry for the diagnosis of meniscal tear of the knee. J Orthop Surg Rep China 12:1–5

    Google Scholar 

  28. Jiang CC, Liu YJ, Yip KM, Wu E (1993) Physiological patellofemoral crepitus in knee joint disorders. Bull Hosp Joint Dis 53(4):22–26

    Google Scholar 

  29. Kernohan WG, Barr DA, McCoy GF, Mollan RAB (1991) Vibration arthrometry in assessment of knee disorders: the problem of angular velocity. J Biomed Eng 13:35–38

    Article  Google Scholar 

  30. Kernohan WG, Beverland DE, McCoy GF, Hamilton A, Watson P, Mollan RAB (1990) Vibration arthrometry. Acta Orthop Scand 61(1):70–79

    Google Scholar 

  31. Kernohan WG, Beverland DE, McCoy GF, Shaw SN, Wallace RGH, McCullagh GC, Mollan RAB (1986) The diagnostic potential of vibration arthrography. Clin Orthop Rel Res 210:106–112

    Google Scholar 

  32. Kernohan WG, Mollan RAB (1982) Microcomputer analysis of joint vibration. J Microcomp Appl 5:287–296

    Article  Google Scholar 

  33. Kotani K, Suzuki K (1983) Acoustic analysis of joint-sound through passive motion with special reference to degenerative osteoarthrosis of the knee joints. Nippon Seikeigeta Gakkai Zasshi 57:1869–1880

    Google Scholar 

  34. Krishnan S, Rangayyan RM, Bell GD, Frank CB (2000) Adaptive time-frequency analysis of knee joint vibroarthrographic signals for noninvasive screening of articular cartilage pathology. IEEE Trans Biomed Eng 47(6):773–783

    Article  Google Scholar 

  35. Krishnan S, Rangayyan RM, Bell GD, Frank CB (2001) Auditory display of knee-joint vibration signals. J Acoust Soc Am 110(6):3292–3304

    Article  Google Scholar 

  36. Krishnan S, Rangayyan RM, Bell GD, Frank CB, Ladly KO (1997) Adaptive filtering, modelling, and classification of knee joint vibroarthrographic signals for non-invasive diagnosis of articular cartilage pathology. Med Bio Eng Comput 35:677–684

    Article  Google Scholar 

  37. Ladly KO, Frank CB, Bell GD, Zhang YT, Rangayyan RM (1993) The effect of external loads and cyclic loading on normal patellofemoral joint signals. Spl Iss Biomed Eng Def Sci J (India) 43:201–210

    Google Scholar 

  38. Lund F, Nilsson BE (1980) Arthroscopy of the patello-femoral joint. Acta Orthop Scand 51:297–302

    Article  Google Scholar 

  39. Mankin HJ (1982) The response of articular cartilage to mechanical injury. J Bone Joint Surg 64-A:462–466

    Google Scholar 

  40. Marques de Sá JP (2003) Applied Statistics using SPSS, STATISTICA, and MATLAB. Springer, Berlin

    Google Scholar 

  41. McCoy GF, McCrea JD, Beverland DE, Kernohan WG, Mollan RAB (1987) Vibration arthrography as a diagnostic aid in diseases of the knee. J Bone Joint Surg 69-B(2):288–293

    Google Scholar 

  42. Metz CE (1978) Basic principles of ROC analysis. Sem Nucl Med VIII(4):283–298

    Article  Google Scholar 

  43. Metz CE, Pesce L (2006) Readings in ROC Analysis, with Emphasis on Medical Applications; available at www. radiology. uchicago. http://www.edu /krl/ KRL_ROC/ ROC_analysis_by_topic4.htm. University of Chicago, Chicago

  44. Mollan RAB, Kernohan WG, Watters PH (1983) Artefact encountered by the vibration detection system. J Biomech 16(3):193–199

    Article  Google Scholar 

  45. Moussavi ZMK, Rangayyan RM, Bell GD, Frank CB, Ladly KO, Zhang YT (1996) Screening of vibroarthrographic signals via adaptive segmentation and linear prediction modeling. IEEE Trans Biomed Eng 43(1):15–23

    Article  Google Scholar 

  46. Mu T, Nandi AK, Rangayyan RM (2007) Strict 2-surface proximal classification of knee-joint vibroarthrographic signals. In: Proc. 29th ann intl conf IEEE eng med bio soc. IEEE, Lyon, pp 4911–4914

  47. Nagata Y (1988) Joint-sounds in gonoarthrosis—clinical application of phonoarthrography for the knees. J Univ Occup Environ Health Japan 10(1):47–58

    Google Scholar 

  48. Nagata Y, Suzuki K, Kobayashi Y, Sasaki M, Inoue J, Takyu H (1986) Joint-sounds clinical experience of the knee joint. Sangyo Ika Daigaku Zasshi 8:425–428

    Google Scholar 

  49. Peylan A (1953) Direct auscultation of the joints (preliminary clinical observations). Rheumatolgy 9:77–81

    Google Scholar 

  50. Rabin EL, Ehrlich MG, Cherrack R, Abermathy P, Paul IL, Rose RM (1978) Effect of repetitive impulsive loading on the knee joints of rabbits. Clin Orthop 131:288

    Google Scholar 

  51. Rangayyan RM (2002) Biomedical signal analysis—a case-study approach. IEEE/Wiley, New York

    Google Scholar 

  52. Rangayyan RM (2005) Biomedical image analysis. CRC, Boca Raton

    Google Scholar 

  53. Rangayyan RM, Krishnan S (2001) Feature identification in the time-frequency plane by using the Hough–Radon transform. Patt Recog 34:1147–1158

    Article  MATH  Google Scholar 

  54. Rangayyan RM, Krishnan S, Bell GD, Frank CB, Ladly KO (1997) Parametric representation and screening of knee joint vibroarthrographic signals. IEEE Trans Biomed Eng 44(11):1068–1074

    Article  Google Scholar 

  55. Rangayyan RM, Wu YF (2007) Analysis of knee-joint vibroarthrographic signals using statistical measures. In:Proc. 20th IEEE intl symp computer-based med sys. IEEE, Maribor, pp 377–382

  56. Reddy NP, Rothschild BM, Mandal M, Gupta V, Suryanarayanan S (1995) Noninvasive acceleration measurements to characterize knee arthritis and chondromalacia. Ann Biomed Eng 23:78–84

    Article  Google Scholar 

  57. Reddy NP, Rothschild BM, Verrall E, Joshi A (2001) Noninvasive measurement of acceleration at the knee joint in patients with rheumatoid arthritis and spondyloarthropathy of the knee. Ann Biomed Eng 29(12):1106–1111

    Article  Google Scholar 

  58. Sasaki M, Suzuki K, Inoue J (1991) Analysis and application of joint sounds to osteoarthritis of the knee. Trans Comb Meet Orthop Res Soc, USA, Japan and Canada, p 164

  59. Shen YP, Rangayyan RM, Bell GD, Frank CB, Zhang YT, Ladly KO (1995) Localization of knee joint cartilage pathology by multichannel vibroarthrography. Med Eng Phys 17(8):583–594

    Article  Google Scholar 

  60. Steindler A (1937) Auscultation of joints. J Bone Joint Surg 19(1):121–136

    Google Scholar 

  61. Szabo E, Danis L, Torok Z (1972) Examination of the acoustic phenomena observed in the knee. Traumatologia 15(2):118–127

    Google Scholar 

  62. Tavathia S, Rangayyan RM, Frank CB, Bell GD, Ladly KO, Zhang YT (1992) Analysis of knee vibration signals using linear prediction. IEEE Trans Biomed Eng 39(9):959–970

    Article  Google Scholar 

  63. Umapathy K, Krishnan S (2006) Modified local discriminant bases algorithm and its application in analysis of human knee joint vibration signals. IEEE Trans Biomed Eng 53(3):517–523

    Article  Google Scholar 

  64. Zhang YT, Frank CB, Rangayyan RM, Bell GD (1992) Mathematical modeling and spectrum analysis of the physiological patello-femoral pulse train produced by slow knee movement. IEEE Trans Biomed Eng 39(9):971–979

    Article  Google Scholar 

  65. Zhang YT, Rangayyan RM, Frank CB, Bell GD (1994) Adaptive cancellation of muscle contraction interference from knee joint vibration signals. IEEE Trans Biomed Eng 41(2):181–191

    Article  Google Scholar 

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Acknowledgments

This work was supported by the Doctoral Program Foundation of the Ministry of Education of China under Grant No. 20060013007 awarded to Y. F. Wu, and by the University of Calgary in the form of a “University Professorship” awarded to R. M. Rangayyan. We thank Dr. Cyril B. Frank and Dr. G. Douglas Bell, Department of Surgery and Sport Medicine Centre, University of Calgary, for their contributions to previous related projects.

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  1. Department of Electrical and Computer Engineering Schulich School of Engineering, 2500 University Dr. NW University of Calgary, Calgary, AB, Canada, T2N 1N4

    Rangaraj M. Rangayyan

  2. School of Information Engineering, Beijing University of Posts and Telecommunications, 10 Xi Tu Cheng Road, Haidian District, Beijing, 100876, China

    Y. F. Wu

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Correspondence to Rangaraj M. Rangayyan.

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Rangayyan, R.M., Wu, Y.F. Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions. Med Biol Eng Comput 46, 223–232 (2008). https://doi.org/10.1007/s11517-007-0278-7

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