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. 2014 Dec 12:15:426.
doi: 10.1186/1471-2474-15-426.

Joint motion quality in vibroacoustic signal analysis for patients with patellofemoral joint disorders

Dawid Bączkowicz  1 , Edyta Majorczyk
Affiliations

Joint motion quality in vibroacoustic signal analysis for patients with patellofemoral joint disorders

Dawid Bączkowicz et al. BMC Musculoskelet Disord. .

Abstract

Background: Chondromalacia, lateral patellar compression syndrome and osteoarthritis are common patellofemoral joint disorders leading to functional and/or structural disturbances in articular surfaces. The objective of the study was to evaluate their impact on joint motion quality via the vibroacoustic signal generated during joint movement analysis.

Methods: Seventy-three patients (30 with chondromalacia, 21 with lateral patellar compression syndrome, and 22 with osteoarthritis) and 32 healthy controls were tested during flexion/extension knee motion for vibroacoustic signals using an acceleration sensor. Estimated parameters: variation of mean square (VMS), difference between mean of four maximum and mean of four minimum values (R4), power spectral density for frequency of 50-250 Hz (P1) and 250-450 Hz (P2) were analyzed.

Results: Vibroacoustic signals recorded for particular disorders were characterized by significantly higher values of parameters in comparison to the control group. Moreover, differences were found among the various types of patellofemoral joint disturbances. Chondromalacia and osteoarthritis groups showed differences in all parameters examined. In addition, osteoarthritis patients exhibited differences in VMS, P1 and P2 values in comparison to lateral patellar compression syndrome patients. However, only the value of R4 was found to differ between knees with lateral patellar compression syndrome and those with chondromalacia.

Conclusion: Our results suggest that particular disorders are characterized by specific vibroacoustic patterns of waveforms as well as values of analyzed parameters.

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Figures

Figure 1
Figure 1
Correct attachment of vibroacoustic sensor.
Figure 2
Figure 2
Time series specific for particular PFJ disorders. (A), control healthy knee; (B) knee with lateral patellar compression syndrome; (C) knee with chondromalacia; (D) knee with patellofemoral joint osteoarthritis.
Figure 3
Figure 3
Signal time-frequency analysis representative for particular PFJ disorders. (A), control healthy knee; (B) knee with lateral patellar compression syndrome; (C) knee with chondromalacia; (D) knee with patellofemoral joint osteoarthritis.
Figure 4
Figure 4
Power spectrum distribution in VAG signal for each analyzed group.
See this image and copyright information in PMC

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Pre-publication history
    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/15/426/prepub

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