Use of incremental decomposition and spectrogram in vibroacoustic signal analysis in knee joint disease examination

Dołęgowski, M.

doi:10.15199/48.2018.07.41

Cited by 6 publications

(4 citation statements)

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“…Nevertheless, there is evidence to suggest that the presented method is sensitive for tribological changes within the articular environment and may be a helpful tool to monitor the effectiveness of VS using in knee OA treatment. 43 acknowledged. The author(s) received no financial support for the research, authorship, and/or publication of this article.…”

Section: Discussionmentioning

confidence: 99%

Effects of Viscosupplementation on Quality of Knee Joint Arthrokinematic Motion Analyzed by Vibroarthrography

Bączkowicz

Skiba²,

Szmajda

et al. 2019

CARTILAGE

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Objective To evaluate the influence of viscosupplementation on osteoarthritic knee arthrokinematics analyzed by VAG. It is considered that intra-articular hyaluronic acid injection may improve the function of synovial joints by recovery of friction-reducing properties of articular environment. Design Thirty-five patients with knee osteoarthritis (grade II according to the Kellgren-Lawrence system) and 50 asymptomatic subjects were enrolled in the study. Patients were analyzed at 3 time points: 1 day before and 2 weeks and 4 weeks after single injection of 1.5% cross-linked hyaluronate. Control subjects were tested once. The vibroarthrographic signals were collected during knee flexion/extension motion using an accelerator and described by variation of mean square (VMS), mean range (R5), and power spectral density for frequency of 50 to 250 Hz (P1), and 250 to 450 Hz (P2). Results Patients before viscosupplementation were characterized by about 2-fold higher values of vibroarthrographic parameters than controls. Two weeks after the procedure, the values of R5, P1, and P2 significantly decreased, in comparison to pre-injection. At 4 weeks post-injection, we noted a significant increase in R5, P1, and P2 values, when compared to 2 weeks post-injection. Finally, at 4 weeks post-injection, the level of VMS, R5, and P2 parameters did not differ from values obtained at pre-injection. Conclusions We showed that viscosupplementation may be effective in providing arthrokinematics improvement, but with a relatively short period of duration. This phenomenon is observed as decreased vibroacoustic emission, which reflects a more smooth movement in the joint.

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Section: Discussionmentioning

confidence: 99%

Effects of Viscosupplementation on Quality of Knee Joint Arthrokinematic Motion Analyzed by Vibroarthrography

Bączkowicz

Skiba²,

Szmajda

et al. 2019

CARTILAGE

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“…The requirements for such a system are a 100 MHz clock and 32 kB program memory microcontroller with an external 5 MS/s sampling rate and 8-bit resolution ADC. Apart from its use in electric arc detection, incremental decomposition has found an application in medicine [71].…”

Section: Analyses Of Measurements Using Incremental Decompositionmentioning

confidence: 99%

A Novel Algorithm for Fast DC Electric Arc Detection

Dołęgowski

Szmajda

2021

Energies

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Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.

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“…Using the spatiotemporal analysis method Wu recommends to use adaptive segmentation [ 8 , 9 ] to avoid redundancy in given segments, and emphasizes its usefulness for calculating sets of features and signal classification. The statistical analysis is often used to determine distribution measures and statistical parameters [ 10 , 11 ], giving the possibility to display data in the form of a tabular summary [ 12 ] and graphic forms such as the histogram [ 6 ] or the box plot [ 13 , 14 , 15 ], and to analyze variations using various types of tests (t-test [ 16 ], Kruskal–Wallis test [ 13 ], one-way ANOVA test [ 4 ], Wilcoxon rank-sum test [ 11 ]). The time-frequency analysis and the frequency analysis supported by using statistical analysis are commonly used in the field of signal processing.…”

Section: Standard Descriptorsmentioning

confidence: 99%

“…Łysiak et al [ 14 ] used STFT and spectrograms, on whose specific analysis the new three descriptors have been proposed. Dołęgowski et al [ 15 ] proposed the incremental decomposition of voltage in time and the spectrogram as the methods to identify the knee joint disease stage and compared the statistical parameters of normalized energy values of the band 50–250 Hz (P1) and 250–450 Hz (P2). Befrui et al [ 2 ] in their measurement system used the two accelerometers, the piezoelectric disk and the potentiometer (four channels) in their measurement system.…”

Section: Standard Descriptorsmentioning

confidence: 99%

Vibroarthrographic Signal Spectral Features in 5-Class Knee Joint Classification

Łysiak

Fron

Bączkowicz

et al. 2020

Sensors

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Vibroarthrography (VAG) is a non-invasive and potentially widely available method supporting the joint diagnosis process. This research was conducted using VAG signals classified to five different condition classes: three stages of chondromalacia patellae, osteoarthritis, and control group (healthy knee joint). Ten new spectral features were proposed, distinguishing not only neighboring classes, but every class combination. Additionally, Frequency Range Maps were proposed as the frequency feature extraction visualization method. The results were compared to state-of-the-art frequency features using the Bhattacharyya coefficient and the set of ten different classification algorithms. All methods evaluating proposed features indicated the superiority of the new features compared to the state-of-the-art. In terms of Bhattacharyya coefficient, newly proposed features proved to be over 25% better, and the classification accuracy was on average 9% better.

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Use of incremental decomposition and spectrogram in vibroacoustic signal analysis in knee joint disease examination

Cited by 6 publications

References 0 publications

Effects of Viscosupplementation on Quality of Knee Joint Arthrokinematic Motion Analyzed by Vibroarthrography

Effects of Viscosupplementation on Quality of Knee Joint Arthrokinematic Motion Analyzed by Vibroarthrography

A Novel Algorithm for Fast DC Electric Arc Detection

Vibroarthrographic Signal Spectral Features in 5-Class Knee Joint Classification

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