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. 2022 Dec 6;22(23):9542.
doi: 10.3390/s22239542.

Repeatability of the Vibroarthrogram in the Temporomandibular Joints

Adam Łysiak  1 , Tomasz Marciniak  2 , Dawid Bączkowicz  3
Affiliations

Repeatability of the Vibroarthrogram in the Temporomandibular Joints

Adam Łysiak et al. Sensors (Basel). .

Abstract

Current research concerning the repeatability of the joint's sounds examination in the temporomandibular joints (TMJ) is inconclusive; thus, the aim of this study was to investigate the repeatability of the specific features of the vibroarthrogram (VAG) in the TMJ using accelerometers. The joint sounds of both TMJs were measured with VAG accelerometers in two groups, study and control, each consisting of 47 participants (n = 94). Two VAG recording sessions consisted of 10 jaw open/close cycles guided by a metronome. The intraclass correlation coefficient (ICC) was calculated for seven VAG signal features. Additionally, a k-nearest-neighbors (KNN) classifier was defined and compared with a state-of-the-art method (joint vibration analysis (JVA) decision tree). ICC indicated excellent (for the integral below 300 Hz feature), good (total integral, integral above 300 Hz, and median frequency features), moderate (integral below to integral above 300 Hz ratio feature) and poor (peak amplitude feature) reliability. The accuracy scores for the KNN classifier (up to 0.81) were higher than those for the JVA decision tree (up to 0.60). The results of this study could open up a new field of research focused on the features of the vibroarthrogram in the context of the TMJ, further improving the diagnosing process.

Keywords: JVA; TMD; TMJ; VAG; intraclass correlation coefficient; joint sounds; joint vibration analysis; repeatability; temporomandibular disorders; vibroarthrography.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure A1
Figure A1
Box plots of raw features obtained for the first measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A2
Figure A2
Box plots of raw features obtained for the second measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A3
Figure A3
Box plots of norm1 features obtained for the first measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A4
Figure A4
Box plots of norm1 features obtained for the second measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A5
Figure A5
Box plots of norm2 features obtained for the first measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A6
Figure A6
Box plots of norm2 features obtained for the second measurement: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure A7
Figure A7
Confusion matrices for raw features used in the JVA decision tree classifier for the (a) first and (b) second signals.
Figure A8
Figure A8
Confusion matrices for norm1 features used in the JVA decision tree classifier for the (a) first and (b) second signals.
Figure A9
Figure A9
Confusion matrices for norm2 features used in the JVA decision tree classifier for the (a) first and (b) second signals.
Figure A10
Figure A10
Confusion matrices for raw features used in the KNN classifier for the (a) first and (b) second signals.
Figure 1
Figure 1
Exemplary VAG signal for (a) asymptomatic and (b) symptomatic temporomandibular joints.
Figure 2
Figure 2
Sensors and their placement on the subject’s joints.
Figure 3
Figure 3
Box plots of raw features: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure 4
Figure 4
Boxplots of the norm1 features: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
Figure 5
Figure 5
Box plots of norm2 features: (a) TI feature, (b) IB3 feature, (c) IA3 feature, (d) IBAR feature, (e) PA feature, (f) PF feature, (g) MF feature.
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