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. 2008:2008:1948-51.
doi: 10.1109/IEMBS.2008.4649569.

Autoregressive nodeling of physiological tremor under microsurgical conditions

Brian C Becker  1 , Harsha Tummala, Cameron N Riviere
Affiliations

Autoregressive nodeling of physiological tremor under microsurgical conditions

Brian C Becker et al. Annu Int Conf IEEE Eng Med Biol Soc. 2008.

Abstract

Tremor was recorded under simulated vitreoretinal microsurgical conditions as subjects attempted to hold an instrument motionless. Several autoregressive models (AR, ARMA, multivariate, and nonlinear) are generated to predict the next value of tremor. It is shown that a sixth order ARMA model predictor can predict a tremor having an amplitude of 96.6 +/- 84.5 microns RMS with an error of 8.2 +/- 5.9 microns RMS, a mean improvement of 47.5% over simple last-value prediction.

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Figures

Figure 1
Figure 1
(a) ASAP measuring and displaying instrument position on LCD screen. (b) Instrument tip with LEDs being inserted through face mask eye. The two notches on opposite sides function as simulated sclerotomies to brace the tool.
Figure 2
Figure 2
AR and ARMA results for X (top), Y (middle), and Z (bottom) tremor components for a typical subject under Scenario 1 (instrument braced against side of eye). For this sample, tremor amplitude is 45.4, 62.9, and 5.4 μm RMS in x, y, and z, respectively.
Figure 3
Figure 3
AR and ARMA results for X (top), Y (middle), and Z (bottom) tremor components under Scenario 2 (instrument not braced against side of eye). For this sample, tremor amplitude is 46.4, 31.9, and 24.1 μm RMS in x, y, and z, respectively.
Figure 4
Figure 4
AR and ARMA results for X (top), Y (middle), and Z (bottom) tremor components for a typical subject under Scenario 3 (instrument braced, but no visual feedback). For this sample, tremor amplitude is 254.0, 166.1, and 15.2 μm RMS in x, y, and z, respectively.
Figure 5
Figure 5
Mean percentage improvement for AR and ARMA in comparison with last-value prediction.
Figure 6
Figure 6
Box and whisker plot of the ARMA coefficients (the error term coefficients yield a similar plot with smaller coefficients).
Figure 7
Figure 7
Bode diagram of sixth order mean ARMA model.
Figure 8
Figure 8
Bode diagram of Scenario 1 ARMA model for X component
Figure 9
Figure 9
Bode diagram of Scenario 1 ARMA model for Y component
Figure 10
Figure 10
Bode diagram of Scenario 1 ARMA model for Z component
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