1. Movement quantification in epileptic seizures: A feasibility study for a new 3D approach 
João Paulo Silva Cunha, Luís M. Paula, Virgílio F. Bento, Candas Bilgin, Eduardo Dias, Soheyl Noachtar 
Medical Engineering and Physics 
Volume 34, Issue 7, Pages (September 2012)
DOI: /j.medengphy
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2. Fig. 1 2D video setup geometric model. Adapted from Re. [9].
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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3. Fig. 2
System setup with the 4 high-speed SVCams to achieve a 3D motion tracking system for seizure movements. A datastation processes the massive information coming from the cameras and feeds pre-processed data to the workstation where the MOIs are analyzed.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
Copyright © 2011 IPEM Terms and Conditions

4. Fig. 3
Setup of the infrared reflective markers placed on the patient/subject.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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5. Fig. 4
Simple motor paradigm executed perpendicularly to the 2D projection plane. The volunteer left-arm punch movement was used as one of the worst cases for a 2D approach.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
Copyright © 2011 IPEM Terms and Conditions

6. Fig. 5
Complex motor motion characterized by a periodic movement in both legs due to an epileptic seizure.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
Copyright © 2011 IPEM Terms and Conditions

7. Fig. 6
References used to convert the 2D movement quantification data from pixels to millimetres (simple motor case).
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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8. Fig. 7
References used to convert the 2D movement quantification data from pixels to millimetres (complex motor case).
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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9. Fig. 8
Aspect of the MovEpil3D software framework. Several 3D motion extracted features can be analyzed and compared. In this example, a marker (USL1) movement velocity (top, left), the corresponding 3D stick figure (top, right) and the 3D spatial trajectory (lower, right) are visualized. In the lower left the software presents a marker position interactive diagram where the user can select the marker for analysis.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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10. Fig. 9
Aspect of a synchronized output video obtained with the MovEpil3D software framework support. The seizure EEG (on the left) is displayed dynamically synchronized with the 3D stick figure (top right) and the corresponding video of the seizure (lower right). This and other video files can be downloaded from the supplementary files section of this paper.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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11. Fig. 10
Distance to the initial position and error between 2D and 3D methods for movement of a marker located in the right hand wrist, using the worst 2D reference (A and B), and the best reference (C and D).
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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12. Fig. 11
Frequency spectrum of 2D (top; obtained with the best reference) and 3D (bottom) distance estimation signals of the selected MOI of the simple motor paradigm.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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13. Fig. 12
Distance to the initial position and error between 2D and 3D methods for movement of a marker located in the lower leg using the worst reference (A and B) and the best reference (C and D).
Medical Engineering and Physics  , DOI: ( /j.medengphy )
Copyright © 2011 IPEM Terms and Conditions

14. Fig. 13
Frequency spectrum for 2D (top) and 3D (bottom) distance estimation signals for the complex motor MOI of the epileptic seizure.
Medical Engineering and Physics  , DOI: ( /j.medengphy )
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