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Exproloring Micro-Movements for Diagnostics of Neurological Problems

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AAFG 2005 . Exproloring Micro-Movements for Diagnostics of Neurological Problems. Jalo Kääminen Department of Computer Sciences University of Tampere Finland Jalo.Kaaminen @uta.fi. April , 2005. FDexterity.

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slide1

AAFG 2005

Exproloring Micro-Movements for Diagnostics of Neurological Problems

Jalo Kääminen

Department of Computer Sciences

University of Tampere Finland

[email protected]

April, 2005

slide2

FDexterity

The original goal of Finger Dexterity software (FDTT) was the training of fine accurate motor movement.

The game can be used as a test to measure finger dexterity and hand-eye coordination.

The software allows recording and estimation of an individual\'s ability to move the fingers and to control fine micro-movements using a stylus.

We explored the possibility to use FDTT to record micro-movements and behavioral artifacts for earlier diagnostics of neurological problems in children and adults.

J.Kääminen p 02_19 04.04.2005

slide3

FDexterity

Tremor can be as a symptom of such neurological diseases as Parkinson\'s disease, multiple sclerosis, diseases of or damage to the cerebellum, or as a result of some drugs\' application.

Coordination problems in Parkinson’s disease include difficulty in carrying out such tasks as brushing teeth, walking, speaking, and writing, and worsening rigidity.

While the more obvious Parkinson’s symptoms, such as visible tremors and muscular rigidity, appear at a later stage in the progress of the disease, the level of deterioration in a patient’s ability to control micromovements must be detected as early as possible.

J.Kääminen p 03_19 04.04.2005

slide4

FDexterity

A successful test may help in the early diagnostics of diseases such as Parkinson’s or the drugs dependence or other neurological syndromes.

This could open the way for treatment that may delay the progression of this presently incurable disease.

Several techniques have been proposed, most of them with complex test procedured and specialized harware.

J.Kääminen p 04_19 04.04.2005

slide5

FDexterity

Research Questions are:

Could relevant information be gained from FDTT recordings to estimate whether the technique could be used as a screening method?

Does tremor have an impact on a personal game performance?

How do coordination problems show themselves in the recordings?

J.Kääminen p 05_19 04.04.2005

slide6

The scanpath is being recorded.

The green rectangle is the green start zone.

To complete the game the player need to cross the red rectangle.

The small field is intended for input.

FDexterity

Finger Dexterity Test & Training (Game)

There are two fields when player start the game.

The big field restricted with white border, where the graphs appears.

Play!

J.Kääminen p 06_19 04.04.2005

slide7

1/130pxls 2/246pxls 3/228pxls 4/232pxls 5/236pxls

FDexterity

5 different contour graphs have been used in testing.

The graphs\' sampling is homogeneous enough both on X and Y axis.

J.Kääminen p 07_19 04.04.2005

slide8

FDexterity

Pilot Game Testing

8 subjects: with normal vision and hearing, ages 10-59

Software: ‘Finger Dexterity’ game, iPAQ pocket PC version

Hardware: iPAQ pocket PC with touchscreen and stylus input

Conditions: a normal room, with silent background music to release any tension and concern for how results might be evaluated.

Training: A brief training session preceded the actual recording to make sure the subject knows how to handle the pen and use the application. Usually, 2-4 inputs were enough to learn the application well to carry out the actual recordings. Generally, the software was surprisingly easy to adopt even with persons over 50 years old with normal vision.

J.Kääminen p 08_19 4.04.2005

slide9

FDexterity

  • Recordings: Each subject has implemented 20 recorded trials.
  • Log file format:
    • Graph number
    • Scale/zoom factor
    • Time, s, to complete the task
    • Errors (out-of-screen)
    • The average deviation on X, pxls
    • The average deviation in Y, pxls
    • Correlation on X
    • Correlation on Y
    • Correlation on XY

J.Kääminen p 09_19 04.04.2005

slide10

FDexterity

Data analysis & Results

The average data in total performance of the subjects were very close to the mean value.

When there is a problem in micro-motorics or unknown ethiology,

the problem has to be detected:

(next, the cases are explained in detail)

J.Kääminen p 10_19 04.04.2005

slide11

FDexterity

A surprise for the person himself

Mean values for corr. on XY

J.Kääminen p 11_19 04.04.2005

slide12

FDexterity

The effects of tremor and hand-eye coordination

J.Kääminen p 12_19 04.04.2005

slide13

Subject1:

Subject1 with simulation:

Subject 2:

Subject 3:

FDexterity

The second graph ε is quite sensitive than others.

J.Kääminen p 13_19 04.04.2005

slide14

FDexterity

Graph ε , Corr. on Y-axis, the subjects 1 & 7

Subject7:

Subject1:

J.Kääminen p 14_19 04.04.2005

slide15

FDexterity

Conclusions:

When there is a problem, there is a problem: Coordination problems show themselves clearly in the data even though they no problems had been previously detected by the person himself.

The variation in the total results is very small.

It would be relatively easy to figure out normal performance in the test proposed.

Age itself doesn’t have an impact on the results. The best results were collected with the second oldest subject. But the population sample under current investigation was restricted enough to make any final decision.The test might be applicable to people of various ages. Normal vision (or corrected with eyeglasses) is the only requirement.

J.Kääminen p 15_19 04.04.2005

slide16

FDexterity

Tremor affects the results slightly but detectably.

Simulated tremor had a visible effect on the subject 1 results (The subject 4 had exceptional problems in test setting with stylus during the inputs 10-20. If only successful recordings are considered in the study, his results are just the average and noticeably better than the subject 1 with tremor simulation.)

Still, there are some additional software options (zoom) which were not tested yet. That could increase a sensitivity of the method especially in detecting the effects of tremor.

J.Kääminen p 16_19 04.04.2005

slide17

FDexterity

Constraints:

The study was carried out in the field of human-computer-interaction.

Further research should be done under medical supervision.

Recordings among people suffering from various neurological diseases might be carried out to estimate the values of deviation from the normal.

J.Kääminen p 17_XX 04.04.2005

slide18

FDexterity

References:

Bain PG, Findley LJ, Atchison P, Behari M, Vidailhet M, Gresty M, Rothwell JC, Thompson PD, Marsden CD. Assessing tremor severity Journal of Neurology, Neurosurgery & Psychiatry.1993;56:868-73.

van Emmerik, R.E.A., Wagenaar, R.C.(1995) Tremor and symmetry properties in bimanual coordination in Parkinson’s disease. In: Bardy, B.G., Bootsma, R.J. & Guiard, Y. (eds.) Studies in Perception and Action. Lawrence Erlbaum, pp. 61-64.

Sharon Smaga, Tremor. American Family Physician, 68, 8, (Oct. 2003), 1542-1552.

Essential Tremor: A Practical Guide to Evaluation, Diagnosis, and Treatment, Vol. 19 No. 2 ISSN 0264-6404 May 2001. http://www.baylorcme.org/tremor/tremor.pdf

J.Kääminen p 18_19 04.04.2005

slide19

FDexterity

Click here to go to first slide

J.Kääminen p 19_19 04.04.2005

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