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Classification of Tremor In Multiple Sclerosis Using Accelerometers and Standardized Tests

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00362257" target="_blank" >RIV/68407700:21230/22:00362257 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Classification of Tremor In Multiple Sclerosis Using Accelerometers and Standardized Tests

  • Original language description

    Tremor is an involuntary rhythmic oscillatory movement of a part of the body which belongs to one of the most disabling features of multiple sclerosis (MS). In clinical practice, the tremor is typically classified according to clinical scales. Unfortunately, this approach is almost subjective. There is a lack of objective, easy-to-use clinical classification. As is shown in the literature, the tremor can also be investigated by accelerometers and gyroscopes. This approach opens the possibilities for objective classification. This paper is focused on the classification of individuals as healthy/diseased from the point of multiple sclerosis. The tremor is classified by measuring postural tremor in upper limbs using accelerometers, both with open and closed eyes. The evaluation of the signal from the accelerometer is combined with an assessment of upper limb functionality using standardized tests – the Nine-Hole Peg Test and the Coin Rotation Task. The K-means and K-NN classifiers are applied to data to evaluate the tremor. On a sample of 15 people with multiple sclerosis and 18 people in the control group, a classification success of 82 % was achieved using the K-means algorithm for specific three parameters – Nine-Hole Peg Test results for both the left and right upper limb and a cumulative value of the PSD examination of tremor with an accelerometer measuring in a fixed band of 0–4 Hz on the right upper limb with closed eyes. The K-NN algorithm on such a small sample of data did not produce any conclusive results. The experiment and data acquisition were realized in accordance with ethical standards and the Helsinki Declaration and with the consent of the responsible ethical committee. The presented research is a part of a large project concerning the objectivization of multiple sclerosis diagnostics.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů