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A Multi-modal Tool Suite for Parkinson’s Disease Evaluation and Grading

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Neural Approaches to Dynamics of Signal Exchanges

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 151))

Abstract

The traditional diagnosis of Parkinson’s disease (PD) aims to assess several clinical manifestations, and it is commonly based on medical observations. However, an overall evaluation is extremely difficult due to the large variety of symptoms that affect PD patients. Furthermore, the traditional PD assessment is based on visual subjective observation of different motor tasks. For this reasons, an automatic system could be able to automatically assess and rate the PD and objectively evaluate the performed motor tasks. Such system could then support medical specialists in the assessment and rating of PD patients in a real clinical scenario. In this work, we developed multi-modal tool suite able to extract and process meaningful features from different motor tasks by means of two main experimental set-ups. In detail, we acquired and evaluated the motor performance acquired during the finger tapping, the foot tapping and the hand writing exercises. Several sets of features have been extracted from the acquired signals and used to both successfully classify a subject as PD patient or healthy subject, and rate the disease among PD patients.

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Acknowledgements

This work has been supported by the Italian project RoboVir (within the BRIC INAIL-2017 programme).

Author information

Authors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechcnic University of Bari, Bari, Italy

    Giacomo Donato Cascarano, Antonio Brunetti, Domenico Buongiorno, Claudio Loconsole & Vitoantonio Bevilacqua

  2. Department of Mechanics, Mathematics and Management Engineering, Polytechnic University of Bari, Bari, Italy

    Gianpaolo Francesco Trotta

  3. Institute of Clinical Physiology, National Research Council, Pisa, Italy

    Ilaria Bortone

Authors
  1. Giacomo Donato Cascarano
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  2. Antonio Brunetti
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  3. Domenico Buongiorno
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  4. Gianpaolo Francesco Trotta
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  5. Claudio Loconsole
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  6. Ilaria Bortone
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  7. Vitoantonio Bevilacqua
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Correspondence to Vitoantonio Bevilacqua .

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Editors and Affiliations

  1. Department of Psychology, University of Campania Luigi Vanvitelli, Caserta, Italy

    Anna Esposito

  2. Tecnocampus, Mataró, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environment, Energy and Materials Engineering, Mediterranea University of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Turin, Italy

    Eros Pasero

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Cascarano, G.D. et al. (2020). A Multi-modal Tool Suite for Parkinson’s Disease Evaluation and Grading. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore. https://doi.org/10.1007/978-981-13-8950-4_24

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