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Advanced Computing and Intelligent Technologies pp 17–32Cite as

Prognosis of Parkinson’s Malady—A Multimodal Approach

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 914)

Abstract

The increment in elderliness is directly proportional to the enhancement in Parkinson's disease patients. Lamentably, the authentic and prompt prognosis of PD plays a big challenge in emergent nations on the grounds of lack of resources and alertness. Moreover, the symptoms of PD patients are not identical nor do they all occur at the same stage of the disease. Thus, in our study, we have suggested a joint prototype by analyzing and conducting tests of three main symptoms, namely tremor analysis, dysphonia analysis and writing analysis test of PD occurring in the initiatory phase of the disease to predict the disease in the early stages and control it accordingly. This model can also prove to be a boon to patients living in areas, where qualified neurologists are not immediately accessible.

Keywords

  • Parkinson’s disease
  • Tremor
  • Dysphonia
  • Handwriting analysis
  • Machine learning
  • Telemonitoring

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Authors and Affiliations

  1. AKGEC, Ghaziabad, Uttar Pradesh, India

    Shanvi Sharma & Pratima Singh

Authors
  1. Shanvi Sharma
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  2. Pratima Singh
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Correspondence to Shanvi Sharma .

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Editors and Affiliations

  1. Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India

    Rabindra Nath Shaw

  2. Regional Campus Manipur, Indira Gandhi National Tribal University, Imphal, Manipur, India

    Sanjoy Das

  3. Department of Computer Science, University of Milan, Milan, Italy

    Vincenzo Piuri

  4. Department of Information Engineering and Mathematics, University of Siena, Siena, Italy

    Monica Bianchini

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Sharma, S., Singh, P. (2022). Prognosis of Parkinson’s Malady—A Multimodal Approach. In: Shaw, R.N., Das, S., Piuri, V., Bianchini, M. (eds) Advanced Computing and Intelligent Technologies. Lecture Notes in Electrical Engineering, vol 914. Springer, Singapore. https://doi.org/10.1007/978-981-19-2980-9_2

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  • DOI: https://doi.org/10.1007/978-981-19-2980-9_2

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