Abstract
In this research, a machine learning approach has been used to solve one of the prominent problems in the healthcare field related to the neurological disorder. Tremor is the most common movement disorder that infects the upper or lower limbs or both extremities which are prevalent in old age population and is increasing at an unstoppable rate. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor. The tremor patients face enormous trouble in performing the daily activity, need the adequate diagnosis and all-time caretaking. In the clinics, the tremor assessment is manual which is a time taking and cumbersome procedure and also hard to classify tremor types.
A novel method for automatic and accurate classification of tremor has been designed and developed using machine learning methods so that adequate diagnosis can be provided to the correct patient.
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Ranjan, R., Palaniswami, M., Bhushan, B. (2020). A Machine Learning Approach for Classification of Tremor - A Neurological Movement Disorder. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_95
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DOI: https://doi.org/10.1007/978-3-030-29513-4_95
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