Titlebook: Deep Learning in Smart eHealth Systems; Evaluation Leveragin Asma Channa,Nirvana Popescu Book 2024 The Editor(s) (if applicable) and The Au

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Integrity and normality. The singular locus,s. This chapter delves into the multifaceted diagnostic challenges associated with PD, including the heterogeneous progression of the disease, patient-reported biases, and the influence of medication. To evaluate disease severity, various rating scales like UPDRS and the Hoehn and Yahr scale are emp

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Determinanten der DemokratiezufriedenheitParkinson’s Disease (PD). These devices predominantly rely on inertial sensors and computational algorithms, offering promising advancements. However, they also introduce fresh challenges, including concerns related to security, privacy, connectivity, and power efficiency. From a clinical perspectiv

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Einleitung: Abgrenzung und Systematikd assessment of Parkinson’s Disease (PD) severity through remote and continuous monitoring. The chapter is divided into two sections, outlining the methodology and results of the study. In the first section, an A-WEAR bracelet is employed for the objective assessment of tremor and bradykinesia in PD

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https://doi.org/10.1007/978-3-531-19729-6, like levodopa, wear off, resulting in the recurrence of PD symptoms. The methodology harnesses features derived from heart rate, stress levels, sleep patterns, and step counts, combined with machine learning techniques, to forecast wearing-off in patients. Relevant features encompass mean conditio

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https://doi.org/10.1007/978-3-642-53065-4formative therapeutic advancements that have converted PD from a life-threatening condition into a manageable disease. Nevertheless, the intricate and progressive nature of PD continues to pose challenges for its effective management and the enhancement of patients’ quality of life. The chapter acce

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https://doi.org/10.1007/978-3-031-45003-7A-WEAR Bracelet; Cloud Platform; Continuous Wavelet Transform; Convolutional Neural Network; Deep Learni

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