Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment
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...Also, [7] applies a CNN to the classication of bradykinesia present and absent states based on the wearable sensor data collected during several motor tasks....
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...…tapping) for upper limb motion analysis (Fukawa et al., 2007; Okuno et al., 2007; Patel et al., 2009; Yokoe et al., 2009; Hoffman andMcNames, 2011; Cavallo et al., 2013; Robles-García et al., 2013; Jia et al., 2014; Delrobaei et al., 2016; Djurić-Jovičić et al., 2016; Eskofier et al., 2016)....
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...Alternatively, a recent work proposed the use of deep learning as a promising method to analyse wearable sensor data in place of machine learning approaches (Eskofier et al., 2016)....
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...Also, Eskofier et al. (2016) performed an assessment of bradykinesia, but they introduced the use of deep learning instead of machine learning techniques as a promising method to analyse wearable sensor data....
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...For the minimization, we employed Adam [25], a gradient-based optimizer for stochastic objective functions. an optimization algorithm for stochastic loss functions....
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...For the minimization, we employed Adam [25], a gradient-based optimizer for stochastic objective functions....
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...The Adam algorithm was used in the configuration recommended by Kingma & Ba (learning rate 10-3, β1 = 0.9, β2 = 0.999, ε = 10-8) [25]....
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...6), which is a collection of ML algorithms for data mining tasks [20]....
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