"Wearable and wireless accelerometer systems for monitoring Parkinson’s disease patients—A perspective review"
written by Robert LeMoyne,
published by Advances in Parkinson's Disease, Vol.2 No.4, 2013
has been cited by the following article(s):
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[9] * Northern Arizona University, Flagstaff, AZ, United States,† Independent, Pittsburgh, PA, United States
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[17] Development of an Assessment Method of Forearm Pronation/Supination Motor Function based on Mobile Phone Accelerometer Data for an Early Diagnosis of Parkinson’s Disease
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[18] Development of a MEMS Accelerometer based Hand Tremor Stabilization Platform
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[19] Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by multilayer perceptron neural network
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[20] A Low Cost Wireless Sensor Interface for the Quantification of Tremor in Parkinson's Disease
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[21] Design of a smart pressure signal based biometric system for aircraft cockpit security
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[22] Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning
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[23] 3D akcelerometr/gyroskop pro detekci pohybu osob
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[24] The method for processing electromyography and inertial sensors supporting chosen set of neurological symptoms for clinical trials support and treatment assessment
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