Advances in Parkinson's Disease

Advances in Parkinson's Disease

ISSN Print: 2169-9712
ISSN Online: 2169-9720
www.scirp.org/journal/apd
E-mail: apd@scirp.org
"Wireless accelerometer configuration for monitoring Parkinson’s disease hand tremor"
written by Robert LeMoyne, Timothy Mastroianni, Warren Grundfest,
published by Advances in Parkinson's Disease, Vol.2 No.2, 2013
has been cited by the following article(s):
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[1] Kinetic tremor analysis using wearable sensors and fuzzy inference systems in Parkinson's disease
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[2] Feasibility of Magnetic Resonance–Compatible Accelerometers to Monitor Tremor Fluctuations During Magnetic Resonance–Guided Focused Ultrasound …
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[3] Feasibility of virtual low-cost quantitative continuous measurement of movements in the extremities of people with Parkinson's disease
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[4] Parkinson's Disease Action Tremor Detection with Supervised-Leaning Models
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[5] Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants' Well-being: Ecological Momentary Assessment
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[6] Classification of extremity movements by visual observation of signals and their transforms
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[7] Internet de las cosas en el ámbito de la atención médica: tendencias y desafíos
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[8] Monitorización de la enfermidad de Parkinson mediante sensores vestibles
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[9] An Evolutionary Perspective for Network Centric Therapy through Wearable and Wireless Systems for Reflex, Gait, and Movement Disorder Assessment with …
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[10] TremorSense: Tremor Detection for Parkinson's Disease Using Convolutional Neural Network
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[11] Applied Software Development with Python & Machine Learning by Wearable & Wireless Systems for Movement Disorder Treatment via Deep Brain …
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[12] Parametric evaluation of deep brain stimulation parameter configurations for Parkinson's disease using a conformal wearable and wireless inertial sensor system and …
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[13] Detection of Parkinson's Disease through Smell Signatures
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[14] Application of deep learning to distinguish multiple deep brain stimulation parameter configurations for the treatment of Parkinson's disease
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[15] Traditional Ordinal Strategies for Establishing the Severity and Status of Movement Disorders, Such as Parkinson's Disease and Essential Tremor
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[16] A low-cost quantitative continuous measurement of movements in the extremities of people with Parkinson's disease
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[17] Movement Disorders: Parkinson's Disease and Essential Tremor—A General Perspective
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[18] Preliminary Wearable and Locally Wireless Systems for Quantification of Parkinson's Disease and Essential Tremor Characteristics
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[19] Wearable and Wireless Systems for Movement Disorder Evaluation and Deep Brain Stimulation Systems
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[20] Evaluation of Machine Learning Algorithms for Classifying Deep Brain Stimulation Respective of 'On'and 'Off'Status
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[21] Cognitive health care system and its application in pill‐rolling assessment
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[22] Machine learning-based motor assessment of Parkinson's disease using postural sway, gait and lifestyle features on crowdsourced smartphone data
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[23] The Evaluation of the Tremor: Signal Database of Healthy Control Subjects
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[24] Big data in Parkinson's disease: using smartphones to remotely detect longitudinal disease phenotypes
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[25] Probabilistic Methods for Analyzing and Measuring Tremor in Humans
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[26] Procesamiento y análisis de señales biomecánicas adquiridas por redes de sensores
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[27] Dispositivo electrónico para la adquisición de señales asociadas a la enfermedad de parkinson (EP)
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[28] Trends and New Advances on Wearable and Mobile Technologies for Parkinson's Disease Monitoring and Assessment of Motor Symptoms: How New Technologies …
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[29] Parkinson's disease prediction based on hand tremor analysis
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[30] Algoritmo de detección de caídas en un sistema embebido
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[31] Sistema de Adquisición y Caracterización de Temblor de la Enfermedad de Parkinson en Extremidades Superiores Mediante Acelerometría
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[32] Evaluación del Movimiento a través de Acelerometría en Pacientes con Enfermedad de Parkinson
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[33] Smartphone and portable media device: a novel pathway toward the diagnostic characterization of human movement
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[34] Development of an assessment method of forearm pronation/supination motor function based on mobile phone accelerometer data for an early diagnosis of …
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[35] A holistic approach to assess the feasability of telehealth for Parkinson's disease management
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[36] Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by …
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[37] Differential analysis of muscle fatigue induced elbow and wrist tremor in controlled laparoscopic manoeuvring
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[38] Telemedicine Perspectives for Wearable and Wireless Applications Serving the Domain of Neurorehabilitation and Movement Disorder Treatment
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[39] On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists
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[40] 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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[41] Development of a MEMS Accelerometer based Hand Tremor Stabilization Platform
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[42] Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by …
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[43] Trends and New Advances on Wearable and Mobile Technologies for Parkinson's Disease Monitoring and Assessment of Motor Symptoms: How New Technologies …
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[44] A compact monitoring system for patients affected by neurodegenerative diseases
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[45] Development of MEMS Accelerometer based Hand Tremor Stabilization Platform
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[46] Development of an acquisition and visualization of forearm tremors and pronation/supination motor activities in a smartphone based environment for an early …
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[47] Use of smartphones and portable media devices for quantifying human movement characteristics of gait, tendon reflex response, and Parkinson's disease hand tremor
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[48] Quantitative assessment of forearm pronation/supination motor functions using a smartphone accelerometer for an early diagnosis of Parkinson's
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[49] Evaluating a Miniature Multisensor Biosignal Recorder for Unsupervised Parkinson's Disease Monitoring
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[50] Development of an acquisition and visualization of forearm tremors and pronation/supination motor activities in a smartphone based environment for an early diagnosis of Parkinson’s disease
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[51] Technologies for Assessment of Motor Disorders in Parkinson's Disease: A Review
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[52] A Smartphone-based Tool for Assessing Parkinsonian Hand Tremor
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[53] Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning
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[54] Design and realization of measuring device for tremor evaluation
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[55] Wearable multimodal sensors for evaluation of patients with Parkinson disease
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[56] Development of an acquisition and visualization of forearm tremors and pronation/supination motor activities in a smartphone based environment for an …
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[57] A literature review on the vehicle routing problem with multiple depots
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[58] Development of an intelligent exercise platform for rehabilitation in Parkinson's disease
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[59] Smartphone-based Evaluation of Movement Disorders: Quantitative Measurements vs Clinical Assessment Scores
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[60] Monitoring of rehabilitation process via gyro and accelerometer sensor
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[61] Smartphone-based evaluation of parkinsonian hand tremor: Quantitative measurements vs clinical assessment scores
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[62] The survey and analysis of sportsâ   influence on teenagersâ   bone mineral density and bone metabolism
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[63] Miniature multisensor biosignal data recorder and its evaluation for unsupervised Parkinson's disease data collection
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[64] Exploitation of accelerometer for rehabilitation process
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[65] Smartphone-based valuation of Parkinsonian and Tremor uantitati easurements vs linical ssessment Scores
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