Biomechanical parameter assessment for classification of Parkinson’s disease on clinical scale

Inertial Measurement Unit-Based Wearable Computers for Assisted Living Applications: A signal processing perspective

(2016) Terrell R. Bennett et al.   IEEE SIGNAL PROCESSING MAGAZINE

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures

(2016) Ken J. Kubota et al.   MOVEMENT DISORDERS

Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study

(2015) S. Arora et al.   PARKINSONISM & RELATED DISORDERS

Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway

(2014) L.F. Yeung et al.   GAIT & POSTURE

A computer vision framework for finger-tapping evaluation in Parkinson's disease

(2013) Taha Khan et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Automatic classification and prediction models for early Parkinson’s disease diagnosis from SPECT imaging

(2013) R. Prashanth et al.   EXPERT SYSTEMS WITH APPLICATIONS

New machine-learning algorithms for prediction of Parkinson's disease

(2012) Indrajit Mandal et al.   INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE

Comparative study on classification performance between support vector machine and logistic regression

(2012) Abdallah Bashir Musa   International Journal of Machine Learning and Cybernetics

Hilbert–Huang-Based Tremor Removal to Assess Postural Properties From Accelerometers

(2011) Sabato Mellone et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Technology and Innovative Services

(2011) G Turchetti et al.   IEEE Pulse

Monitoring Motor Fluctuations in Patients With Parkinson's Disease Using Wearable Sensors

(2009) S. Patel et al.   IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE

Comparison among probabilistic neural network, support vector machine and logistic regression for evaluating the effect of subthalamic stimulation in Parkinson disease on ground reaction force during gait

(2009) A.M.S. Muniz et al.   JOURNAL OF BIOMECHANICS

Feature selection using localized generalization error for supervised classification problems using RBFNN

(2008) Wing W.Y. Ng et al.   PATTERN RECOGNITION