title: Classification of Movement of People with Parkinsons Disease Using Wearable Inertial Movement Units and Machine Learning.
abstract: In this work, inertial movement units were placed on people with Parkinsons disease (PwPD) who subsequently performed a standard test of walking endurance (six-minute walk test - 6MWT). Five devices were placed on each the limbs and small of the back. These devices captured the acceleration and rotational motion while the person walked as far as they can in six minutes. The wearable devices can objectively indicate the pattern and rhythmicity of limb and body movements. It is possible that this data, when subject to machine learning could provide additional objective measures that may support clinical observations related to the quality of movement. The aim of this work is two fold. First, to identify the most useful features of the captured signals; second, to identify the accuracy of using these features to predict the severity of PD as measured by standard clinical assessment.
authors.affiliation: The Australian E-Health Research Centre, CSIRO, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Ireland
authors.affiliation: School of Information Technology and Electrical Engineering, University of Queensland, Brisbane Australia.
authors.forename: Ziwei
authors.initials: Z
authors.lastname: Wang
authors.affiliation: School of Health and Rehabilitation Sciences, University of Queensland, Australia.
authors.forename: Robyn
authors.initials: R
authors.lastname: Lamont
authors.affiliation: Asia Pacific Center of Neuromodulation, Queensland Brain Institute, Australia.
authors.forename: Jacki
authors.initials: J
authors.lastname: Liddle
mesh_terms: D061725:Accelerometry; D000368:Aged; D005121:Extremities; D005260:Female; D006801:Humans; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D009068:Movement; D010300:Parkinson Disease / Q000175:diagnosis*; D012399:Rotation; D016138:Walking / Q000145:classification; D000076251:Wearable Electronic Devices