ABOUT THIS EPISODE
A five-sensor IMU-based Parkinson's disease patient and control dataset including three activities of daily living, by Joseph Russell, Jemma Inches, Camille B. Carroll and Jeroen H.M. Bergmann, narrated in full by Joseph Russell, as published on 14th August 2023 on Dryad. Full article available at: https://doi.org/10.5061/dryad.fbg79cp1d
This video is part of an initiative by SDU's Biomedical Engineering Centre to improve the accessibility of scientific papers with human-narrated article readings. The text is read out in full in the same manner as a non-fiction unabridged audiobook, with the article displayed page-by-page on-screen for those wishing to see figures, equations and references. Parkinson’s disease is an often-debilitating progressive neurological condition leading to loss of motor control. This dataset contains kinematic sensor data from two groups: one containing 15 patients with Parkinson’s disease, and a control group of 19 participants without any known neurological condition. Participant ages ranged from 40–85, 21 were male, and 13 were female. The participants wore five 9-axis Inertial Measurement Units (IMUs) – one on each upper arm, each lower arm, and on their head. They were asked to perform a calibration pose, followed by three activities: making toast, putting on a cardigan, and unlocking and opening a door, with each activity repeated three times. The IMUs recorded time-series acceleration and orientation data from the moment where the participant was instructed to begin the activity (inception of the idea to act), through to the activity’s completion. This dataset is planned for use in intent-sensing studies for assistive device control but is also applicable for activity recognition. © 2023 by the authors.
