Data underlying the project: Technology in Motion – Augmented Reality for Upper Extremity assessment (TIM-AR-UE)

  • Paulina J.M. Bank (Creator)
  • Marina Cidota (Creator)
  • P.W. Ouwehand (Creator)
  • S.G. (Stephan) Lukosch (Creator)



Data was collected within the Technology in Motion project (protocol registered by CCMO as NL54281.058.15), aimed at developing innovative techniques to characterize motor function in patients with neurological disorders. Augmented reality (AR) systems with contactless tracking of the hand and upper body offer opportunities for objective quantification of motor (dys)function in a challenging, engaging and patient-tailored environment. We therefore explored the potential of AR for evaluating 1) speed and goal-directedness of movements within the individually determined interaction space; 2) adaptation of hand opening to objects of different sizes; and 3) obstacle avoidance in healthy individuals (N=10) and two highly prevalent neurological conditions (N=10 patients with Parkinson’s Disease [PD] and N=10 stroke patients).
This dataset contains data from 10 PD patients, 10 stroke patients and 10 age- and sex-matched controls. For each participant we provide the raw data (recorded during the 3 AR games), consisting of i) LeapMotion data 3D-coordinates of hand ‘joints’ (e.g., hand palm and finger tips) at a sampling rate of 60 frames per second (obtained by means of Leap Motion sensor and Leap Motion Orion Beta software development kit [SDK]); ii) 3D-coordinates of body points (e.g., wrist, elbow and shoulder) at a sampling rate of 30 frames per second (obtained by means of KinectTM v2 sensor and Kinect for Windows SDK version 2.0); and iii) game-specific parameters (e.g. positions of virtual objects and timestamps of events). We additionally provide an SPSS file and a csv-file with general participant characteristics, disease-specific clinical characteristics, scores on user-experience questionnaires (individual items and total scores) and outcome parameters calculated from the raw data for each of the AR games (e.g. time per object, movement speed, success rate).
A more detailed description can be found in the documentation and the associated publication.
Date made available17 Oct 2018
PublisherTU Delft - 4TU.ResearchData
Date of data productionJun 2017 - Jul 2018
Geographical coverageLeiden University Medical Center, The Netherlands

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