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IntelliRehabDS (IRDS)—A Dataset of Physical Rehabilitation Movements

Alina Miron, Noureddin Sadawi, Waidah Ismail, Hafez Hussain, Crina Groşan

2021Data60 citationsDOIOpen Access PDF

Abstract

In this article, we present a dataset that comprises different physical rehabilitation movements. The dataset was captured as part of a research project intended to provide automatic feedback on the execution of rehabilitation exercises, even in the absence of a physiotherapist. A Kinect motion sensor camera was used to record gestures. The dataset contains repetitions of nine gestures performed by 29 subjects, out of which 15 were patients and 14 were healthy controls. The data are presented in an easily accessible format, provided as 3D coordinates of 25 body joints along with the corresponding depth map for each frame. Each movement was annotated with the gesture type, the position of the person performing the gesture (sitting or standing) as well as a correctness label. The data are publicly available and were released with to provide a comprehensive dataset that can be used for assessing the performance of different patients while performing simple movements in a rehabilitation setting and for comparing these movements with a control group of healthy individuals.

Topics & Concepts

GestureRehabilitationComputer scienceCorrectnessSittingMovement (music)Frame (networking)Artificial intelligencePhysical medicine and rehabilitationMotion (physics)Computer visionMotion captureHuman–computer interactionPhysical therapyMedicineAlgorithmPhilosophyTelecommunicationsPathologyAestheticsStroke Rehabilitation and RecoveryHand Gesture Recognition SystemsHuman Pose and Action Recognition
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