IntelliRehabDS (IRDS)—A Dataset of Physical Rehabilitation Movements

TY - JOUR

T1 - IntelliRehabDS (IRDS)—A Dataset of Physical Rehabilitation Movements

AU - Grosan, Crina

N1 - Funding Information: Funding: This research was funded by Innovate UK grant number 102719 and MIGHT (Malaysia Industry-Government for High Technology), application No (62873-455315). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/5

Y1 - 2021/5

N2 - In this article, we present a dataset that comprises different physical rehabilitation move-ments. 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.

AB - In this article, we present a dataset that comprises different physical rehabilitation move-ments. 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.

UR - http://www.scopus.com/inward/record.url?scp=85106930585&partnerID=8YFLogxK

U2 - 10.3390/data6050046

DO - 10.3390/data6050046

M3 - Article

SN - 2306-5729

VL - 6

JO - Data

JF - Data

IS - 5

M1 - 46

ER -