Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor
The ever-growing and widespread use of touch, face, full-body, and 3D mid-air gesture recognition sensors in domestic and industrial settings is serving to highlight whether interactive gestures are sufficiently inclusive, and whether or not they can be executed by all users. The purpose of this stu...
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doaj-c306a670235c44aaac4a87f019d7cc112020-11-25T02:54:40ZengMDPI AGSensors1424-82202020-07-01203930393010.3390/s20143930Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect SensorMarta Sylvia Del Rio Guerra0Jorge Martin-Gutierrez1Department of Computer Science, Universidad de Monterrey, Nuevo León 66238, MexicoDepartment of Techniques and Projects in Engineering and Architecture, Universidad de La Laguna, 38071 Tenerife, SpainThe ever-growing and widespread use of touch, face, full-body, and 3D mid-air gesture recognition sensors in domestic and industrial settings is serving to highlight whether interactive gestures are sufficiently inclusive, and whether or not they can be executed by all users. The purpose of this study was to analyze full-body gestures from the point of view of user experience using the Microsoft Kinect sensor, to identify which gestures are easy for individuals living with Down syndrome. With this information, app developers can satisfy Design for All (DfA) requirements by selecting suitable gestures from existing lists of gesture sets. A set of twenty full-body gestures were analyzed in this study; to do so, the research team developed an application to measure the success/failure rates and execution times of each gesture. The results show that the failure rate for gesture execution is greater than the success rate, and that there is no difference between male and female participants in terms of execution times or the successful execution of gestures. Through this study, we conclude that, in general, people living with Down syndrome are not able to perform certain full-body gestures correctly. This is a direct consequence of limitations resulting from characteristic physical and motor impairments. As a consequence, the Microsoft Kinect sensor cannot identify the gestures. It is important to remember this fact when developing gesture-based on Human Computer Interaction (HCI) applications that use the Kinect sensor as an input device when the apps are going to be used by people who have such disabilities.https://www.mdpi.com/1424-8220/20/14/3930Microsoft Kinectsensorcorporal gesturesfull-body gesturesuser interfaceuser experience |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marta Sylvia Del Rio Guerra Jorge Martin-Gutierrez |
spellingShingle |
Marta Sylvia Del Rio Guerra Jorge Martin-Gutierrez Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor Sensors Microsoft Kinect sensor corporal gestures full-body gestures user interface user experience |
author_facet |
Marta Sylvia Del Rio Guerra Jorge Martin-Gutierrez |
author_sort |
Marta Sylvia Del Rio Guerra |
title |
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor |
title_short |
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor |
title_full |
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor |
title_fullStr |
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor |
title_full_unstemmed |
Evaluation of Full-Body Gestures Performed by Individuals with Down Syndrome: Proposal for Designing User Interfaces for All Based on Kinect Sensor |
title_sort |
evaluation of full-body gestures performed by individuals with down syndrome: proposal for designing user interfaces for all based on kinect sensor |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-07-01 |
description |
The ever-growing and widespread use of touch, face, full-body, and 3D mid-air gesture recognition sensors in domestic and industrial settings is serving to highlight whether interactive gestures are sufficiently inclusive, and whether or not they can be executed by all users. The purpose of this study was to analyze full-body gestures from the point of view of user experience using the Microsoft Kinect sensor, to identify which gestures are easy for individuals living with Down syndrome. With this information, app developers can satisfy Design for All (DfA) requirements by selecting suitable gestures from existing lists of gesture sets. A set of twenty full-body gestures were analyzed in this study; to do so, the research team developed an application to measure the success/failure rates and execution times of each gesture. The results show that the failure rate for gesture execution is greater than the success rate, and that there is no difference between male and female participants in terms of execution times or the successful execution of gestures. Through this study, we conclude that, in general, people living with Down syndrome are not able to perform certain full-body gestures correctly. This is a direct consequence of limitations resulting from characteristic physical and motor impairments. As a consequence, the Microsoft Kinect sensor cannot identify the gestures. It is important to remember this fact when developing gesture-based on Human Computer Interaction (HCI) applications that use the Kinect sensor as an input device when the apps are going to be used by people who have such disabilities. |
topic |
Microsoft Kinect sensor corporal gestures full-body gestures user interface user experience |
url |
https://www.mdpi.com/1424-8220/20/14/3930 |
work_keys_str_mv |
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