Interdisciplinary development of manual and automated product usability assessments for older adults with dementia: lessons learned

Abstract

The changes in cognitive abilities that accompany dementia can make it difficult to use everyday products that are required to complete activities of daily living. Products that are inherently more usable for people with dementia could facilitate independent activity completion, thus reducing the need for caregiver assistance. The objectives of this research were to: (1) gain an understanding of how water tap design impacted tap usability and (2) create an automated computerized tool that could assess tap usability. 27 older adults, who ranged from cognitively intact to advanced dementia, completed 1309 trials on five tap designs. Data were manually analyzed to investigate tap usability as well as used to develop an automated usability analysis tool. Researchers collaborated to modify existing techniques and to create novel ones to accomplish both goals. This paper presents lessons learned through the course of this research, which could be applicable in the development of other usability studies, automated vision-based assessments and the development of assistive technologies for cognitively impaired older adults. Collaborative interdisciplinary teamwork, which included older adult with dementia participants, was key to enabling innovative advances that achieved the projects' research goals.

Implications for Rehabilitation

• Products that are implicitly familiar and usable by older adults could foster independent activity completion, potentially reducing reliance on a caregiver.

• The computer-based automated tool can significantly reduce the time and effort required to perform product usability analysis, making this type of analysis more feasible.

• Interdisciplinary collaboration can result in a more holistic understanding of assistive technology research challenges and enable innovative solutions.

Keywords:

• Action identification
• automated video analysis
• dementia
• health informatics
• interdisciplinary collaboration
• non-invasive sensing and monitoring
• product usability

Acknowledgements

The authors thank the Harold and Grace Baker Centre for their support and participation and the Delta Tap Company for the donation of their tap to this research. We would also like to acknowledge and thank Kate Fenton, Tammy Craig, Jasper Snoek, Yulia Eskin, David Giesbrecht, Valerie Leuty and Ellen Maki for their contributions to this research.

Declaration of interest

This project was funded by NIDRR through the RERC on Universal Design and the Built Environment, a partnership between the Center for Inclusive Design and Environmental Access (IDeA) and the Ontario Rehabilitation Technology Consortium (ORTC). This paper does not necessarily represent the policy of NIDRR and readers should not assume any endorsement of its contents by the US Federal government.

Notes

¹ A classifier is the act of automated computerized identification and categorisation of data.

² Observer XT is a commercially available tool developed by Noldus Information Technology (www.noldus.com).