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Review

A Review of Data Gathering Methods for Evaluating Socially Assistive Systems

1
Department of Design, Shanghai Jiao Tong University, Shanghai 200240, China
2
Department of Industrial Design, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands
3
School of Design, Southern University of Science and Technology, Shenzhen 518055, China
4
School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
5
Department of Industrial Design, Nantong University, Nantong 226019, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2022, 22(1), 82; https://doi.org/10.3390/s22010082
Submission received: 20 November 2021 / Revised: 16 December 2021 / Accepted: 21 December 2021 / Published: 23 December 2021
(This article belongs to the Special Issue Recent Advances in Human-Computer Interaction)

Abstract

Social interactions significantly impact the quality of life for people with special needs (e.g., older adults with dementia and children with autism). They may suffer loneliness and social isolation more often than people without disabilities. There is a growing demand for technologies to satisfy the social needs of such user groups. However, evaluating these systems can be challenging due to the extra difficulty of gathering data from people with special needs (e.g., communication barriers involving older adults with dementia and children with autism). Thus, in this systematic review, we focus on studying data gathering methods for evaluating socially assistive systems (SAS). Six academic databases (i.e., Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore) were searched, covering articles published from January 2000 to July 2021. A total of 65 articles met the inclusion criteria for this systematic review. The results showed that existing SASs most often targeted people with visual impairments, older adults, and children with autism. For instance, a common type of SASs aimed to help blind people perceive social signals (e.g., facial expressions). SASs were most commonly assessed with interviews, questionnaires, and observation data. Around half of the interview studies only involved target users, while the other half also included secondary users or stakeholders. Questionnaires were mostly used with older adults and people with visual impairments to measure their social interaction, emotional state, and system usability. A great majority of observational studies were carried out with users in special age groups, especially older adults and children with autism. We thereby contribute an overview of how different data gathering methods were used with various target users of SASs. Relevant insights are extracted to inform future development and research.
Keywords: assistive technology; social interaction; data gathering methods; older adults; people with disabilities assistive technology; social interaction; data gathering methods; older adults; people with disabilities

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MDPI and ACS Style

Qiu, S.; An, P.; Kang, K.; Hu, J.; Han, T.; Rauterberg, M. A Review of Data Gathering Methods for Evaluating Socially Assistive Systems. Sensors 2022, 22, 82. https://doi.org/10.3390/s22010082

AMA Style

Qiu S, An P, Kang K, Hu J, Han T, Rauterberg M. A Review of Data Gathering Methods for Evaluating Socially Assistive Systems. Sensors. 2022; 22(1):82. https://doi.org/10.3390/s22010082

Chicago/Turabian Style

Qiu, Shi, Pengcheng An, Kai Kang, Jun Hu, Ting Han, and Matthias Rauterberg. 2022. "A Review of Data Gathering Methods for Evaluating Socially Assistive Systems" Sensors 22, no. 1: 82. https://doi.org/10.3390/s22010082

APA Style

Qiu, S., An, P., Kang, K., Hu, J., Han, T., & Rauterberg, M. (2022). A Review of Data Gathering Methods for Evaluating Socially Assistive Systems. Sensors, 22(1), 82. https://doi.org/10.3390/s22010082

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