Abstract
The classifier selection problem in Assistive Technology Adoption refers to selecting the classification algorithms that have the best performance in predicting the adoption of technology, and is often addressed through measuring different single performance indicators. Satisfactory classifier selection can help in reducing time and costs involved in the technology adoption process. As there are multiple criteria from different domains and several candidate classification algorithms, the classifier selection process is now a problem that can be addressed using Multiple-Criteria Decision-Making (MCDM) methods. This paper proposes a novel approach to address the classifier selection problem by integrating Intuitionistic Fuzzy Sets (IFS), Decision Making Trial and Evaluation Laboratory (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The step-by-step procedure behind this application is as follows. First, IF-DEMATEL was used for estimating the criteria and sub-criteria weights considering uncertainty. This method was also employed to evaluate the interrelations among classifier selection criteria. Finally, a modified TOPSIS was applied to generate an overall suitability index per classifier so that the most effective ones can be selected. The proposed approach was validated using a real-world case study concerning the adoption of a mobile-based reminding solution by People with Dementia (PwD). The outputs allow public health managers to accurately identify whether PwD can adopt an assistive technology which results in (i) reduced cost overruns due to wrong classification, (ii) improved quality of life of adopters, and (iii) rapid deployment of intervention alternatives for non-adopters.
Highlights
Introduction published maps and institutional affilAs life expectancy has been increasing globally due to medical advances and improvements in the quality of life of people in later stages of life, age-related diseases such as dementia have been increasing
People with Dementia (PwD) can improve their quality of life through the support of assistive technologies, enabling them to perform their daily activities in a more natural manner with a greater degree of autonomy in their decisions
Different classifiers have been proposed to address this necessity, the decision about which algorithm should be used goes beyond performance metrics and involves aspects characterizing the healthcare sector and implementation context
Summary
As life expectancy has been increasing globally due to medical advances and improvements in the quality of life of people in later stages of life, age-related diseases such as dementia have been increasing. Technology solutions have been used to improve the quality of life of PwD, to support the work of carers, and to provide more personalized types of treatment. Assistive Technology-based Solutions (ATS) [3] have been commonly prescribed as a form of non-pharmacological treatment to PwD to help them complete everyday activities whilst maintaining a level of independence, yielding health and social benefits for them. Some of the areas in which ATS provide support include memory, mobility, indoor and outdoor safety, independence, and socializing.
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