Smart technologies for assisting the life quality of persons in a mobile environment: a review

Chen, Tin-Chih; Chiu, Min-Chi

doi:10.1007/s12652-016-0396-x

“…756 , 6 . 182 ) (23) which revealed that there was some consensus among experts since CR could be less than 0.1. However, the upper bound of the fuzzy consistency index was high, showing that there was considerable uncertainty behind such a judgement.…”

Section: An Experimentsmentioning

confidence: 99%

“…They concluded from a questionnaire survey that perceived service availability (PSA) and personal innovativeness in information technology (PIIT) were the most critical factors. Other researchers such as Demirkan [22] , Chen & Chiu [23] , and Chen [17] have similarly encouraged using smart technology applications for mobile environments, all of which has been summarized in Table 2 .…”

Section: Classification Of Smart Technologiesmentioning

confidence: 99%

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Chen

¹

2020

Health Policy and Technology

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a b s t r a c tSmart technologies present numerous opportunities for enhancing mobile health care. However, some concerns regarding the viability of smart technology applications must be addressed. This study investigated these concerns by reviewing the current practices of smart technology applications to mobile health care. As a result, five factors critical to the applicability of a smart technology to mobile health care are identified, and the fuzzy geometric mean-fuzzy analytic hierarchy process (FGM-FAHP) approach is proposed to assess the relative importance levels of the identified factors. The experimental results showed that the three most critical factors identified include: (a) the relaxation of the related medical laws; (b) unobtrusiveness; and (c) the precise need and situation of a user. Accordingly, approximately 44%, 26%, and 15% of the budget should be allocated to the realization of the three critical factors, respectively. In addition, the challenges involved and opportunities for enhancing the effectiveness of existing applications are discussed.

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“…• The derived fuzzy weights could be used to guide the government of a region in allocating its budget, as shown in Fig. 182 ) (23) which revealed that there was some consensus among experts since CR could be less than 0.1. It is noted that the values shown in this figure are flexible, since all weights are given in TFNs.…”

Section: An Experimentsmentioning

confidence: 99%

Evaluating the sustainability of a smart technology application to mobile health care: the FGM–ACO–FWA approach

Chen

¹

2019

Complex Intell. Syst.

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a b s t r a c tSmart technologies present numerous opportunities for enhancing mobile health care. However, some concerns regarding the viability of smart technology applications must be addressed. This study investigated these concerns by reviewing the current practices of smart technology applications to mobile health care. As a result, five factors critical to the applicability of a smart technology to mobile health care are identified, and the fuzzy geometric mean-fuzzy analytic hierarchy process (FGM-FAHP) approach is proposed to assess the relative importance levels of the identified factors. The experimental results showed that the three most critical factors identified include: (a) the relaxation of the related medical laws; (b) unobtrusiveness; and (c) the precise need and situation of a user. Accordingly, approximately 44%, 26%, and 15% of the budget should be allocated to the realization of the three critical factors, respectively. In addition, the challenges involved and opportunities for enhancing the effectiveness of existing applications are discussed.

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“…The suitabilities of eleven smart health practices were assessed. To this end, the performances of these smart health practices in optimizing the five criterion were evaluated by the same decision makers using the following linguistic terms [3]:…”

Section: Applicationmentioning

confidence: 99%

“…As smart health practices are becoming more and more sophisticated, how to recommend suitable smart health practices to a target population becomes a challenging task. For example, Chen and Chiu [3] reviewed the literature and concluded that the most effective smart health practices adopted smart mobile services, smart phones, smart glasses/spectacles/contact lens, and smart surveillance cameras. Haymes et al [4] applied behavior analysis to find out factors that contributed to the success of smart health practices for individuals with intellectual disabilities.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Collaborative Approach for Evaluating the Suitability of a Smart Health Practice

Chen

¹

,

Wang

²

,

Lin

³

et al. 2019

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A fuzzy collaborative approach is proposed in this study to assess the suitability of a smart health practice, which is a challenging task, as the participating decision makers may not reach a consensus. In the fuzzy collaborative approach, each decision maker first applies the alpha-cut operations method to derive the fuzzy weights of the criteria. Then, fuzzy intersection is applied to aggregate the fuzzy weights derived by all decision makers to measure the prior consensus among them. The fuzzy intersection results are then presented to the decision makers so that they can subjectively modify the pairwise comparison results to bring them closer to the fuzzy intersection results. Thereafter, the consensus among decision makers is again measured. The collaboration process will stop when no more modifications are made by any decision maker. Finally, the fuzzy weighted mean-centroid defuzzification method is applied to assess the suitability of a smart health practice. The fuzzy collaborative approach and some existing methods have been applied to assess the suitabilities of eleven smart health practices for a comparison. Among the compared practices, only the fuzzy collaborative approach could guarantee the existence of a full consensus among decision makers after the collaboration process, i.e., that the assessment results were acceptable to all decision makers.

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Smart technologies for assisting the life quality of persons in a mobile environment: a review

Cited by 42 publications

References 28 publications

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Assessing factors critical to smart technology applications to mobile health care − the fgm-fahp approach

Evaluating the sustainability of a smart technology application to mobile health care: the FGM–ACO–FWA approach

A Fuzzy Collaborative Approach for Evaluating the Suitability of a Smart Health Practice

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