Fig 1.
(A) Year-wise number of mHealth apps uploaded in the google play, and (B) Smart phone penetration in the last five years, and (C) Pie chart shows various categories of apps in percentage.
Table 1.
Various mHealth app rating scale.
Fig 2.
Factors affecting mobile app review.
Fig 3.
Relationship between input parameters and model parameters.
Fig 4.
Flow diagram for opinion mining.
Fig 5.
Word cloud for Polarity of words found in the comments of selected apps– (A) positive polarity words, and (B) negative polarity words.
Fig 6.
Calculation of clinical approval value.
Fig 7.
Fuzzy logic based fusion technique which combines the knowledge extracted from the users’ star rating, users’ text review, clinical approval, UI design, functionality and security & privacy and thereby generates a score.
Fig 8.
Input membership and relation between the input-output in the rule base system.
Fig 9.
Case study design and app selection flowchart.
Fig 10.
Correlation matrix illustrating the coefficient among factors considered for the assessment of the app scale.
Fig 11.
Comparison of traditional mobile app ratings and fuzzy based app ratings.
(A) Average scores with respect to each parameter for all the selected 43 apps, (B) Box plot for the average rated value for traditional, fuzzy based ratings, as well as ratings based on expert opinion, (C) app scores for traditional and fuzzy based ratings for all the selected apps, and (D) Comparison of various app scales in terms of ICC.