Critical Success Factors of Analysing User Emotions to Improve the Usability of Systems

Wattearachchi, Wasura D.; Hettiarachchi, Enosha; Hewagamage, K. P.

doi:10.1109/ubi-media.2019.00026

Cited by 4 publications

(4 citation statements)

References 16 publications

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“…Moreover, according to the best of our knowledge, no application addresses all the features stated in Table 2. Nevertheless, each has its benefits as reviewed in [4]. Incorporating all of these features paved the path to finding a way to build an optimal model for decision-making to perform affective interactions by considering user emotions based on the context.…”

Section: Applicationsmentioning

confidence: 99%

“…After calculating the Frequent Probabilities for each function, those were added to the corresponding Preference Tree probabilities and were averaged using (4) where Pnew is the new probability of the chosen function, Pfrequent is the frequent probability of the chosen function calculated using (3) and Pcurrent_chosen is the current probability of the chosen function from the Preference Tree. Pnew = {(Pfrequent + Pcurrent_chosen)/2} x 100%.…”

Section: Prototypementioning

confidence: 99%

“…As explained in "Affective Computing" [3], emotions can be considered a factor to be used when designing a usable system [4]. The intelligence from emotions was used when designing intelligent robots [5], user interfaces [6], and appliances for households [7].…”

Section: Introductionmentioning

confidence: 99%

“…To facilitate further improvement, models could be created to gather user data and emotions which could then be stored in a profile. It can later be used to predict the most affective action to be performed by the system based on the context data and also to provide affective feedback [4]. Furthermore, when analysing the HCI research that has been carried out over the past 60 years [16], it can be seen that developing context-aware systems has become a trend since it is highly needful.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Emotional Keyboard: To Provide Adaptive Functionalities Based on the Current User Emotion and the Context

Wattearachchi¹,

Hewagamage²,

Hettiarachchi³

2022

IxD&A

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Improving the User Experience (UX) of mobile devices is of vital importance due to the advent of emerging technologies and the prevalence of using mobile devices. This research aims to develop a model for a mobile device that can suggest adaptive functionalities, based on the current user emotion and the context by changing the user’s negative emotions (sadness and anger) into positive ones. As a proof of concept, a keyboard named “Emotional Keyboard” was developed through five prototypes iteratively using Evolutionary Prototyping. Action Research was adopted as the methodology along with User-Centered Design (UCD) which further included two user surveys. The first three prototypes were implemented to decide the most optimal perception from facial expressions and text analytics. Subsequent prototypes provided affective functions to the user such as listening to music, playing a game, chat with friends, based on the detected negative emotion and the context. The evaluation of each of the prototypes was performed iteratively with user participation. The final (fifth) prototype evaluation was done in two phases, an individual analysis (to measure the performance of each user separately), and an overall analysis (a general analysis that averaged all the results from individual analysis and measured the performance of the overall model). Results of both analyses showed that eventually the Emotional Keyboard was able to predict the adaptive functions correctly to the user and it did not terminate its learning process where the users’ feedback was continuously used to improve its performance. In conclusion, an “Adaptive System with User Control” was developed thus improving the acceptability and usability of a mobile device which aligns with the research aim.

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Section: Applicationsmentioning

confidence: 99%

Section: Prototypementioning

confidence: 99%