Brain-Computer Interface as a Method for Evaluating User Emotions

How would you feel if you were late for a meeting because of a Google Maps error? What if your favorite movie stopped loading at the most interesting moment? What if you missed your flight due to problems with your e-ticket? What would you do? Emotional states are greatly influenced by how people interact with environments and systems—including digital products and user interfaces.

Users have a substantial amount of emotional experience with the product—both positive and negative—and emotions may fluctuate from minute to minute and day to day.

The Range of User Emotions

Ways to Measure User Emotions

UX specialists have many methods of evaluating user emotions—for example, the Likert scale, the Semantic differential scales, emojis, open-ended questions, product reaction cards, and more. However, in all these methods, the amount of information that the participant can provide is limited. As a result, examining unconventional and innovative rather than common means of emotion evaluation is important.

Brain-Computer Interface

The brain-computer interface (BCI) is a combination of hardware and software that allows scientists to research the brain’s cognitive processes as well as register changes in emotional states and levels of attention. Studying brain activity by using a neural interface has a high temporal resolution. With this method, registering rapid changes that correspond to the high speed of brain-information processing is possible. Advanced signal processing and machine learning methods are applied in order to investigate the neural correlates.

Initially, BCI technology that was developed for disabled users promised the invention of assistive technology. However, current BCI exploration has encouraged researchers to study BCI involvement in entertainment for healthy people.

BCI Equipment

Applying BCI to usability testing is appropriate for real-world settings. Equipment needed to conduct the research includes only a wireless device connected by Bluetooth to the app. Basic BCI equipment is available for purchase on Amazon. The starting price is $200. In order to conduct research, a UX specialist does not need to be a scientist or have any specific knowledge. Each BCI device comes with a QuickStart guide that helps users operate the equipment and analyze the results.

How Does it Work?

The BCI app interface includes four displays: brainwave visualizer, brainwave power spectrum, attention meter, and meditation meter. The brainwave visualizer tracks the frequency bands of a participant’s brainwaves. In this circular chart, each of the eight axes corresponds to a different frequency band. As a participant’s brainwaves naturally fluctuate, the circle changes and flows artistically. The brainwave power spectrum is a display of the voltage of the participant’s brainwave signal. The attention meter is controlled by focusing on a single thought or point. As the participant shifts away from such focus, his or her attention value decreases. The meditation meter displays levels of calm and meditation. When a participant breathes deeply and sits with a straight back and closed eyes, the meter shows high values.

Deep Dive into Brainwaves

Conclusions about a participant’s emotional state are based on brainwave fluctuations. For example, a Gamma brainwave demonstrates decision-making and deep-learning processes; Alpha waves appear in moments of calm and relaxation.

How the BCI Method Leads to Better Usability

BCI technology provides accurate results and a deeper understanding of user experiences. The research described in the article, “Human-Computer Interaction for BCI Games Usability and User Experience,” shows that BCI can provide new kinds of information—specifically, on the user’s mental state. Brain activity detected by the BCI identifies the participant’s concentration level, degree of emotional involvement, overall emotional state.

Accurate data about participants’ emotional states during testing make weaknesses on the website easier to identify and fix. BCI research results provide UX specialists with insights regarding further website improvement.

References:

Bernhaupt, R., Dalvi, G., Joshi, A., Balkrishan, D. K., ONeill, J., & Winckler, M. (2017). Human-Computer Interaction – INTERACT 2017: 16th IFIP TC 13 International Conference, Mumbai, India, September 25-29, 2017, Proceedings, Part IV. Cham: Springer International Publishing.

Deniz, G., & Durdu, P. O. (2016). BCI-Related Research Focus at HCI International Conference. Lecture Notes in Computer Science Human-Computer Interaction. Interaction Platforms and Techniques, 151-161. doi:10.1007/978-3-319-39516-6_14

Szalowski, A., & Picovici, D. (2016). Investigating color’s effect in stimulating brain oscillations for BCI systems. 2016 4th International Winter Conference on Brain-Computer Interface (BCI). doi:10.1109/iww-bci.2016.7457449

Menzies, M. (2014). Neurofeedback: A Tool for Educational Research. Ottawa: Library and Archives Canada = Bibliothèque et Archives Canada.

Design Critique: Yandex search engine

Created in 2000, Yandex now is the largest Russian search engine on the Internet, with a market share of over 52%. Yandex is the most popular in Russia, Turkey, Belorussia and Kazakhstan. In Russia the Yandex.ru home page is the 4th most popular website. It also has the largest market share of any search engine in the Commonwealth of Independent States and is the 5th largest search engine worldwide after Google, Baidu, Bing, and Yahoo!. One of its biggest advantages for Russian-language users is the ability to recognize Russian inflection in search queries.

As a search engine Yandex has a lot of advantages:

  • Main page includes some signifiers (icons, search button) that helps users to understand search opportunities so Yandex has strong discoverability:

 

  • Search query correction

Yandex Search takes all possible word forms into account:

 

  • Yandex affordances is achieved through customizable settings that make Yandex more adjustable for specific user

You can personalize:

– the search form appearance;

– how the search results look;

– where the search results are displayed, on your site or on Yandex.

 

  • Search suggestions

– let users search twice as fast;

– help users word their query;

– correct mistakes, typos and incorrect keyboard layouts.

Also you can manage your search suggestions: change their order, delete unnecessary suggestions, add new ones.

 

  • Search constraints

Constraints are filters that help users narrow their searches by:

– date;

– section;

– keyword;

– format;

– language.

 

But sometimes you can encounter some problem using Yandex as a search engine:

  • Sometimes it does not display video results:

 

  • A lot of unused space in the right part of the page which can be used for short summary about requested topic.

E.g. the same request in Google:

 

 

  • Search result is a huge amount of information that has no categorizing (e.g. Google uses catalogue system distribution for separating search result into a categories)
  • Sometimes the search result displays sites that are in the development process

Traditionally, the task of any search engine was to find information on the Internet, but now that role has expanded. The Internet can no longer be seen as separate from the reality surrounding us, and search engines now have to look for all kinds of things, not just online but all over the offline world as well. And they don’t just look for things and find them – they also give helpful suggestions in any real-life situation. Contemporary search understands the desires of every individual user, as well as the reality in which the user exists. That’s why Yandex conceptual model can give suitable suggestions for each person, individually – including what to read, where to go for a meal, what music to listen to, how to get home in the fastest possible way, where to book the cheapest flights, and much more.

Background of Yandex is technological approach and statistical examination of all content changes. Every change should be reasonable and it helps to understand how it is useful for users. Yandex uses their own machine learning method for ranging elements in search results, target ads placement and machine translation.

Despite of some disadvantages Yandex affects the Internet ecosystem as much as any other key player on the market. Their core value is the interests of users – wherever they are or whatever goal they are trying to achieve, so Yandex remains a competitive player on the search engine market.