Measuring Players’ Emotions Through Biometrics: The Power of Psychophysiology in Games User Research

As a game developer or publisher, you probably know that emotions are key to player experience. They impact how players perceive games, what motivates them, and how they behave. Emotions also help players remember the game and the experience; they play a vital role in whether players will purchase the game. With 14,531 games released on Steam in 2023, it’s more important than ever to evoke emotions in players. Your ability to do so can make or break your game. So, how can you be sure that your game, teaser, trailer, or gameplay movie will win the crowd?

You may do it the traditional way…

Games user researchers commonly use observation, surveys, and interviews to evaluate players’ emotions. However, these methods have both advantages and drawbacks. Surveys and interviews help obtain feedback on a player’s experiences, but they rely on the player’s memory, which can result recall bias and lost information due to forgetting. Additionally, responses can be biased due to recency bias, where players remember their experiences better towards the end of the gameplay session rather than at the beginning. Administering surveys or interviews during gameplay can minimize this bias but may interfere with the player’s natural behavior. Another major methodological issue is bias in self-reported data, such as social desirability bias, where respondents provide answers they believe are more acceptable to present themselves better. Participant engagement is another concern, as fatigue or lack of interest can result in incomplete or unreliable responses. Players might also incorrectly identify the cause of an emotion due to misattribution or generalize an emotion to the whole experience rather than to the element that sparked that emotion.

To understand a particular subject, it is best to use information gathered from various sources to strengthen the credibility of research findings. Therefore, it is advantageous to supplement subjective methods, focusing on players’ conscious attitudes, with more objective psychophysiological measures.

… but it might be better to use the psychophysiological way

Psychophysiology is a fascinating field of study that offers unique and valuable insights into the complex workings of the human mind. By measuring physiological signals like changes in skin conductance, muscle activity, brainwaves, and heart rhythm, we can better understand players’ psychological processes in ways that were once impossible.

These signals are spontaneous, involuntary, and difficult to fake, which makes them incredibly reliable and unbiased sources of information.

The research psychologist can access this data in real-time throughout the gameplay session, eliminating any reliance on the player’s memory. This technology allows us to capture signals as they occur, with minimal interference in the player’s natural behavior. Its high precision detects even the smallest responses—far beyond what the human eye can observe—making it more accurate than traditional observation for specific use cases. Leveraging psychophysiology, we’re reaching new levels of precision and insight into how players react to games.

However, these measures have limitations. Directly mapping a psychological state to a physiological effect is impossible, as one physiological response may be associated with many psychological states.

For example, a faster heartbeat and clammy hands might signal the body’s reaction to something frightening—or to seeing someone attractive. It’s important to note, however, that no psychophysiological method currently enables researchers to read players’ minds. While physiological measurements offer valuable insights into players’ psychological states, researchers must interpret these signals indirectly. This is why physiological data should be analyzed in context by trained researchers who understand psychology, ideally supplemented with follow-up interviews or surveys for deeper insights.

First, know how we measure emotions in modern psychology

Russell’s circumplex model of affect is a key framework in psychophysiological research for understanding emotions. The model maps emotions along two main dimensions: valence and arousal. Valence reflects the emotional direction, indicating whether an emotion is positive or negative, while arousal (or excitement) measures the intensity level of the emotion, ranging from high to low. This interaction between valence and arousal allows for a nuanced view of emotions.

For instance, both anger and sadness have a negative valence, yet they differ in arousal—anger is high-arousal, while sadness is low-arousal.

Russell’s model is popular in psychophysiological research because it addresses the limitations of physiological responses in pinpointing specific emotions. Although psychophysiological instruments cannot directly identify discrete emotions, they can measure signals related to valence and arousal. From these measurements, researchers can infer the emotional states of individuals.

With this foundation, we can now explore how the model interprets bodily signals to better understand emotional experiences.

Second, understand how emotions translate to physiology

Given the scope of this article, we will provide a brief overview of the most commonly used types of psychophysiological measurements. For readers interested in exploring these methods further, a list of sources will be available at the end of the article.

Electromyography (EMG)

As previously highlighted, most physiological signals are linked to just one of the two emotional dimensions—valence or arousal. Among the various methods for measuring valence, electromyography (EMG) stands out as one of the most commonly used.

In simple terms, EMG works by detecting electrical signals generated during muscle contractions. When a muscle contracts, it produces electrical activity, which EMG can measure. In Games User Research (GUR), valence is typically studied through facial EMG, which assesses the activation of specific muscles tied to emotional expressions.

For instance, brow muscle activation is linked to negative valence, as these muscles are engaged when a person frowns, which commonly occurs in response to emotions such as anger, frustration, or sadness.

On the other hand, the activation of muscles around the lower eyelid and cheek is associated with positive valence, as they are involved in smiling, which often signals happiness, joy, or contentment.

One of the significant advantages of EMG is its sensitivity. It can detect even the smallest facial muscle movements, often invisible to the naked eye. This sensitivity allows researchers to capture subtle facial expressions that might otherwise be overlooked. However, this sensitivity is also a double-edged sword. While it allows for the detection of small muscle contractions, EMG electrodes can also pick up activity from nearby, unintended muscles, which may introduce noise into the data. This makes it challenging to isolate the specific emotional response being measured.

As a result, participants must remain still and avoid actions like talking, laughing, or chewing during the measurement, as these movements can interfere with the data and make it unreliable.

This requirement can be particularly uncomfortable during extended gameplay sessions, where natural movements and expressions are difficult to suppress.

Moreover, using facial EMG requires placing electrodes on the participant’s face, which some may find intrusive or uncomfortable. The process of electrode placement also requires precision, as accurate positioning is critical for ensuring that the right muscles are being measured. In non-clinical settings, such as in a gaming environment, achieving this precision can be challenging, and any deviation from the ideal electrode placement can lead to inaccurate readings.

Respiration

Respiration offers several types of data that can be used to infer emotional arousal. Key metrics include respiratory rate, variability, breath depth, and even sigh rate.

Typically, a faster respiration rate is associated with high arousal, indicating a heightened emotional response such as excitement or stress.

Conversely, a slower respiratory rate is typically linked to the activation of the parasympathetic nervous system (PNS), which promotes calm and relaxation. By reducing physiological arousal, the PNS lowers heart rate and muscle tension, leading to a state of tranquility and decreased emotional intensity. As a result, slower breathing is commonly associated with calming effects and reduced arousal.

However, emotional arousal is not always captured by the rate alone; it can also be seen in respiratory variability. This variability manifests as irregular breathing patterns, sudden fluctuations in breath rate, or brief pauses in breathing, all of which are common during intense emotional experiences. For instance, negative emotions like fear and anxiety are associated with both increased respiratory rates and greater variability, particularly in expiratory time. This indicates that the body’s response to fear involves intricate changes in both the rhythm and depth of breathing. Additionally, respiratory variability can also be an indicator of cognitive load. Research shows that fluctuations in respiratory patterns are sensitive to cognitive demands, which can be influenced by emotional states. This suggests that respiration not only reflects emotional arousal but also provides insight into cognitive engagement.

When it comes to breath depth, deeper breathing is often linked to positive emotional states, whereas shallower, more rapid breathing tends to correlate with negative emotions such as anxiety or sadness. Therefore, the depth of breath can serve as a marker for emotional valence. Similarly to the respiratory rate, deep breathing can activate the parasympathetic nervous system (PNS), promoting relaxation and emotional stability, while shallow breathing often reflects sympathetic activation associated with stress and anxiety.

Another important factor is sigh rate. Research has shown that increased sigh rates are associated with higher overall respiratory variability, which is commonly observed during negative emotional states. This suggests that

sighing may act as a compensatory mechanism to counterbalance the disruptions in breathing caused by emotional tension.

By restoring balance to respiratory patterns, particularly during heightened emotional arousal, sighing helps regulate the body’s response. As such, it is often linked to negative emotions, such as sadness, frustration, and anxiety, and can function as a physiological reset in response to emotional distress.

Additionally, sighing has been shown to occur more frequently during tasks that induce mental load, further supporting its role as a resetter of physiological states. This reset function is especially important in situations where individuals experience emotional overload or stress, as sighing can provide temporary relief from these intense feelings.

In Games User Research (GUR), stretch sensors are commonly used to measure breathing activity. These sensors are placed around the player’s chest to capture the movement of the chest during respiration. Stretch sensors work by detecting the expansion and contraction of the chest as the player inhales and exhales, providing real-time data on the player’s breathing patterns. While effective, these sensors have limitations. They are highly sensitive to movement, meaning that any shift in posture, talking, or other physical movements can disrupt the data. This sensitivity becomes especially problematic during longer gameplay sessions, as players may naturally adjust their position or talk, which could lead to inaccurate measurements or data loss.

Heart Rate (HR)

Another approach to assessing emotional arousal involves examining the cardiovascular system, which includes the heart, blood vessels, and blood circulation. Within psychophysiology, several cardiovascular metrics are often analyzed, such as heart rate (HR), interbeat interval (IBI), heart rate variability (HRV), and blood volume pulse (BVP). For simplicity, this article will focus on heart rate, as it is one of the most commonly used measures in psychophysiological research.

Heart rate (HR) is the frequency of heart contractions per minute, essentially a measure of how often the heart beats.

Research shows that high-arousal emotions, whether positive (e.g., excitement) or negative (e.g., anger), are closely associated with increased heart rate. This elevation signals the body’s state of heightened alertness or readiness, which often occurs during intense emotional experiences like stress, shock, fear, or anger. When the heart rate rises, it reflects the body’s mobilization in response to perceived challenges or stimulating events.

In contrast, low-arousal emotions generally have the opposite effect on heart rate. For instance, when experiencing low-arousal negative emotions, such as sadness, or low-arousal positive emotions, like contentment, the heart rate tends to slow down. This decrease corresponds to the body’s more relaxed, subdued state during calmer emotional experiences. Such slowing of the heart rate aligns with the activation of the parasympathetic nervous system, which supports relaxation and recovery, allowing the body to conserve energy and promote overall balance.

However, heart rate alone cannot fully capture the nature of the emotional experience, as it primarily indicates arousal level without specifying whether the arousal is positive or negative. In other words,

while a heightened heart rate tells us that the player is emotionally engaged, it doesn’t reveal the emotion’s valence—whether it is pleasurable or unpleasant.

To gain more insight into the emotional quality of the experience, researchers often combine heart rate data with other measures, such as skin temperature. By analyzing heart rate alongside physiological indicators associated with valence, researchers can begin to distinguish between positive arousal, such as excitement, and negative arousal, such as anxiety or frustration. For instance, studies have shown that positive emotional arousal is often associated with increased skin temperature in specific facial regions, such as the cheeks and nose, while negative emotions may lead to a decrease in skin temperature.

These distinctions are valuable in psychophysiological research, as they provide insight into how the body’s autonomic responses align with different emotional intensities and qualities. This understanding is particularly useful in settings like Games User Research (GUR), where tracking players’ heart rate changes can offer insights into their emotional engagement with gameplay—whether they’re experiencing thrills of excitement or the frustration of a challenging level.

Pupillometry

Pupillometry measures changes in pupil diameter (dilation and constriction). These changes are linked to visual and non-visual stimuli, which means that the pupil can change its diameter in reaction to changes in light intensity, but also to mental or emotional processes. Pupil dilation can indicate that the player finds a stimulus emotionally arousing, regardless of its positive or negative valence.

Pupillometry has the advantage of being a non-invasive measurement that can be quickly taken alongside eye movement. However, it is essential to note that game graphics changes, such as a variation in light conditions or color, can also cause fluctuations in pupil diameter.

Electrodermal Activity

The last measure of emotional arousal that I want to introduce, but certainly not the least, is electrodermal activity (EDA). EDA refers to the skin’s electrical conductivity resulting from differences in sweat production in specific sweat glands. Unlike other sweat glands, whose primary function is to moderate body temperature, these respond principally to psychological stimulation. They are primarily located in the palms of the hands and soles of the feet but are also present on the shoulders, wrists, forehead, and neck. Sometimes, it’s called Galvanic Skin Response (GSR).

EDA is perhaps one of the most established measures of emotional arousal and is widely recognized in psychophysiology as having an almost one-to-one relationship with arousal. While EDA is praised for its reliability and accuracy, when analyzing the response to a direct event, we have to account for delayed reaction time in response to a stimulus and for a period of recovery time afterward, during which no further event responses will be detected.

Moreover, since EDA is primarily measured by the electrodes attached to hands, players’ movement while manipulating a game controller might compromise the signal. Fortunately, researchers have successfully experimented with alternative electrode placement sites or electrode attachment methods.

Electroencephalography (EEG)

EEG measures signals generated by neural activity in the brain using electrodes placed on the scalp. Contrary to many myths, EEG doesn’t work like sci-fi technology that would let researchers into peoples’ minds and allow them to read their thoughts.

Then how does it work? Simply put, brain activity is processed using two basic parameters: amplitude (how large the signal is) and frequency (how fast the signal cycles). This allows us to detect patterns in brainwave activity, such as delta, theta, alpha, beta, and gamma activity. These patterns, also known as bands, are related to distinct cognitive, affective, or attentional processes.

While EEG isn’t a method to measure emotions in the sense of Russell’s model, it nonetheless can give valuable insights into players’ attitudes. We can gain insight into the approach or withdrawal-related tendencies in behavior and emotions by measuring the frontal asymmetry index. Research has found that an increased activity of the left frontal brain is linked to a tendency to approach a stimulus. In contrast, higher engagement of the right frontal brain indicates a tendency to withdraw from a stimulus.

Like other methods, EEG has drawbacks that must be considered before research. Generally, researchers use an EEG cap or headset consisting of wet electrodes to make electrode placement easier and mitigate motion artifacts. You can probably imagine wet hair’s effect on players’ comfort level. Furthermore, EEG measurements are prone to artifacts caused by head movement, making them unsuitable for studying active games or long gameplay periods.

Eye tracking

Finally, I’d like to briefly mention one more psychophysiological method, though not directly related to measuring emotions, which can be successfully combined with other measures to obtain even more valuable insights. As we have covered it in our other article, I will keep it short and sweet.

Eye tracking is a method that allows us to track eye movement and gaze to inform us where and for how long the player looked and how the player’s eyes were moving on the screen. While eye tracking can provide insight into a player’s visual attention, solely tracking gaze positions only reveals a little about the cognitive processes and the emotional states that influence eye movements. That’s why, to get the most from eye tracking, combining it with additional data sources, for example, with previously mentioned psychophysiological methods can be beneficial.

Psychophysiology in practice – real-life application

In our lab, we have successfully used various psychophysiological measures to investigate players’ experiences even further. For example, in one of our studies, we compared two trailers for upcoming games, Hellblade: Senua’s Sacrifice and Godfall, to determine which one was more emotionally arousing and attractive to players.

By combining EDA (GSR) with eye tracking, we were able to identify emotional arousal patterns and scenes that triggered emotional activation and track the actual focus of players’ gazes.

In addition, we expanded our understanding by surveying an additional means of gathering information. The survey provided us with insights into how appealing the trailer was to the audience and their willingness to play the game after watching it.

Similarly, Pierre Chalfoun and Jonathan Dankoff have described the study they carried out at Ubisoft’s user research lab on the Far Cry 4 demo trailer. Their work focused on identifying the most emotionally engaging moments in the trailer, assessing its attractiveness, and evaluating the understanding of introduced features. By combining EDA with self-report measures, they found that the co-op feature needed to be adequately introduced and showcased.

They used their findings to refine the trailer through an iterative process, using feedback from each study to modify it before the next test.

Another interesting example of applying psychophysiological methods in assessing trailers comes from studying horror movie trailers. The team at iMotions conducted a small study to determine which of the three trailers was the scariest. They combined eye tracking, EDA, EEG (frontal asymmetry), and self-reports to assess visual attention, emotional arousal, approach vs. avoidance motivation, and each trailer’s likeability and scariness, respectively.

They found that the scariest trailer, as rated by the viewers, was also the most emotionally arousing. Moreover, it elicited the highest behavioral approach motivation,

which may seem counterintuitive as we expect people to be more likely to avoid fear-inducing situations.

However, it’s essential to keep in mind that EEG can’t tell us what’s causing this motivation. It could be triggered by the trailer itself, the context in which it’s being watched, the viewer’s thoughts and feelings towards the trailer, or a combination of all these factors. Nevertheless, by analyzing these findings in the context of the purpose of a movie trailer, the researchers hypothesized that the approach motivation occurred because viewers felt interested in seeing this movie in the cinema. Their hypothesis was confirmed by the additional data obtained from viewers’ self-reports.

However, evaluating trailers is one of many ways to utilize psychophysiological methods in game research. In another one of our studies,

we focused on video game characters and more precisely, on their attractiveness to the players. By measuring EDA, we determined which heroes and heroines caused a high level of arousal in the players.

Not surprisingly, The Witcher’s Geralt of Rivia was the most stimulating male character. We could hypothesize on potential sources of emotional arousal based on which elements drew players’ attention as captured by eye tracking. This research methodology could be effectively applied to character design evaluation.

Psychophysiological methods can also be used on a larger scale, as demonstrated in Macromill’s study of Capcom’s Resident Evil 3 (2020).

Their team used heart rate and EDA as indicators of excitement and vigilance to understand better how the players received the game’s core concepts (survival x horror).

Researchers divided the game into 12 chapters and analyzed the average HR and EDA for each one. This way, they could determine which chapters evoked intense fear and panic in players and which didn’t deliver the intended experience. They learned that one chapter, where a group of zombies chased a character, was less scary for players than anticipated. Additionally, researchers found that fear prompted increased vigilance in players. These findings pushed Capcom to reassess how people feel fear and why they confront it, consequently returning to the crucial question of what horror is.

Takeaways

Emotions are crucial to player experience and impact player behavior and game sales. Leading voices in the Game User Research area agree that combining traditional methods with studying human psychophysiology offers a gateway toward a better understanding of players’ behavior and experience. By accessing human emotions at a more basic, unconscious level, we can gain more accurate insights, which better inform design decisions.

The increased accessibility of physiological sensors has expanded the use of psychophysiological research beyond academic settings into commercial settings. Sensors have become more affordable and more accessible to use outside of clinical settings. Commercially available research software, such as iMotions, which we use in our laboratory, has also made many aspects of psychophysiological analysis faster and more convenient. However, fully automated AI-powered emotion detection models have yet to be made available.

Currently, we use our knowledge of human psychology, its connections to physiology, and its limitations to infer players’ emotions based on human body signals.

This approach reduces susceptibility to bias and is less dependent on the player’s memory, self-esteem, and honesty.

Psychophysiological measures such as changes in skin conductance, muscle activity, brainwaves, and heart rhythm are reliable and unbiased sources of information.

They can be accessed in real time with minimal impact on the player’s natural behavior. The most established ways to measure emotions in Game User Research are electrodermal activity and, to a lesser extent, cardiac activity.

*

There is no surefire way to guarantee that your game, teaser, trailer, or gameplay movie will resonate with the crowd. However, as demonstrated by case studies, psychophysiological methods have been effectively employed in Games User Research labs, such as Try Evidence’s facility, to provide a competitive advantage to design and marketing teams. These insights have enabled developers to prioritize and improve aspects crucial to player experience while ensuring that they deliver emotionally engaging and memorable experiences, without compromising on their original goals.

Further reading

If you’d like to read more about the general overview of psychophysiological methods in Game User Research, you’ll find dedicated chapters in “Games User Research” (Drachen, Mirza-Babaei and Nacke), “Game Usability: Advice from the Experts for Advancing UX Strategy and Practice in Videogames” (Isbister and Hodent), “Game Analytics: Maximizing the Value of Player Data” (El-Nast, Drachen and Canossa) and “Emotion in Games. Theory and Praxis” (Karpouzis and Yannakakis).

Other valuable sources of information are research papers such as “A review of the use of psychophysiological methods in game research” (Kivikangas et al., 2011) or “Let’s Get Physiological, Physiological!”: A Systematic Review of Affective Gaming” (Robinson et al., 2020).
For a deeper understanding of the relationship between emotions in psychology and physiology, I’d recommend reading “Autonomic nervous system activity in emotion: a review” by Sylvia Kreibig.

If you want to see how psychophysiological measures are used in an academic setting, these two articles provide a good example: “Correlation between Heart Rate, Electrodermal Activity and Player Experience in First-Person Shooter Games” (Drachen et al., 2010) and “A fuzzy physiological approach for continuously modeling emotion during interaction with play technologies” (Mandryk and Atkins, 2007).

If you want to know which method best suits your game and goals, don’t hesitate to contact us.