Experiential Maps: Visualizing Emotional and Cognitive States in space
At RE-AK Technologies, our mission is to advance knowledge and develop tools for a deeper understanding of the human experience. Our specialization lies in emotional and cognitive analytics, leveraging brain-computer interfaces. Alongside the technological hurdles of capturing biometrics, we encountered an initial challenge: effectively communicating our findings to individuals outside the field, who comprise the majority of our clients. To address this, we’ve invested in the development of visualization tools to simplify result representation and enhance accessibility. One such tool is the Experiential Map.
Motivation Behind Experiential Maps
Experiential Map are used when the captured experience has a spatial dimension. In such instances, emotional and cognitive metrics can be technically represented as a function of participants’ locations when the data was captured.
We had to work out some math, first, because the data is noisy, but also because we needed to perform local averaging to extract meaningful statistical metrics, as summative metrics are heavily biased by how much time participants spent at a given location. We documented part of this process in a blog post during our exploration. However, this was only a small hurdle in our journey as it revealed the greatest challenge of all, how do we deal with the problem of representing many metrics, in a concise way?
Our initial approach led us to generate as many maps as we had metrics. This resulted in a total of 13 individual maps, considering all emotional, cognitive, and physiological measurements. While we could eliminate non-pertinent maps, such as those containing less important emotional metrics for a particular experience, we still ended up with around six maps for any given experience. So much for simplicity and briefness. (We published a workshop paper with some of our results, back then, here’s Figure 2)
We then began the work on what would become the Experiential Maps as we know them today Unfortunately, we cannot divulge the technical intricacies of the process, as it remains a trade secret, but we succeeded and achieved our objective of creating Experiential Maps that agglomerates the most significant information, coming from all metrics, into one color-coded map. Although, we refer to the individual colors as state of minds, instead of individual metrics (described below).
This article will now explain how to work with these maps, detailing their benefits and limitations. Additionally, it will expand on the tools integrated with these maps to break down the results, enabling an even more precise understanding of participants’ experiences.
States of Mind
Instead of attempting to represent all the information for each spatial position (referred to as a point hereafter) on the map, the experiential maps utilize an algorithmic strategy to extract the most meaningful information for a given point.
If we were to, for example, represent the most important metric for each point, we would overlook a significant amount of information since multiple metrics can be important simultaneously. This is where the concept of “state of mind” becomes crucial. A state of mind encompasses emotional, cognitive, and physiological states, collectively representing a psychophysiological state that can be interpreted or simplified as a state of mind.
The experiential maps utilize an algorithmic strategy to extract the most meaningful information for a given point.
By selecting the most important state of mind for each point, the problem becomes simpler and preserves more information compared to selecting a single “winning” metric for each point. This proprietary process is what underlies the construction of Experiential Maps.
Benefits of Experiential Map
Once the algorithm has processed the data, we are presented with a simplified representation of the participants’ experience, where each state of mind is assigned a distinct color. Our maps always include a legend that provides a breakdown of each state of mind.
Experiential Maps are typically easy to communicate, containing a relevant amount of detail. While we often annotate them and offer interpretations, their visual appeal allows individuals familiar with the physical layout of the space to retrace participants’ movements and understand transitions between different states of mind.
Internal teams frequently use experiential maps to reflect on participants’ experiences and validate hypotheses formulated during the design of the journey. Additionally, marketing teams utilize experiential maps as media content to showcase their experiences.
However, the Experiential Map is not exhaustive and is usually accompanied by a position density heatmap, indicating where participants spent the most time. Position density heatmaps are generally intuitive, requiring minimal supplementary information for our clients to understand them.
Experiential and position maps serve not only for representation and interpretation but also as annotation tools. Once these maps have been comprehended and analyzed, we can further segment them into regions of interest (ROI). These ROI can then be utilized to calculate detailed statistics concerning the emotional, cognitive, and physiological states of the participants, thus capturing information lost during the conversion to the state of mind, should a more in-depth analysis be necessary.
Limitation of Experiential Map
Experiential maps offer a simplified representation, yet we’ve identified two significant limitations.
- The foremost limitation is that at times, they may obscure crucial states of mind. When utilizing experiential maps, it’s essential to bear in mind that states of mind may overlap, and only the most significant one is depicted. We are currently contemplating methods to address this issue, but the approach involves remaining vigilant for indicators that an important state of mind could be overshadowing another slightly less significant one.
- The second limitation is that experiential maps do not depict the magnitude of the metrics. While the extent they cover may offer some indications of metric levels, a deeper understanding of how various regions compare against each other requires reliance on ROI statistics. Alternatively, we also generate heatmaps for each metric as supplementary material. Thus, for a more comprehensive analysis of the experience, you can utilize the metric-centric heatmaps to enhance the granularity of your examination.
In Conclusion
Experiential maps serve as an excellent tool for presenting a simplified depiction of an experience with a spatial dimension. They facilitate the communication of a concise description of the experience and can even serve as marketing content. However, whenever a simplified representation is employed, there is a risk of overlooking certain details. For a more comprehensive understanding, one should turn to ROI statistical analysis, metric-specific heatmaps, or even Chronological Maps (as discussed in the next blog post) to obtain a more accurate representation of the metrics.
If you’re eager to delve deeper into RE-AK, Experiential Maps, or the realm of emotional, cognitive, and physiological analytics applied to human experiences, we encourage you to subscribe to our newsletter (by visiting our website) or join our Discord community. Experiential maps are just one of the tools that will be accessible through our suite of companion applications developed to support the Nucleus-Hermès (Beta launch: Fall 2024).