Augmented Reality for Enterprise Alliance

Impact of Spatial Vision on Visual Encoding and Memory Anchoring

Why is this Important?

  • All AREA members seek to reduce cognitive load and increase performance and memory encoding of workers during the performance of complex tasks.
  • To date, the role of stereoscopic vision in AR experiences in spatial understanding and memory has not been studied. When these are better understood and the impacts are quantified, designers of experiences and interfaces will be able to accelerate memory anchoring and spatial awareness.
  • Determining the specific contributions of AR to human memory and cognitive functions will contribute to calculating return on investment on AR in the enterprise, justifying investments and removing enterprise AR adoption barriers.

Some complex instructions and illustrations used in training or on the job require greater time and cognitive load for workers to understand, retain, and use when displayed in planar mode (2D). Three-dimensional representations and spatial vision enabled by stereoscopy has been shown to increase comprehension of spatially relevant concepts and increases their encoding and retention in memory. Although technology today enables spatial vision, frequently it requires some level of compromise around performance, wearability, or resource requirements.

This research topic focuses on measuring the impact of binocular (vs monocular) vision on short- and long-term memory encoding (i.e., the process of changing sensory inputs into forms that are stored in the brain and anchored in such a way that enables effective retrieval).

Stakeholders

User experience designers, AR experience developers, human resources professionals, AR display designers, AR display manufacturers, researchers studying cognition and performance of users in the workplace

Possible Methodologies

The research topic would need experts to develop and use a combination of existing neuro-analytical tools (tools that measure neurological brain activity) and biometric tools that infer neurological responses by proxy. The former includes EEG, fMRI (functional MRI), fNIRS (functional near-infared spectroscopy) and steady state topography (SST), all of which directly measure brain activity related to specific brain functions. For instance, SST measures the speed of electrical activity on the surface of the brain, linking changes in certain areas to specific metrics like engagement and memory encoding. The latter includes eye tracking, facial coding, and biometric data like heart rate monitoring. This research will analyze data for broader interpretation, offering insights into the use and impacts of 3D spatial viewing with AR, compared to measurements made by technology like SST and fMRI.

Research Program

This research topic can be integrated with fundamental research on brain function. It could also be combined with studies of specific use cases in which the system recalls the users’ spatial vision strategies and enhances those selectively. User experience design would also benefit from studies of this and related neuro-analytical tools and topics.

Miscellaneous Notes

There has been research published on the topics of spatial vision and more specifically on AR and memory encoding. This 2019 article published in Frontiers in Human Neuroscience reports on research conducted using AR to assess the impact of gender on spatial vision and anxiety.

Keywords

Spatial vision, spatial memory, visual encoding, memory anchoring, spatial frequency, receptive Field, modulation transfer function, high spatial frequency, threshold

Research Agenda Categories

Displays, Technology, End User and User Experience

Expected Impact Timeframe

Near

Related Publications

Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:

More publications can be explored using the AREA FindAR research tool.

Author

Peter Orban, Christine Perey

Last Published (yyyy-mm-dd)

2021-08-31

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