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Recent Advanced Human Factors Science Research Methodologies Developed and Validated by Mauro Usability Science

Over the past year, our research group has been focused on the development and validation of several advanced human factors research methodologies designed to provide demanding product development groups with robust and validated human factors testing expertise. The following six summaries cover a portion of the research methodologies we have developed and validated. A detailed description of each methodology follows the list. All methods have been validated in major client projects.

1 eSports Human Factors Gameplay Optimization.

2 Methodology for Development of Psycho-Socially Salient MVP Feature Sets Designed to Increase Likelihood of User Adoption for New Products and Services.

3 Advanced Human Factors / Usability Fit and Comfort Assessment for AR Glasses / VR Headset and Wrist-Worn devices.

4 Advanced Website Usability Optimization Methodology Focusing on User Navigational Performance and Related Business Impact Modeling for Critical e-Com Use Cases.

5 AGILE Medical Device Summative Human Factors / Usability Testing Focusing on Rapid IFU Optimization and Cost Reduction.

6 Updates to the Empirical Ordinary Observer Test (EOOT) Developed by MUS and Accepted by the Court in Major Design Patent Litigation.


Detailed Descriptions

1 eSports Human Factors Gameplay Optimization

  • The Problem: eSports, including professional competitive video game events and even individual at-home gameplay, is rapidly becoming one of the largest sports categories in the world, with current revenue of over 1.8 billion dollars. However, a primary problem with eSports professional events attended by millions of users has been the inability to create a user experience that can be understood and optimized to improve an observer’s and player’s ability to understand what is happening in the game in real time. This problem is due in large measure to the rapid response time of gameplay and action clusters taking place simultaneously in multiple areas of the screen. These interface attributes directly relate to the limitations of human information processing and the design and layout of gaming workstations and user interfaces present during gameplay sequences. These same limitations apply to those participating in actual at-home gameplay, those observing large-scale competitive eSports events, and professional gamers working in teams at massive venues such as the Crypto.Com Center in LA. Without dramatically improved human factors research and workstation optimization, the continued growth and interest in eSports at all levels will likely soon find a plateau. To address this problem, MUS has developed the first fully integrated eSports human factors performance testing laboratory combining physical workstation configuration testing with live game-play performance.
  • Our Solution: The MUS eSports Human Factors Optimization Lab combines into one primary data stream 28 channels of psychophysical monitoring that runs in real-time during full gameplay sequences of up to 3 hours of continuous gameplay. The system provides for the first time extensive 3D spatial tracking of all primary workstation physical components including seating, display interfaces, direct manipulation devices, and work surface configurations, as well as capture of respondent cognitive and physical attributes during live gameplay sessions. The system allows for the first time a detailed scientific analysis of the relationship between workstation design and game-design attributes as they impact longitudinal gameplay performance. The system enables micro-level tracking of the relationship between all critical human factors performance variables with a focus on cognitive / physical workload, fatigue, and stress vs. gameplay outcomes. MUS is currently partnering with leading video game technology companies with a focus on creating and validating workstation design innovations and actual video game interfaces that will dramatically improve user acceptance and participation in the rapidly expanding eSports space.


2 Methodology for Development of Psycho-Socially Salient MVP Feature Sets Designed to Increase Likelihood of User Adoption for New Products and Services.

  • The Problem: The development of a robust and emotionally salient feature set for new products is the most complex problem development teams face today. Traditionally, feature sets have been based essentially on the personal opinions and thinking of the initial development team, without formal and validated reference to the underlying psychosocial needs of their potential customers. For decades, product development teams have incorrectly assumed the view of how users rate feature sets. This has led in large measure to the massive problem of feature creep and products which consumers outright ignore. We believe that this failure to match the initial feature set design with the psycho-social needs of users is a primary reason for why so many start-ups and even large new product development efforts fail. At MUS, we have worked for over a decade to address this problem. The result has been the development of a robust testing methodology that is based in large measure on a well-understood and widely researched topic known as “Subjective Well Being” or SWB for short. This methodology has been utilized to identify feature sets that are far more emotionally salient and relevant to potential users of new products and services. This is a product development risk-reduction methodology.
  • Our Solution: By mapping the SWB conceptual framework from peer-reviewed research onto our extensive neuroscience-based data capture system, we are able to provide development teams with weighted and ranked feature sets based on the presentation of use-case simulations before formal product engineering has been undertaken. The structured testing methodology is designed to provide product development management and design teams with validated minimum viable product (MVP) use case structures and feature sets focused on the delivery of the most salient features that are likely to drive adoption and long-term product utilization. Utilizing a combination of product feature simulations and structured data capture, the methodology specifically identifies core feature sets that will have the highest emotional salience, desirability, value, and emotional resonance for the projected user groups. The system uses (in part) a combination of micro-facial expression analysis, eye-tracking, galvanic skin response, electroencephalography, and specialized subjective user response data capture systems to test for the objective existence of high positive emotional valence vs. subjective response. This is a highly collaborative methodology.


3 Advanced Human Factors / Usability Fit and Comfort Assessment for AR Glasses / VR Headset and Wrist-Worn Devices.

  • The Problem: The measurement and optimization of user comfort, fit, alignment, and device stability when interacting with all manner of AR and VR wearable devices, including wrist/arm and head-mounted products, is a complex and challenging human factors research problem. Our research team has a deep understanding of the formal research and validation methodologies related to acute and chronic pain measurement, fatigue, disorientation, body part fit, and comfort optimization. Our team has extensive experience with large-sample anthropometric data sets and a working knowledge of how to properly size devices for the appropriate percentile distributions of users across age domains and ethnicity. We have developed and validated methodologies for measuring comfort and pain in a wide range of wearable applications including smartwatches, AR glasses, VR headsets, action controllers, and other complex combinations of these platforms. We have validated methods utilized in major studies for leading wearable device development teams on a global basis. We have undertaken extensive longitudinal studies related to such devices for the specific purpose of identifying user rejection rates as a function of complex interacting variables such as weight, fit, application area, adjustability, and related functions.
  • Our Solution: We offer clients a full range of validated testing methodologies, including short team comfort and fit assessments, disorientation analysis, adjustment analysis, as well as longitudinal wear pattern and comfort analysis. Our experience includes in-depth knowledge of all critical vascular, biomechanical and anthropometric variables in head and wrist-mounted devices. Our experience also extends to complex studies involving device fit and sizing for consumer populations. For specialized fit and comfort problems where there is no actual published and reliable anthropometric or biomechanical data, our team can design, plan and execute custom consumer body size and biomechanical studies for a wide range of populations. Our team is highly experienced with rapid prototype assessment and lead-time compression methodologies, as required to meet the most demanding development schedules and product design optimization objectives. This is a highly collaborative methodology.


4 Advanced Website Usability Optimization Methodology Focusing on User Navigational Performance and Related Business Impact Modeling for Critical e-Com Use Cases.

  • The Problem: It is well understood that the majority of major website redesigns fail to regain their prior level of business performance when measured by user engagement and the profitability of per-user transactions. There are multiple reasons for this negative outcome, including the failure on the part of the UX design team to understand the actual behavioral impact of the following human factors science variables: 1) Failure to properly consider the prior learning of users who work on the site frequently, 2) Failure to properly and reliably document exactly which aspects of the current website UX design actually need a redesign to improve business performance, 3) Failure to properly balance graphic design/branding requirements vs. usability enhancements, and 4) Failure to optimize the most critical navigation flows as a priority for improving business performance. Taken as a group, these 4 problems constitute a complex decision space that requires substantial and robust early-stage testing of a website experience to determine which aspects of a website can benefit from a major or even incremental redesign effort. Past major website redesigns that have failed due to not identifying the relationship between design changes and business impact have given way to a more science-based assessment strategy. To aid in the resolution of these complex problems, MUS has developed and validated the following methodology.
  • Our Solution: Utilizing advanced and validated neuroscience-based usability and user engagement testing methods, MUS has developed a website usability testing methodology that provides robust insights into critical usability optimization use cases and feature set improvements for existing major website entities. Employing combinations of high-performance eye-tracking, micro-facial expression analysis, and subjective data capture, MUS provides website optimization research focused on understanding and optimizing only those aspects of a given web presence that have a direct and measurable impact on business outcomes. The central focus of this methodology is user navigation and look-forward content analysis. The system is configured to simultaneously test both desktop and mobile website interaction behaviors and to provide the development team with validated insights into which use cases and feature sets possess unique and meaningful business value. Data provided includes cognitive workload assessment, emotional engagement, way-finding, and critical business impact workflows. The methodology has been utilized in studies for major e-Com entities and cultural institutions. This is a collaborative methodology.


5 AGILE Medical Device Summative Human Factors / Usability Testing Focusing on Rapid IFU Optimization and Cost Reduction.

  • The Problem: Medical devices undergoing final summative FDA human factors (HF) testing require professional testing expertise and careful tracking of user behavior. To provide valid and supportable data for FDA submission, the HF performance of the total product in production form including packaging, instructions for use (IFU), product labeling, and the product itself must together deliver high levels of usability and HF performance. However, it is a fact that complex medical devices do arrive at summative user testing with usability problems not resolved in prior formative studies. When this happens, it is imperative that the HF testing team and the corporation producing the medical device rapidly identify the extent and nature of such problems and take action as early as possible to halt study execution, update the necessary device systems, and, to the extent possible, address such issues before restarting the summative study sequence. Ignoring critical usability problems that surface during summative testing is both costly and dangerous since the study will produce data that shows poor HF performance. A far better approach is to constantly monitor on a daily basis HF outcomes, take immediate action to resolve critical problems, and finish the study with improved and reliable HF performance data for FDA submission.
  • Our Solution: Having experienced these types of critical HF testing problems over the past 20 years, MUS has developed a robust and structured methodology that is focused on four critical aspects of this problem: 1) Daily tracking and detailed reporting of all primary HF performance variables for all respondents in the study in rapid succession, 2) Early and aggressive identification of error states that are consistent across primary user profiles that may constitute a usability problem trend, 3) Rapid and early identification of the root causes of such errors, and 4) Identification and schematic development of possible solution sets for resolving such critical problems. It is often the case that modifications to the IFU design, content structure, and flow will provide the necessary improvements required to meet FDA HF approval. To rapidly update the primary IFU flow, MUS has developed a formal IFU optimization methodology based on the application of structured cognitive task analysis combined with rapid-response pilot testing of IFU updates BEFORE returning to the final stages of summative testing. Our methodology is specifically focused on the resolution of all critical root causes of error variables through rapid redesign of the IFU systems, followed by actual pilot-session respondent testing with the optimized medical device system. Only after the medical device system refinements are validated is summative HF testing restarted and completed. This approach has saved clients hundreds of thousands of dollars in study re-do fees, not to mention reduced delays for critical FDA submissions. This methodology is a collaborative effort with the medical device development, regulatory, and product management teams.


6 Updates to the Empirical Ordinary Observer Test Developed by MUS and Accepted by the Court in Major Design Patent Litigation.

  • The Problem: For those colleagues who may not have been following our development of a science-based EOOT methodology, we are proud to announce that the EOOT has now been formally accepted by the court and has withstood numerous aggressive Daubert challenges. We currently have several EOOT studies in process for leading design patent litigation matters. As part of our ongoing commitment to continuous updates, we have undertaken additional refinement of the EOOT methodology. Below is a brief description of important updates to the EOOT.
  • Our Solution: Based on feedback from our leading legal clients, our research team has updated critical aspects of the EOOT methodology to produce even more robust scientific results in shorter study lead times and at a relatively lower cost. We have been specifically focusing on how to improve the process of capturing and creating valid visual references for use in the prior art section of EOOT studies. We have also updated the EOOT to capture data on issues related to 101 defense and anticipation. This new application of the EOOT is being executed for defendants in current design patent litigation. Overall, the EOOT has been continuously updated and optimized for improved scientific rigor, always with the overall objective of meeting research guidelines from both Daubert and Federal Judicial Center specifications. We are currently fielding 6 major studies in the consumer and professional market spaces. It is important to note that we have also updated aspects of the EOOT to take into account recent court decisions related to design patent infringement analysis. Since the initial launch of the EOOT methodology, the methodology has been published in several top-tier legal proceedings, including the Berkeley Technology Law Journal and the Research Handbook on Design Law published by Edward Elgar Publishing. The EOOT has also been accepted for CLE and presented at ABA, IPO, and AIPLA conferences.


Please feel free to contact our research team for more information by emailing Charles directly (Cmauro@MauroUsabilityScience.Com).

We are also active on LinkedIn.

Thank you.

Charles L. Mauro CHFP
President / Founder (1975-Present)

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