DawgSense
Your Dog's Emotions, Understood and Managed
Team
Ji
Huang
Shao
Que
Torkmanzadeh
Problem and Design Overview
Many dog owners struggle to effectively respond to and manage their dogs' emotional and reactive behaviors, particularly in high-stress or unexpected situations such as barking at other dog or behaving abnormally in unfamiliar environments. This issue stems from a lack of tools to help owners interpret and address their dogs’ behaviors in real-time, compounded by limited opportunities to learn from these situations to prevent recurrence. This creates challenges in both immediate intervention and long-term behavior management, leaving owners feeling unprepared and dogs more anxious.
Our approach emphasizes equipping dog owners with the means to respond to immediate behavioral challenges with Augmented reality (AR) and reflect on those scenarios for deeper understanding with Virtual reality (VR). By focusing on both the reactive and proactive aspects of behavior management, the design ensures that owners are not only able to address a situation as it arises but also gain insights into potential triggers and alternatives for future prevention. This dual focus helps build owners’ confidence in navigating complex behavioral challenges while fostering a stronger connection with their pets.
Design Walkthrough
The focus tasks—supporting in-the-moment crisis response and practicing skills to interpret emotional cues—align perfectly with DawgSense's dual AR and VR capabilities. The AR mode on Orion glasses enables real-time detection of behavioral cues and crisis triggers during live interactions with the dog, guiding the user to de-escalate or manage situations effectively as they happen. The VR practice mode enables the reflective learning by allowing users to replay past crises and revisit previously encountered scenarios, learning to identify and interpret signs of anxiety, stress, or aggression in a safe environment. The synergy between our focused tasks and design stems from how AR and VR complement each other, creating a well-rounded system that not only enhances immediate responses but also builds dog owners' foundational knowledge and confidence in understanding and managing dog behavior in various real-world contexts.
Select Mode to Start.
Support In-The-Moment Response to the Crisis
Upon activating the monitoring function (AR mode), a pop-up notification “Analyzing in Real-Time” and a visual clue of the dog’s tail movement status appear. This assures the user that the system is actively scanning their dog’s behaviors and environmental triggers.
Monitoring and Real-Time Analysis Initialization.
When unusual behavior is detected, such as rapid tail wagging or stiff posture, the system can recognize these early warning signs and alert the user with a warning message “Unusual Behavior Detected.” This message is accompanied by a prompt asking the user to confirm the system’s detection.
Crisis Detection and Warning Message.
Once a crisis is confirmed, the system presents a series of tailored suggestions to help de-escalate the situation. These suggestions may include actions like guiding the dog to a calm space, offering a distraction, or using specific calming commands.
Suggested Interventions and Crisis De-Escalation.
Once the suggested intervention is completed, the system prompts the user to evaluate their dog’s current state to adapt dynamically to the outcome, offering further suggestions if necessary.
Post-Intervention Feedback and Confirmation.
Practice Skills Interpreting Dog’s Emotional Triggers and Responses to Prevent Crisis from Occurring
Upon launching the system to practice mode (VR mode), users can choose a crisis scenario based on previously recorded incidents.
Scenario Selection and Initial Setup.
Once a scenario is selected, users watch a simulated VR video of the incident, observing the dog’s behavior in real-time. The system then prompts users to identify the dog’s emotional state, such as nervousness or fear, and the potential triggers causing these emotions.
Emotion and Trigger Recognition in Simulated Videos.
After users submit their responses, the system provides immediate feedback, highlighting whether the correct emotion and trigger were identified. If any triggers were missed, the system offers a list of potential triggers with explanations to enhance user understanding and learning.
Feedback and Learning Support.
At the end of the session, users receive a personalized report detailing their performance. The report highlights key achievements, such as correctly identifying emotions and triggers, and offers suggestions for improvement, like focusing on more nuanced behavioral cues earlier.
Performance Report and Improvement Suggestions.
Design Research and Key Insights
The goal of our design research was to understand the challenges dog owners face in interpreting and managing their pets' emotional and reactive behaviors. We aimed to identify gaps in current solutions and explore how real-time emotional monitoring could enhance behavior management. Our method was to conduct semi-structured interviews with three participants: a dog owner, a veterinarian, and a dog trainer, each providing unique perspectives on dog behavior, training, and management. These participants were selected for their diverse experiences, ensuring a holistic view of the challenges faced. Semi-structured interviews were chosen to allow flexibility in gathering in-depth insights into dog's emotional cues, behavioral management, and training needs. This approach provided actionable insights that informed our design decisions.
Overview of Design Research Insights.
Real-Time Emotional Monitoring Enables Timely Interventions
Interviews revealed that dog owners struggle to recognize early signs of stress or anxiety in their pets, often leading to delayed responses that exacerbate reactive behaviors. For instance, a trainer mentioned, “It’s hard to know what’s going on in her mind until it’s too late, and by then, she’s already reacting.” This insight highlighted the importance of real-time tools for detecting subtle cues like tucked tails or pinned ears. Incorporating this into our design, we prioritized features like AR-driven real-time behavior analysis to guide owners in preventing crises before they escalate.
Owner Education Requires Long-Term, Reflective Approaches
Participants emphasized the need for comprehensive education on dog behavior. While training videos and apps provide some support, they lack personalized guidance tailored to specific dogs and contexts. The veterinarian noted that “dog owners need to learn how to manage their own emotions” since stress can transfer to pets. This insight shaped our focus on combining immediate support with long-term learning tools, such as VR scenarios for reflective practice, helping owners understand their dog's triggers and manage interactions proactively.
Behavioral Triggers are Complex
During interviews with dog owners, a recurring theme emerged: many struggled to identify the triggers behind their dog's behaviors, especially during stressful situations. One participant shared, "When she gets stressed, I just pull the leash and take a different route to help her relax." This response underscores a tendency among owners to rely on reactive measures instead of responding appropriately to the behavioral triggers. This insight highlighted the need for tools that not only provide behavioral cues but also connect these behaviors to the surrounding environment, such as noise or movement nearby. This learning pushed us to prioritize real-time contextual support as a central aspect of the design.
Iterative Design and Key Insights
Our iterative design process started with low-fidelity sketches to establish basic design concepts based on our design research. We evolved these sketches into storyboards and task walkthroughs to convey context and illustrate interactions, focusing on two primary tasks: supporting in-the-moment crisis responses and practicing behavioral interpretation. This led to the development of paper prototypes and heuristic evaluations, where we identified crucial usability issues such as the absence of a back/undo button and confusing visual indicators.
Overview of the Paper Prototype.
Usability testing with target users further revealed problems like insufficient feedback, complex task flows, and unclear navigation, which informed our refinement in the digital mockup stage, such as refining a cohesive and functional interface for both focused tasks and adding a 'History & Reports' interface to enhance user reflective learning.
Reflecting on this process, the iterative nature of our design approach—from prototyping to user testing—was instrumental in uncovering and addressing user needs effectively, making the final design both intuitive and effective. Each cycle provided critical insights that directly shaped subsequent revisions, culminating in a design that helps dog owners manage and understand their pets' behavior both in real time and through reflective learning.
Streamlining Interaction Complexity Enhances User Efficiency and Engagement
In our initial paper prototype, users were required to use two distinct interfaces to accomplish each of our focused tasks—“Monitor in Real-Time” and “Practice Your Skills.” This separation not only introduced unnecessary complexity but also disrupted the fluidity of the user experience. Observations during usability testing underscored the confusion caused by this disjointed interaction model.
To address these issues, we consolidated both key functionalities into a unified 'Home' interface in our digital mockup. This integration allows users to seamlessly toggle between monitoring in real-time and practicing their skills without the need to switch contexts. This design refinement simplifies user interactions and enhances the accessibility of the application, fostering a more cohesive and streamlined experience. It encourages more intuitive and personalized engagement with the system, significantly boosting user satisfaction and efficiency. By streamlining these features into a single interface, the revised design effectively supports users in achieving their intended goals with greater ease, thereby elevating the overall utility and user-friendliness of our application.
Before: Two separate homepages were designed for each focused task.
After: Both focused tasks have been integrated into a single homepage. Users can now choose between the two modes.
Intuitive Navigation and Responsive Controls Empower User Experience
Our heuristic evaluations and usability tests highlighted the lack of essential navigation and directive elements. For instance, one user accessed the main interface but struggled to navigate to the next frame due to the lack of clear prompts. In another case, a user wanted to switch from practicing how to identify potential 'barking' warnings to 'shaking' warnings. However, due to the absence of functionality for modifying selections, the user was unable to make any changes once a choice had been made. This oversight limited users' ability to perform, adjust, or revert actions, leading to frustration and a diminished sense of control over the application, contrary to the User Control and Freedom heuristic.
To address these issues, we enhanced the design to include backward navigation and undo functionalities, thereby empowering users with the flexibility to easily navigate back or terminate actions when they change their minds. Additionally, we introduced a 'continue' button on the homepage and a new interface detailing various operational modes. These enhancements make the progression steps and available functionalities clear, significantly improving the user experience by ensuring consistency and simplifying navigation. Together, these improvements have transformed our design into a more user-friendly and responsive tool, enhancing both its functional integrity and user satisfaction.
Before the change, there is no button to go back or exit. A Back Button was added to allow users to navigate, and an Exit Button was added to provide a clear way to leave the session entirely.
Instructive Feedback is the Key to Enhance User Progress and Long-Term Learning
The usability tests revealed that the initial feedback mechanisms after completing practice sessions were too general and lacked detailed, actionable feedback. Users received generic messages like 'Good Job!' without a comprehensive breakdown of their performance or suggestions for improvement. This deficiency in meaningful feedback violated the Visibility of System Status and Feedback heuristic, as it failed to communicate to users how well they performed and how they could improve. The absence of actionable information hindered the learning process, leaving users unable to gauge their progress or identify areas requiring attention.
To address this shortfall, the feedback mechanism was overhauled to include both positive reinforcement and constructive suggestions. In the revised design, post-training feedback not only praises correct actions, such as identifying early signs of anxiety with statements like 'You identified early signs of anxiety correctly. Great work!', but it also highlights specific areas for improvement, such as 'Focus on noticing tail movements earlier,' accompanied by actionable advice. This enhancement is highly effective for long-term learning.
Before: Post-practice feedback screen displaying the vague 'Good Job' message without any additional description or summary.
After: Post-practice feedback screen displaying the detailed summary of user performance and further improvements.