A System That Detects Attention Decline and Reflects It Before Self-Blame Begins
OVERVIEW.
Modern life places people under constant pressure to keep up. Many work relentlessly and seek new knowledge not out of curiosity, but from a quiet fear of falling behind. As stress builds, efficiency starts to decline. Focus becomes harder to sustain during work, and when it is time to rest, people often struggle to truly switch off. Over time, the growing gap between effort and results leads to even more anxiety and self-blame.
To cope, many turn to productivity apps that rely on control—blocking websites, setting timers, and enforcing discipline. When these tools fall short, they often leave users feeling more guilty rather than more supported.
In this project, I worked end-to-end as a product designer, from problem framing and user research to app design and system direction. The project takes a different approach, treating focus not as a behavior to control, but as a process that naturally shifts over time.
The product uses glasses to sense eye blink patterns and heart rate variability as signals from the body, without compromising user privacy. These signals are then sent to the app, where they are visualized in a clear and accessible way. By seeing their own patterns over time, users can better understand how their body responds to sustained effort and pressure, and make more thoughtful decisions about rest, leading to work that feels more sustainable and less exhausting.
Role: Product Designer
Year: 2025
Problem Statement.
Many people turn to website blockers and timers to manage their focus. When these tools fail, the outcome is often reduced to a single conclusion: failure. Missed sessions or unfinished tasks are interpreted as a lack of discipline, without understanding whether the drop in efficiency was caused by fatigue or a genuine need for rest.
This lack of insight leads to self-blame rather than adjustment. Users respond by pushing themselves harder, which increases pressure and strain. As stress builds, focus becomes even more difficult to sustain. Attention drifts more easily, effort feels heavier, and the gap between time spent and progress made continues to widen. Instead of easing pressure, existing tools often intensify it, locking users into a cycle of control, frustration, and diminishing focus.
Solution.
Through research, eye blink patterns and heart rate variability were identified as signals that reflect how a person’s focus changes over time. Instead of treating these signals as raw data, the product translates them into an understandable view of the user’s focus rate across a session or day.
By seeing these patterns, users gain context for moments when efficiency drops. Rather than assuming a lack of ability or discipline, they can recognize when reduced focus is linked to accumulated strain or a need for rest. This shift in understanding changes how users respond. Rest becomes a deliberate decision instead of a source of guilt, and effort is applied more intentionally rather than through pressure.
By helping users understand their state before pushing further, the product supports more balanced pacing and allows productivity to recover naturally after rest, instead of being forced under stress.
From Sensing to Understanding.
The glasses capture changes in the body, but these signals do not carry meaning on their own. To help users truly understand what is being sensed, the system passes this data to the app, where it is organized and presented through visualization.
Rather than exposing raw measurements, the app translates these signals into patterns of rhythm and change. This allows users to see how their attention builds, softens, and recovers over time, turning subtle physiological signals into something that can be read, reflected on, and understood.
This screen marks the moment when sensing begins, and it is always initiated by the user. The glasses do not collect data continuously in the background. They only become active after the user explicitly chooses to start a session.
By making the start state visible and intentional, the design reinforces a clear boundary between everyday wear and data collection. Users are aware of when sensing is happening and remain in control of when it stops. This approach avoids passive surveillance and ensures that attention data is gathered with consent, not assumption.
The language and visual tone of this screen are deliberately calm and unhurried. Rather than signaling productivity or urgency, the interface invites presence. The goal is to help users ease into a focus session without pressure, while knowing that their data is only being read when they choose to engage.
This screen is designed for reflection rather than real-time action. Instead of showing raw data or moment-by-moment alerts, it offers a calm overview of how attention unfolded across the day.
The interface avoids language of success or failure, emphasizing that focus does not follow a straight line but moves in waves. This framing helps users step back from individual moments and see their experience as a whole.
The Today’s Rhythm summary is generated by AI based on patterns observed in eye blink and HRV signals throughout the day. Rather than explaining the data directly, it translates these patterns into a short narrative that describes how effort shifted and recovered, helping users make sense of their experience without feeling judged or corrected.
Below, the Focus Energy visualization brings multiple signals together. Focus, HRV, and eye blink are shown side by side to provide context, not comparison. No single metric is treated as a definitive answer. Instead, users are encouraged to notice relationships between signals and how their state changed over time.
By presenting data in this way, the screen supports awareness without pressure. It allows users to understand their own patterns, recognize moments of strain or recovery, and reflect on how attention responds to sustained effort—without turning observation into another form of performance tracking.
This screen expands on the Today’s Rhythm summary, offering a more detailed reflection on how attention shifted throughout the day. Rather than presenting new data, it slows the experience down and gives users space to read what was already sensed.
The Key Moments section breaks the day into a few meaningful points in time. These moments are selected based on noticeable shifts in eye blink and HRV patterns. Each entry simply describes what changed and how the body responded. The AI does not judge whether attention was focused or unfocused, productive or inefficient. It does not treat loss of focus as something wrong. Its role is to describe what happened, as it happened.
Below, How your body supported attention today connects individual moments back to broader patterns. The AI explains how signals often appear together during sustained effort, helping users understand context without telling them what they should have done differently.
Across this screen, the AI acts as a translator rather than an authority. It reflects the truth of the day in clear language, allowing users to see their experience without pressure to fix, optimize, or perform.
Key Takeaways.
I learned that design decisions are strongest when they are guided by what the system should not do, not just what it should include.
I learned that translating complexity into something readable is more impactful than adding more functionality.
I learned that giving users control over when a system is active fundamentally changes how trustworthy it feels.
I learned that language, tone, and pacing are as important as visual layout when designing experiences around pressure and attention.
I learned that a product can be supportive without being directive, and that restraint can be an intentional design choice.
I learned that designing systems, rather than isolated screens, requires thinking across hardware, software, and interaction boundaries.