Fit Grid

Introduction

People stick with habits when progress is easy to see and act on. Habit research shows that repeating a behavior in a stable context builds automaticity over time (often on the order of weeks to months), so cues and simple feedback matter. In self-tracking, tools work best when they support a tight loop of collection → reflection → action.

FitGrid is my small contribution to this space: a free iOS app that turns Apple Health workouts into a GitHub-style heatmap or contribution grid, with weekly, monthly, and yearly views plus home-screen widgets. The goal is glanceable feedback that lives mostly in the periphery and only asks for attention when needed.

The problem

Apple’s Activity rings feel good in the moment, and workout lists are detailed, but neither gives me a stable picture of how the month is going or whether a streak is forming how I’m actually doing over time. I wanted a view that made consistency visible at a glance and made gaps obvious without digging.

The solution

FitGrid visualizes each day as a cell. Darker cells mean more activity. Clusters and gaps pop out without reading numbers, leveraging basic preattentive perception so the eye does the work. Widgets keep your activity top-of-mind without nagging.

Personally, I play tennis and cycle almost daily. When a busy week hits, one look at the grid shows a hole I want to fill. That tiny nudge has helped me keep my rhythm, which is why the widget lives on my first home screen. And it is a fun way to visualize how life comes in waves and cycles.

How it works

• Pulls workouts from Apple Health collected by a wearable like Apple Watch and aggregates by day.
• Computes a simple intensity score (duration) for each cell.
• Renders the same visual grammar across week / month / year so zooming doesn’t require relearning.
• Updates widgets automatically so the grid stays current with near-zero interaction.

Key features

• Grid view of workout streaks
• Weekly, monthly, yearly insights
• Widgets for instant activity snapshots
• Automatic Apple Health sync
• Free to use

Research alignment

• Habit formation: FitGrid aims to strengthen contextual cues and repetition by making today’s action (filling one cell) concrete, aligned with evidence that consistent repetition in a stable context builds habits over time.
• Personal informatics: The design follows the stage-based model of low-friction collection, always-available reflection (the grid), and a clear path to action (do any workout to darken today’s cell).
• Glanceable / peripheral feedback: The grid and widgets are built for quick, low-effort checks that minimize attentional cost, consistent with best practices for glanceable peripheral displays and calm technology.
• Perceptual grounding: Using consistent color and position taps preattentive vision so streaks and gaps are immediately visible without numeracy demands.
• Pathways to embodiment is something I’d like to explore: The same signals could be exposed to an agent or robot to negotiate timely, context-aware nudges (e.g., “streak at risk” near day’s end) while respecting attention.

In short: FitGrid is a simple interface that makes consistency visible. By keeping feedback clear, stable, and largely peripheral, it supports the everyday work of behavior change.