SleeveStat
Project Overview
Role: Hardware Engineering, Firmware, Industrial Design
Tools: Arduino, Autodesk Fusion, Soldering, Flex Sensors
Duration: 1 Week
SleeveStat is a physical computing prototype that uses a wearable compression sleeve and flex sensors to detect and count push-up repetitions in real-time. The project features dynamic sensor calibration to adapt to different users and displays live data on a custom-housed 7-segment display.
Objective: Design and engineer a fully integrated prototype that utilizes digital logic to translate physical sensor input into a functional visual output
Inspiration
Wearable Tech
I've always been fascinated by how products like Whoop and Garmin can optimize human performance.
Accuracy
While these products are highly effective in tracking endurance and workouts, I noticed consistent inaccuracy when it came to bodyweight movements —specifically push-ups.
Ideation

Sensor
I landed on a Flex Sensor because it directly measures the angle of the elbow joint, allowing for a more reliable way to track repetition depth and accuracy.
Wearable
I decided to use a compression sleeve to house the sensor because it keeps the component perfectly aligned with the elbow while remaining unnoticeable to the athlete during exercise.

Digital Logic
Dynamic Calibration
I programmed a sequence that averages 20 initial readings to establish a unique "neutral baseline" at the start of each session, allowing the device to calibrate to the user's specific neutral form with a single button press.
Detection
To count a push-up, the user must cross the bend threshold and the count only increments once the user returns to their "neutral baseline" to prevent partial reps.
Hardware

Display
I integrated a 4-digit 7-segment display to provide immediate visual feedback.
Sodering
To transition from a bulky breadboard to a compact prototype, I hand-sodered many parts of the circuit.
Industrial Design
3D Modeling
I used Autodesk fusion to engineer a custom, two-part enclosure to house the Arduino and display.


3D Printing
The housing was manufactured using PLA.

Learnings & Takeaways
This project challenged me to bridge the gap between digital logic and physical interaction by working with a functional wearable product. I learned how to manage low-level sensor data, implement real-time calibration, and design durable enclosures for a high-intensity athletic environment.
Beyond the code, I gained experience in industrial design and electrical assembly. Managing the wire density within a compact, 3D-printed housing taught me the importance of spatial constraints.
If I were to evolve my prototype, I would implement multi-modal workout tracking. Since the current systems relies on just tracking pushups based off elbow bend, the code could be expanded to include modes for different exercises.
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