Project

# Title Team Members TA Documents Sponsor
82 Real-Time Form Correction Device
 Bhanu Kunam
Ishank Pujari
Sree Akkina
 Po-Jen Ko proposal1.pdf
Team Members:
- Bhanuprakash Kunam (bkunam2)
- Sree Akkina (sakkina2)
- Ishank Pujari (ipuja2)

# Problem

Free weight exercises (dumbbells/barbells) require intense focus, and users often cannot safely look at visual displays while performing complex movements. Additionally, beginners frequently suffer from poor form - such as wobbling or using momentum rather than muscle control - which is difficult to self-diagnose without a personal trainer.

# Solution

This project proposes the “Smart-Clip,” an IoT attachment for barbells and free weights that utilizes auditory feedback to correct form in real-time. The system aims to use an ESP32 microcontroller and a 6-axis IMU to analyze the lift’s stability and trajectory. A piezoelectric buzzer provides sound cues: a “clean” tone confirms a stable, good-form repetition, while a dissonant alert signals excessive wobble or dangerous acceleration. This allows the user to maintain safe positioning while receiving instant coaching on their technique. All form data is logged to an app via Bluetooth for post-workout analysis.

# Solution Components

## Data Acquisition (Sensing)

The physical clip attaches securely to the dumbbell handle. Inside, a 6-axis Inertial Measurement Unit (IMU) continuously monitors the weight’s movement in 3D space. The Accelerometer measures the velocity of the lift (is the user moving too fast/jerking the weight?). The Gyroscope measures rotational stability (is the user’s wrist wobbling or tilting effectively?)

## On-Device Processing

The ESP32 microcontroller acts as the central processing unit. Instead of sending raw, noisy data to the phone, the ESP32 performs Edge Computing. Noise Filtering applies a smoothing filter to ignore small hand tremors. The Form Analysis Algorithm compares the motion vector against a “Gold Standard” vertical path. If the vector deviates sideways (wobble) or accelerates beyond a safety threshold (momentum), the system flags the repetition as “Poor Form.”

## Feedback Generation (The Interface)

The system employs a dual-loop feedback mechanism to provide both real-time coaching and long-term analytics. For immediate, a passive piezoelectric buzzer emits distinct auditory cues: a sharp, high-pitched beep confirms a valid repetition with proper form, whereas a low, dissonant buzz alerts the user to instability or dangerous acceleration. In parallel, the device utilizes Bluetooth Low Energy (BLE) to transmit detailed performance metrics, such as total count, lift tempo, and stability scores, to a companion mobile application, allowing users to review their workout history and track progress over time.

## App

The companion mobile application serves as the centralized hub for workout analytics, receiving data from the Smart-Clip via Bluetooth Low Energy (BLE). It records all session metrics, including repetition counts, tempo, and stability scores, locally on the device, allowing users to track and analyze their long-term progress through historical graphs and trend reports. Beyond data storage, the app acts as a control interface, enabling users to customize the clip’s sensitivity thresholds and audio feedback settings to match their specific training regimen.

# Criterion For Success

1. Repetition Accuracy: Counts bicep curls with = 90% accuracy; detects > 15 degrees wobble in >= 9/10 trials with no false alerts on clean reps.

3. Feedback Latency: Audio feedback occurs within 200 ms of IMU-detected rep completion.

4. Bluetooth Integrity: 100% of completed sets transmit correctly to the app within a 2 m range.

5. Mechanical Stability: Clip rotates less than 10 degrees on the handle during a 10-rep set.

6. Power Efficiency: Operates for at least 1 hour with average current draw under 100 mA.

Electronic Replacement for COVID-19 Building Monitors @ UIUC

Patrick McBrayer, Zewen Rao, Yijie Zhang

Featured Project

Team Members: Patrick McBrayer, Yijie Zhang, Zewen Rao

Problem Statement:

Students who volunteer to monitor buildings at UIUC are at increased risk of contracting COVID-19 itself, and passing it on to others before they are aware of the infection. Due to this, I propose a project that would create a technological solution to this issue using physical 2-factor authentication through the “airlock” style doorways we have at ECEB and across campus.

Solution Overview:

As we do not have access to the backend of the Safer Illinois application, or the ability to use campus buildings as a workspace for our project, we will be designing a proof of concept 2FA system for UIUC building access. Our solution would be composed of two main subsystems, one that allows initial entry into the “airlock” portion of the building using a scannable QR code, and the other that detects the number of people that entered the space, to determine whether or not the user will be granted access to the interior of the building.

Solution Components:

Subsystem #1: Initial Detection of Building Access

- QR/barcode scanner capable of reading the code presented by the user, that tells the system whether that person has been granted or denied building access. (An example of this type of sensor: (https://www.amazon.com/Barcode-Reading-Scanner-Electronic-Connector/dp/B082B8SVB2/ref=sr_1_11?dchild=1&keywords=gm65+scanner&qid=1595651995&sr=8-11)

- QR code generator using C++/Python to support the QR code scanner.

- Microcontroller to receive the information from the QR code reader and decode the information, then decide whether to unlock the door, or keep it shut. (The microcontroller would also need an internal timer, as we plan on encoding a lifespan into the QR code, therefore making them unusable after 4 days).

- LED Light to indicate to the user whether or not access was granted.

- Electronic locking mechanism to open both sets of doors.

Subsystem #2: Airlock Authentication of a Single User

- 2 aligned sensors ( one tx and other is rx) on the bottom of the door that counts the number of people crossing a certain line. (possibly considering two sets of these, so the person could not jump over, or move under the sensors. Most likely having the second set around the middle of the door frame.

- Microcontroller to decode the information provided by the door sensors, and then determine the number of people who have entered the space. Based on this information we can either grant or deny access to the interior building.

- LED Light to indicate to the user if they have been granted access.

- Possibly a speaker at this stage as well, to tell the user the reason they have not been granted access, and letting them know the

incident has been reported if they attempted to let someone into the building.

Criterion of Success:

- Our system generates valid QR codes that can be read by our scanner, and the data encoded such as lifespan of the code and building access is transmitted to the microcontroller.

- Our 2FA detection of multiple entries into the space works across a wide range of users. This includes users bound to wheelchairs, and a wide range of heights and body sizes.