Steady

Final Product!
Final Product!
Demo of our application
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Inspiration

Hand tremors, caused by conditions like Parkinson’s disease, essential tremor, or even anxiety and medications, disrupt daily tasks such as eating, writing, and using a phone. Affecting over 10 million Parkinson’s patients and 5% of people over 65 globally, tremors lead to reduced independence, social isolation, and emotional distress. In fact, over 60% of individuals with tremors report avoiding social situations due to embarrassment. With the prevalence of tremor-related conditions expected to rise, there is a growing need for non-invasive, wearable solutions to enhance motor control and improve quality of life.

What it does

The Steady glove is a wearable device designed to suppress hand tremors in real time, offering a practical solution for individuals with Parkinson’s disease, essential tremor, or other conditions that cause involuntary hand movements. The glove uses an MPU6050 accelerometer to continuously monitor and detect tremor patterns along multiple axes. This data is processed by an Arduino-based control system that determines the intensity and direction of the tremors. When detected, reaction wheels driven by DC motors generate precise opposing torque to stabilize the user’s hand and reduce tremor effects.

How we built it

At its core, the device uses an MPU6050 accelerometer, which continuously monitors hand movements along the X, Y, and Z axes. This sensor is connected to an Arduino Uno, where a custom algorithm processes the data to detect involuntary tremors. The Arduino then communicates with an L298N motor driver, which controls two DC motors attached to reaction wheels. The reaction wheels generate opposing torque to counteract the tremors in real time. The system is powered by a 9V battery, providing portability and flexibility for real-world use. To complete the design, we mounted the components onto a glove, ensuring the motors and reaction wheels were positioned to maximize stabilization without restricting hand movement. Through iterative testing and debugging, we refined the balance between sensitivity and motor response, creating a functional prototype capable of reducing hand tremors effectively.

Challenges we ran into

As a team with a software background, integrating hardware components like the MPU6050 accelerometer, Arduino, and motor driver posed several challenges. We faced issues with I2C communication, wiring errors, and library compatibility, which required extensive troubleshooting. Calibrating the accelerometer to distinguish involuntary tremors from normal hand movements was particularly difficult, as overly sensitive settings triggered false responses. Power management also proved challenging, as we had to balance motor performance with efficient battery usage. Despite these obstacles, iterative testing and persistence allowed us to build a fully functional prototype.

Accomplishments that we're proud of

We are proud of successfully integrating the MPU6050 accelerometer with the Arduino and achieving real-time tremor detection and suppression. Despite initial challenges, we developed a fully functional prototype capable of detecting involuntary hand movements and counteracting them using reaction wheels driven by motors. Another key accomplishment was writing and optimizing the control algorithm to ensure precise motor response based on the intensity of the tremors.

What we learned

We learned a lot working with Arduinos in both the hardware, software, and debugging aspects. Additionally, this being our very first hackathon, we learned a lot about the format of hackathons and the overall workarounds.