Unshackled

UnShackled is a project I've been working on for the past 2 years with my colleague Hriday Parekh.

UnShackled is an Arduino-nano based wearable assistive glove designed to diagnose, monitor, and actively suppress hand tremors, particularly those associated with Parkinson’s Disease and Essential Tremor. The project began as a question, can tremors be counteracted in real time using physics rather than medication alone, and evolved into a system that blends sensing, signal processing, and mechanical control.

The glove integrates accelerometers, gyroscopes, flex and force sensors, and vibration sensors to capture fine-grained motion data from the hand. Using frequency-domain analysis, including Fourier-based methods, the system identifies tremor intensity and type in real time. This data is processed on an embedded controller and communicated to a control algorithm that adapts dynamically to the user’s movement rather than applying a static correction.

To actively reduce tremors, UnShackled employs a wheel-based tuned mass damper mechanism driven by N20 high-speed motors mounted strategically on the hand. By generating counter-oscillations matched to the detected tremor frequency, the system aims to nullify up to 95 percent of tremor amplitude without restricting voluntary motion. The design prioritizes balance, responsiveness, and user comfort, ensuring that stabilization feels natural rather than forced.

Beyond its mechanical and computational core, UnShackled is rooted in accessibility and clinical relevance. The long-term goal is to provide clinicians with actionable tremor data while giving users a non-invasive, adaptable tool that restores confidence in everyday tasks. For me, UnShackled represents engineering at its best, where physics, empathy, and real-world impact converge to solve a deeply human problem.