Project description
My project consist on the development of a Wearable device that monitors movement quality, to focus on the detection of early changes in motor control that are associated with mucular disftrophy with a system that analyzes motion pattern to identify the variability, smoothness and range, that serve as indicaions of functional deterioration
Project Concept & Design Sketch
The design of the wearable device focuses on ergonomics and portability, as it is intended for long-term monitoring of patients with neuromuscular conditions. The system is conceived as a modular bracelet located on the wrist or forearm, a strategic position to capture the most significant data regarding arm tremors, range of motion, and movement smoothness.
As illustrated in the conceptual sketch, the device integrates an Inertial Measurement Unit (IMU) containing an accelerometer and a gyroscope. This sensor captures raw data of acceleration, angular velocity, and time, which are then processed through the onboard firmware. The signal processing layer focuses on three main pillars: calculating the Range of Motion, analyzing Movement Variability, and measuring Movement Smoothness through jerk analysis.
The system is designed to be highly functional and user-centric. The output is simplified into two primary feedback methods: a numerical score ranging from 0 to 100, representing the progressive functional deterioration, and a visual "Traffic Light" system. This color-coded feedback, combined with haptic vibration and LED indicators, provides the user with early warnings and preventive alerts regarding their motor control status.
This "closed-loop" design ensures that the device is not just a data logger, but an active monitoring tool. By housing the power management, the processing unit, and the feedback interface within a compact wearable form factor, the bracelet becomes an autonomous unit ready for real-world clinical assessment.
Project Concept & Design Evolution
The system is conceived as a modular bracelet strategic to capturing significant data regarding arm tremors, range of motion, and movement smoothness. The initial functional logic, as defined in my very first rough sketch, centered on using the IMU to process Range of Motion, Movement Variability, and Smoothness, leading to a simple numerical score (0-100) and traffic light feedback system.
Building upon that initial logic, during Week 2, I advanced the concept by creating more detailed design representations. This iteration involved developing a specific visual form factor that transitions the theoretical device into a wearable product. These designs refine the aesthetics of the bracelet, defining the integration of the display and the overall look of the protective shell. You can explore the full computer-aided design process in the Week 2 documentation.
Simultaneously, I leveraged SolidWorks to develop a precise 3D model of the bracelet housing. This CAD iteration was crucial for defining the physical dimensions and component fit, establishing a foundation for future manufacturing. The resulting design features a robust yet streamlined casing that encapsulates the electronics and presents a clear visual interface for user feedback.
The transition from the very simple logical sketch to these detailed 3D representations highlights the early stages of product development, ensuring that the theoretical functional segments are grounded in a manufacturable and ergonomic hardware design.
Hardware Strategy & Motion Analysis
Following the electronics production path established in Week 4, the final device is planned to be powered by the Seeed Studio XIAO nRF52840 Sense. This specific microcontroller was selected because it already integrates a high-precision 6-axis IMU (gyroscope and accelerometer) within its compact footprint. To enhance this sensing capability, and building upon the principles discussed in Week 9, I plan to integrate an external magnetometer. By combining the data from the internal IMU with an external magnetometer, the system will achieve a full 9-axis orientation tracking, providing a much more stable and accurate reference for calculating movement quality.
The primary metric for assessing "smoothness" in this project is Jerk. In physics, Jerk is defined as the rate of change of acceleration over time (the third derivative of position). While acceleration tells us how fast the speed is changing, Jerk tells us how abruptly the acceleration itself is shifting. In a medical context, a "smooth" movement has low jerk values, whereas erratic, shaky, or uncontrolled movements—typical of muscular dystrophy or motor control loss—produce high jerk spikes. By monitoring these spikes, the device can quantify functional deterioration that might be invisible to the naked eye.
Interactive Kinematics: Understanding Jerk
Use the dropdown below to simulate the difference between a healthy, smooth movement and an uncontrolled, jerky movement. Notice how sudden steps in Acceleration translate into massive spikes in the Jerk graph.
Using the 9-axis fusion (Accelerometer + Gyroscope + Magnetometer), the firmware will be able to filter out gravitational noise and focus strictly on the Dynamic Jerk produced by the user. This data will be the foundation for the 0-100 quality score and the traffic light feedback system described in the initial conceptual sketches.