Projects & Experiences
Philips Oral Healthcare Co-Op & Internship
I currently work on the systems engineering team for the Philips Oral Healthcare department, focusing on verification and validation of our product lines.
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A major achievement in my role has been re-engineering the high-speed video (HSV) verification testing methodology for oral irrigator products. I improved measurement accuracy by 70% through enhanced equipment design and automated image analysis. Using Python and OpenCV, I created a pipeline incorporating adaptive thresholding, contour detection, and histogram equalization to extract quantitative performance metrics from video data. I also fine-tuned Meta's SAM 2 model to enable automated segmentation of HSV frames.
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My other responsibilities include verifying and validating power toothbrush product lines, where I have authored over 80 test records using Windchill, Azure DevOps, and Minitab. I execute IQ/OQ/PQ protocols for new test equipment to ensure ISO 13485 compliance. Additionally, I have authored 19 updated design verification protocols and 6 equipment specifications to improve testing efficiency and alignment.
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Throughout these projects, I drive cross-functional collaboration between product development, functional development, verification/testing, and program management teams to establish standardized HSV measurement techniques across the organization.
As I continue in this role, I'm researching particle imaging velocimetry (PIV) testing options for advanced flow analysis of oral irrigator devices to better characterize fluid dynamics and optimize product performance.
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A METHOD FOR PLANTAR SHEAR FORCE MEASUREMENT
I developed a shear force measurement system that enables localized analysis of plantar forces during walking. Traditional pressure plates only provide single-point force measurements and directional data per contact area, but this system captures spatially distributed shear forces across the foot's surface.
This system is made up of a 3D array of posts that deflect in response to applied shear forces. I created the CAD models for the walkway and the integrated array. I validated the mechanical behavior through finite element analysis, simulating shear force application on individual posts to predict system response before physical prototyping. Physical prototyping consisted of machining and 3D printing all parts. Additionally, I developed a computer vision program for high-speed video footage using Python and OpenCV to track post displacement, converting displacement data into precise force measurements. To ensure accuracy, I created a transfer function that maps post displacement to shear force values by calibrating the system with known weights.
This approach offers significant advantages: it's considerably more affordable than existing localized shear measurement systems, making it accessible for widespread clinical use. The multi-point measurement capability is particularly valuable for identifying pressure hotspots in at-risk populations before they develop into ulcers. This is a critical application for diabetic patients and amputees. By enabling early intervention, this technology has the potential to prevent serious complications and improve outcomes for vulnerable populations.
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Development of an IMU-Based Tripping Motion Capture System
I developed and validated a portable ankle and foot motion capture system for outdoor use by comparing an inertial measurement unit (IMU) and distance sensor system against gold-standard optical motion capture. The goal of this research was to capture motion during tripping events to identify their underlying causes. My objective was to verify that IMU-based angular measurements and IR distance sensor data correlated accurately with camera-based motion capture during running, enabling reliable biomechanical analysis outside laboratory settings where tripping naturally occurs.
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I began by comparing Vicon Nexus optical motion capture with data from a SHARP IR Distance Sensor and SparkFun OpenLog Artemis IMU. I rotated an object up to simulate jogging foot motion and converted the IMU's quaternion outputs to Euler angles, allowing me to correlate marker coordinates with distance measurements and establish baseline sensor accuracy. I then validated the system during running trials with multiple test subjects, integrating the sensors using an Arduino Uno with a custom voltage divider circuit and designing 3D-printed mounts to secure the components to footwear.
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My results demonstrated that IMU-derived Euler angles aligned consistently with Vicon-calculated angles across subjects, and the distance sensor produced accurate measurements during dynamic motion. The validated system successfully enables biomechanical analysis of ankle and foot motion in outdoor environments where traditional optical motion capture cannot operate, providing a foundation for studying tripping mechanics in real-world settings.
Testing Ankle Braces for NBA Players
I contributed to a biomechanical research project at the U.S. Department of Veterans Affairs evaluating three ankle brace designs for NBA players using a robotic gait simulator and cadaveric feet. My role involved converting CT scans into precise 3D anatomical models of key ankle structures, including the tibia, fibula, talus, and calcaneus. I completed ~30 segmentations over the course of the project, with each model requiring approximately three hours of meticulous work to ensure anatomical accuracy. These models enabled the team to track foot and ankle movement over time, determining which brace design provided optimal support and stability.
