Julien Chagnon

I developed a complete human activity recognition system that processes raw smartphone accelerometer data to distinguish between walking and jumping. Following a structured workflow encompassing data collection, hierarchical HDF5 storage, signal visualization, preprocessing, feature extraction and normalization, classifier training, and GUI deployment, we leveraged Python’s scientific stack (pandas, h5py, scipy, scikit-learn) to import CSV files from an accelerometer app, clean and smooth the time series with forward-fill and moving-average filters, extract a suite of 40 statistical features per 5-second window, train a logistic regression classifier to over 95% accuracy, and finally package the process into a Tkinter desktop application.

The project followed the Agile Scrum methodology, with development structured around two-week sprints. Our programming was also managed through GitLab, with each feature tracked through milestones, issues, and merge requests across team members.

As part of a client-based design project, our team partnered with the Toronto Police Service to modernize the Perfex training device, a 911 dispatcher testing platform built around manual time checks and paper-based modules that is becoming outdated. We translated all five original test stations (short-story recall, reading aloud, copying critical information, simulated telephone dispatch, and map indexing) into a cohesive web interface seamlessly integrated with an Arduino taskbox housed in a portable briefcase with the goal of increasing test accuracy and repeatability.

Specifically, my roles included translating the physical layout of the original Perfex device into the physical Arduino taskbox, mapping push-buttons, sliders, and rotary encoders to mirror the look and feel of the legacy device's five stations. I co-developed the embedded Arduino code that generated physical stimuli tests through user prompts, timestamping every user action and allowing me to implement a real-time scoring system.

On the web side, I also aided our team to develop an HTML, CSS, and JavaScript web interface that replaced all paper testing modules with a modern interactive experience. Audio prompts are streamed using the Web Audio API, and spoken responses are recorded in-browser using MediaRecorder. For interactive modules like map indexing and transcription, the website validates answers in real time against expected inputs and calculates both accuracy and reaction times. Once all modules are complete, results are sent to a Node.js server which stores the data and generates a downloadable PDF report.

As part of a semester-long engineering design project in first year, I worked on the development of an Automated Fluid Dispenser designed for precise, autonomous mixing of pharmaceutical solutions within strict space, material, and safety constraints. The team prepared and submitted interim reports at key milestones.

My contributions to the project focused heavily on both the system design and the software development. I wrote the complete Arduino C++ codebase, which included coordinating three subsystems: a servo-powered powder dispensing mechanism, a motor rotating turntable, and a peristaltic pump liquid delivery system. The code used arrays to store and iterate over preset dosing instructions for five test tubes dispensing increments between 1 g and 2 g of powder per tube (± 0.2 g) and delivering 20 mL of liquid per tube, controlled with start and emergency stop buttons. I implemented precision timing and motion control logic to ensure accurate dosing, along with real-time interrupt checks for safety overrides.

As a personal web development project, I designed and built this portfolio website from the ground up using HTML, CSS, and JavaScript to showcase my skills, projects, and experience in an interactive format. The website is hosted on GitHub Pages and configured to use a custom domain.

In CSS, I implemented responsive design through dynamic viewport units to ensure optimal viewing across all devices. For instance, media queries detect viewports under 768px and automatically disable floats, stacking content vertically and converting all images to full width for improved readability on smartphones. To observe this firsthand, try changing your browser window width to watch the content wrap dynamically!

I developed JavaScript logic that powers all dynamic behaviors across the site. Mainly an interactive terminal that supports tab autocompletion, arrow key history recall using an array-based history buffer, and localized English and French command sets. The terminal dynamically adjusts its position from absolute to fixed based on scroll depth, with smooth transitions preventing visual jumps. I also included a French version of the entire website by toggling the lang class on the <body> element and dynamically swapping all visible content using data attributes. Another significant element is the matrix-inspired binary rain animation that responds to scroll velocity; moving upward when scrolling down and vice versa, with digit changes on a timed interval for visual interest. Other dynamic elements include a custom scrollbar that interpolates color from white to the primary theme color based on scroll position, and a sidebar with smooth position transitions triggered by scroll events.