Dual-IMU Wearable System for Gait Analysis and Knee Load Estimation; A Kantian Analysis of Boeing’s Actions in the Lion Air Flight 610 Crash 22 views

My technical capstone project and my STS research paper both focus on how complex systems make decisions when operating with limited or imperfect information, and how those decisions ultimately affect the people who depend on them. In my technical work, I focus on a wearable gait analysis system that uses sensor data to estimate joint behavior and provide feedback to users. In my STS paper, I analyze the Boeing 737 MAX MCAS case and how information about the system was handled during design and certification. Even though these projects are in different domains, they are both connected with the same underlying issue: when systems interpret data and produce outputs that users depend on, the way information is processed and communicated becomes critical. This connection highlights how engineering decisions affect not only system performance, but also how users understand system behavior and trust the system’s feedback. In my technical project, I worked on a gait analysis system using Inertia Measurement Unit sensors to provide users with personalized feedback on their running or walking mechanics. The system uses two sensors placed on user’s thigh and calf to collect acceleration and orientation data. Compared to single-sensor systems, this multi-sensor setup allows for a more detailed analysis of joint-level behavior and coordination. The collected data is processed in a machine learning model to estimate joint loading, such as stress on the knee. Abnormalities and imbalance in user’s form will be detected from their movement patterns. Based on this analysis, the system provides feedback to users through a simple interface, helping them adjust their form and reduce injury risk. The goal of the project is to give users more meaningful insight into the causes of their movement patterns. In my STS research paper, I use Kantian duty ethics to evaluate Boeing’s decisions during design and certification process for the MCAS system in the 737 MAX. My argument is that Boeing acted unethically because it failed to respect pilots as rational decision-makers by withholding key system information. I also argue that Boeing violated the duty of honesty by minimizing the system’s authority and behavior during certification process. From a Kantian perspective, these actions were not only regulatory issues but also moral failures because they prevent affected actors from making informed and rational judgments. I further show that this approach cannot be universalized, because if all companies concealed or minimized critical system functions, it would undermine trust and safety in safety-critical engineering systems. Working on both projects helped me understand more clearly how technical design and ethical responsibility are connected. The STS paper influenced how I think about system design by showing that trust is shaped by what the system chooses to reveal through its structure. This made me reflect on my technical project, where I began to see data processing and model outputs not just as computational steps, but as parts of a larger system. This system shapes how users interpret their own movement and make decisions about their health. At the same time, the technical project made me think more concretely about how systems transform raw data into conclusions. From sensing to inference, each step in the system introduces uncertainties to the output. Putting these two perspectives together made me realize that engineering is not only about producing accurate results, but also about ensuring that those results are understandable and reliable to the people who depend on them. In future work, I will apply this insight by paying more attention to how system design influences transparency, user understanding, and trust in real-world applications.

BS (Bachelor of Science)

Gait Analysis; IMU; Knee Load; Boeing 737MAX; Kantian Analysis

School of Engineering and Applied Science Bachelor of Science in Electrical Engineering Technical Advisor: Keith Williams STS Advisor: Benjamin Laugelli Technical Team Members: Anson Lu, Talha Bhutta, Rohina Naqshbandi, Megan Chhu, Sonia Aung

English

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2026-05-09