Description: This endeavor revolves around an extensive survey of cutting-edge research in the domain of gait phase detection, with a particular focus on its implications for prosthetic design. Our review not only offers a comprehensive summary of current research but also paves the way for future investigations in this dynamic field.
Key Insights:
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IMU Sensors in Gait Detection: Our survey highlights the prevalence of Inertial Measurement Unit (IMU) sensors in gait phase and event detection systems. IMUs are favored for their suitability in long-term daily activity applications, offering advantages in terms of energy efficiency, durability, cost-effectiveness, lightweight design, portability, and ease of placement. Moreover, IMU signals prove versatile and applicable in various gait phase detection methodologies.
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Gait Phase Granularity: While achieving 100% accuracy in detecting two gait phases using various methods is feasible, the challenge arises when aiming for higher granularity. As granularity increases, accuracy often decreases within the same detection system. To address this challenge, our project explores the integration of hybrid and complex algorithms, as well as the inclusion of additional parameters, which have shown promise in enhancing results.
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Signal Post-Processing: Effective signal post-processing is essential to mitigate errors, drift, and noise, thereby ensuring high detection performance. However, it's important to balance these enhancements with the potential introduction of delays, especially in real-time applications where minimal detection delay is critical.
Contribution: This project serves as a valuable resource for researchers and developers in the fields of gait analysis and prosthetic design. It compiles state-of-the-art findings and identifies key areas for future research, aiding in the optimization of gait phase detection systems for prosthetic applications.