Project Info
The rise of Artificial Intelligence and technological advancements has significantly boosted productivity for many. However, there's a noticeable gap in applying these innovations to aid the disabled and elderly. Addressing this, we created a transformative solution: a smart wheelchair prototype. This wheelchair is uniquely controlled by EEG signals, enabling mobility for those with paralysis, and offering older individuals the ability to move freely and continue their daily tasks without physical constraints. This project isn't just about mobility; it's about restoring independence and quality of life. Challenges Faced One of the primary technical challenges we faced was developing a reliable method for interpreting EEG signals into precise commands for the wheelchair. Capturing the electrical activity of the brain with the Muse 2 headset and translating it into actionable inputs required sophisticated signal processing algorithms. We had to ensure the system could accurately differentiate between intentional commands and involuntary brain activity. Additionally, integrating this technology into a wheelchair in a way that was both safe and effective presented its own set of engineering hurdles, including optimizing the system to reduce latency as much as possible. Our Mission Our mission extends beyond mobility. We aim to harness EEG signals as a bridge between machines and the human body. With additional funding, we plan to expand our technology to monitor stress levels and other vital metrics, utilizing EEG data to enhance mental health. This innovation will empower individuals to understand and manage their stress, paving the way for a healthier, more connected future. Technology and Innovation To achieve our goals, we utilized the Muse 2 headset to record EEG signals. This innovative approach allowed us to capture the electrical activity of the brain with precision. We then developed a system to interpret these signals, focusing on microaggressions like blinks and slight head movements, as inputs to control the movement of the wheelchair. This method of control is not only intuitive but also enables users with severe mobility restrictions to command the wheelchair effortlessly, showcasing our commitment to enhancing accessibility and independence through technology. Our smart wheelchair prototype is more than a mobility aid; it's a step towards a future where technology bridges the gap between disability and independence, enabling everyone to live their lives to the fullest. We believe in the power of innovation to change lives, and with the right support, we can make this vision a reality.
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Technology
- PythonIn code
1 of 1 appear in the indexed code.
AI coding agents
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Codebase size
Source size
12 KB
Source files
3
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Repository
Jasonnyang/TreeHacks
5 files · 18 KB · @ b55d087
Structure
Application logic
4 files · 80%Domain rules, services and shared utilities.
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Languages
- Python100%
- Markdown0%
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