具有智能功能的脑控轮椅
Brain Controlled Wheelchair with Smart Feature
AI总结：
针对瘫痪者无法使用传统轮椅的问题，本文提出基于 EEG 与眨眼检测、结合 Arduino、多传感器和 Android 应用的智能电动轮椅，实现避障、烟雾和跌落报警。
摘要：
在亚洲，许多残障人士依靠轮椅出行。然而，部分人群（例如完全失能或瘫痪者）尽管认知能力完全正常，却无法使用传统轮椅。为解决这一问题，我们提议开发一种可通过 EEG 信号和眨眼进行控制的电动轮椅。该项目利用 MindWave Mobile 设备和 Arduino 实现无缝控制。此外，系统还集成了多种传感器以提升可靠性：超声波传感器有助于避免意外碰撞，烟雾传感器则检测危险烟雾浓度，并通过向指定人员发送短信触发自动警报。同样，如果乘坐者从轮椅上跌落，系统也会发送通知。轮椅的移动通过 Android 应用程序控制，眨眼检测作为导航的主要输入方式。这一创新设计提供了高性价比的解决方案，使其能够被广泛使用。通过集成这些先进功能，该系统可部署于机动轮椅，以更好地支持残障人士并增强其独立性。
英文摘要：
In Asia, many individuals with disabilities rely on wheelchairs for mobility. However, some people, such as those who are fully disabled or paralyzed, cannot use traditional wheelchairs despite having fully functioning cognitive abilities. To address this issue, we propose the development of an electric wheelchair that can be controlled using EEG signals and eye blinks. The project utilizes a MindWave Mobile device and Arduino to enable seamless control. Additionally, various sensors are incorporated to enhance the system's reliability. An ultrasonic sensor helps avoid unexpected collisions, while a smoke sensor detects hazardous smoke levels, triggering an automatic alert via a short message to a designated person. Similarly, if the passenger falls from the wheelchair, a notification will also be sent. The wheelchair's movement is controlled via an Android application, with eye-blink detection serving as the primary input method for navigation. This innovative design offers a cost-effective solution, making it accessible for widespread use. By integrating these advanced features, the system can be implemented on motorized wheelchairs to better support individuals with disabilities and enhance their independence.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
