Marius-Valentin Drăgoi, Ionuț Nisipeanu, Aurel Frimu, Ana-Maria Tălîngă, Anton Hadăr, Tiberiu Gabriel Dobrescu, Cosmin Petru Suciu, Andrei Rareș Manea
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引用次数: 0
摘要
脑机接口(BCI)通过处理和转换大脑信号,向输出设备发出指令,以执行特定任务。BCI 的主要目的是替代或恢复残疾人缺失或受损的功能,包括肌萎缩侧索硬化症(ALS)、脑瘫、中风或脊髓损伤等神经肌肉疾病。因此,BCI 不使用神经肌肉输出通路,而是绕过传统的神经肌肉通路,直接解读大脑信号来指挥设备。科学家们已经使用了多种技术,如脑电图(EEG)、皮质内和皮质电图(ECoG)技术来收集大脑信号,用于控制机械臂、假肢、轮椅和其他一些设备。脑电图是一种用于收集和监测大脑信号的无创方法。在家庭自动化系统中采用基于脑电图的生物识别(BCI)技术可为残疾人的各种任务提供便利。在这种特殊情况下,帮助瘫痪人士使用现有的家庭自动化系统和小工具并增强其能力非常重要。本文提出了一种使用基于脑电图的生物识别(BCI)来控制门和灯的家庭安全系统。系统原型由 EMOTIV Insight™ 耳机、Raspberry Pi 4、用于开门/关门的伺服电机和 LED 灯组成。该系统可以极大地帮助残疾人,包括无法关闭或打开门或使用遥控器开关灯的手臂截肢者。该系统包括一个用 Flutter 制作的应用程序,用于在智能手机上接收与门和 LED 指示灯状态有关的通知。残疾人可以通过 EMOTIV Insight™ 耳机检测到的大脑信号控制门和 LED 灯。
Real-Time Home Automation System Using BCI Technology.
A Brain-Computer Interface (BCI) processes and converts brain signals to provide commands to output devices to carry out certain tasks. The main purpose of BCIs is to replace or restore the missing or damaged functions of disabled people, including in neuromuscular disorders like Amyotrophic Lateral Sclerosis (ALS), cerebral palsy, stroke, or spinal cord injury. Hence, a BCI does not use neuromuscular output pathways; it bypasses traditional neuromuscular pathways by directly interpreting brain signals to command devices. Scientists have used several techniques like electroencephalography (EEG) and intracortical and electrocorticographic (ECoG) techniques to collect brain signals that are used to control robotic arms, prosthetics, wheelchairs, and several other devices. A non-invasive method of EEG is used for collecting and monitoring the signals of the brain. Implementing EEG-based BCI technology in home automation systems may facilitate a wide range of tasks for people with disabilities. It is important to assist and empower individuals with paralysis to engage with existing home automation systems and gadgets in this particular situation. This paper proposes a home security system to control a door and a light using an EEG-based BCI. The system prototype consists of the EMOTIV Insight™ headset, Raspberry Pi 4, a servo motor to open/close the door, and an LED. The system can be very helpful for disabled people, including arm amputees who cannot close or open doors or use a remote control to turn on or turn off lights. The system includes an application made in Flutter to receive notifications on a smartphone related to the status of the door and the LEDs. The disabled person can control the door as well as the LED using his/her brain signals detected by the EMOTIV Insight™ headset.