Research and Development of Thought Input Systems for Patients with Amyotrophic Lateral Sclerosis (ALS)

With the launch of the "Ice Bucket Challenge", ALS, commonly known as amyotrophic lateral sclerosis (ALS), has gradually attracted wider attention in recent years. It is a progressive neurodegenerative disease characterized by the decline of motor neuron function. As the disease progresses, patients often experience symptoms such as muscle atrophy, weakness, and communication difficulties, leading to social isolation and reduced interaction. Based on brain-computer interface (BCI) technology, this project designs an intention recognition automatic output device. By collecting neural activity and converting it into recognizable intention signals, when the user looks at visual stimuli of a specific frequency, the visual cortex will produce steady-state visual evoked potentials (SSVEPs), which will be detected by the electroencephalogram (EEG) system and decoded through artificial intelligence deep learning algorithms. These recognized signals are converted into instructions for automated equipment to accurately control computer operations, allowing patients to use computers for text input and editing, significantly improving the convenience of communication and interaction in patients' daily lives.