A brain-computer typing interface using finger movements.

Nishal P Shah, Matthew S Willsey, Nick Hahn, Foram Kamdar, Donald T Avansino, Leigh R Hochberg, Krishna V Shenoy, Jaimie M Henderson
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Abstract

Intracortical brain computer interfaces (iBCIs) decode neural activity from the cortex and enable motor and communication prostheses, such as cursor control, handwriting and speech, for people with paralysis. This paper introduces a new iBCI communication prosthesis using a 3D keyboard interface for typing using continuous, closed loop movement of multiple fingers. A participant-specific BCI keyboard prototype was developed for a BrainGate2 clinical trial participant (T5) using neural recordings from the hand-knob area of the left premotor cortex. We assessed the relative decoding accuracy of flexion/extension movements of individual single fingers (5 degrees of freedom (DOF)) vs. three groups of fingers (thumb, index-middle, and ring-small fingers, 3 DOF). Neural decoding using 3 independent DOF was more accurate (95%) than that using 5 DOF (76%). A virtual keyboard was then developed where each finger group moved along a flexion-extension arc to acquire targets that corresponded to English letters and symbols. The locations of these letter/symbols were optimized using natural language statistics, resulting in an approximately a 2× reduction in distance traveled by fingers on average compared to a random keyboard layout. This keyboard was tested using a simple real-time closed loop decoder enabling T5 to type with 31 symbols at 90% accuracy and approximately 2.3 sec/symbol (excluding a 2 second hold time) on average.

使用手指运动的脑机输入接口。
皮质内脑机接口(ibci)解码来自皮质的神经活动,为瘫痪患者提供运动和交流假肢,如光标控制、书写和语言。本文介绍了一种新的iBCI通信假体,该假体采用三维键盘界面,通过多个手指的连续闭环运动进行打字。为一名BrainGate2临床试验参与者(T5)开发了一种特定于参与者的脑机接口键盘原型,该原型使用的是来自左运动前皮层把手区域的神经记录。我们评估了单个手指(5自由度)与三组手指(拇指,食指-中指和无名指-小指,3自由度)的屈伸运动的相对解码精度。使用3独立DOF的神经解码准确率(95%)高于使用5独立DOF的神经解码准确率(76%)。然后开发了一个虚拟键盘,每个手指组沿着弯曲-伸展弧线移动,以获取对应于英语字母和符号的目标。使用自然语言统计优化了这些字母/符号的位置,与随机键盘布局相比,平均手指移动的距离减少了大约2倍。该键盘使用简单的实时闭环解码器进行测试,使T5能够以90%的准确率输入31个符号,平均约2.3秒/个符号(不包括2秒的保持时间)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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