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Design and Validation of an FPGA-Based Configurable Transcranial Doppler Neurofeedback System for Chronic Pain Patients

机译:基于FPGA的慢性疼痛患者可配置经颅多普勒神经反馈系统的设计与验证

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摘要

Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions.
机译:神经反馈是一种自我调节技术,可用于学习自愿控制特定大脑区域的大脑活动。在这项工作中,提出并描述了一种基于经颅多普勒的可配置神经反馈系统。硬件配置基于Red Pitaya主板,它为系统提供了极大的灵活性和处理能力。可以从不同血管中的脑血流速度信号中的几个时间,频谱或复杂性特征中选择要训练的参数。由于先前的研究已经发现慢性疼痛患者的这些参数发生了变化,因此该系统可用于帮助他们自愿控制这些参数。已经提出了两种基于训练时间的不同时长的方案,并与六名健康受试者进行了测试,这些受试者在手术开始时被随机分配给方案之一。为了进行测试,训练的参数是来自两个前脑动脉的汇总数据中的平均脑血流速度。结果表明,使用拟议的神经反馈系统,两组健康志愿者可以通过减少训练次数来从大脑活动中学习自我调节参数。

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