효과적인 뉴로피드백 훈련을 위한 임계값 설정 기법
Auto Thresholding for Efficient Neurofeedback Trainning
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참고문헌
키워드
초록
본 논문에서는 임계값 자동 설정 기능을 지원하는 효과적인 뉴로피드백 시스템을 제안한다. 실시간 뇌파의 신호 처리를 통해 보상 주파수와 억제 주파수에 대한 정확한 피드백을 생성하는 알고리즘을 설계하고, 이를 기반으로 치료사가 정한 목표 성공률을 얻기 위해 자동으로 임계값을 계산하는 기술을 제시한다. 본 논문에서 제시한 자동 임계값 설정 기술은 피험자의 이전 뇌파 패턴을 분석하여 목표 성공률과의 차이를 최소로하는 최적의 임계값을 계산한다. 다양한 조건의 실험을 통해 제안된 기법의 효율성과 안정성을 입증한다.
Abstract
We develop a complete system that includes data collection, signal processing, and real-time interaction for effective neurofeedback training. Our system supports a sophisticated technique to find threshold values which are quite important for effective neurofeedback system. A therapist specifies a target success rate of positive feedback, allowable error and time. The system computes a current success rate and compare it with the target one. If the difference between two rates exceeds the allowable error for allowable time, we find an optimum threshold value to obtain the target success rate by using numerical optimization technique. We conduct several experiments by varying input parameters: target success rate, allowable error and time, and demonstrate the effectiveness of our technique by showing the desired target success rate is stably obtained and systematically controlled by input parameters.
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