基于递推最小二乘自适应滤波和最小二乘支持向量机的近红外光谱脑活动测量生理干扰抑制。

IF 1.5 4区 医学 Q3 SURGERY
Xin Liu, Yan Zhang, Dan Liu, Qisong Wang, Ou Bai, Jinwei Sun, P. Rolfe
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引用次数: 0

摘要

近红外光谱技术是一种很有前途的无创技术,它可以通过监测血流动力学浓度的变化来检测脑功能的激活。获得的近红外光谱信号通常受到呼吸和心脏收缩引起的生理干扰的污染。采用最小均方算法的自适应滤波方法或基于多距离探头配置的递推最小二乘算法虽然可以提高脑活动诱发反应的质量,但这两种方法都只能去除头部组织浅层的生理干扰。为了克服这一缺点,我们将递归最小二乘自适应滤波方法与最小二乘支持向量机相结合,对头部组织的表层和深层进行生理干扰抑制。基于性能测量的量化结果表明,该方法对诱发血流动力学变化的估计性能优于传统的递推最小二乘法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physiological interference reduction for near infrared spectroscopy brain activity measurement based on recursive least squares adaptive filtering and least squares support vector machines.
Near infrared spectroscopy is the promising and noninvasive technique that can be used to detect the brain functional activation by monitoring the concentration alternations in the haemodynamic concentration. The acquired NIRS signals are commonly contaminated by physiological interference caused by breathing and cardiac contraction. Though the adaptive filtering method with least mean squares algorithm or recursive least squares algorithm based on multidistance probe configuration could improve the quality of evoked brain activity response, both methods can only remove the physiological interference occurred in superficial layers of the head tissue. To overcome the shortcoming, we combined the recursive least squares adaptive filtering method with the least squares support vector machine to suppress physiological interference both in the superficial layers and deeper layers of the head tissue. The quantified results based on performance measures suggest that the estimation performances of the proposed method for the evoked haemodynamic changes are better than the traditional recursive least squares method.
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来源期刊
Computer Assisted Surgery
Computer Assisted Surgery Medicine-Surgery
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
10 weeks
期刊介绍: omputer Assisted Surgery aims to improve patient care by advancing the utilization of computers during treatment; to evaluate the benefits and risks associated with the integration of advanced digital technologies into surgical practice; to disseminate clinical and basic research relevant to stereotactic surgery, minimal access surgery, endoscopy, and surgical robotics; to encourage interdisciplinary collaboration between engineers and physicians in developing new concepts and applications; to educate clinicians about the principles and techniques of computer assisted surgery and therapeutics; and to serve the international scientific community as a medium for the transfer of new information relating to theory, research, and practice in biomedical imaging and the surgical specialties. The scope of Computer Assisted Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotactic procedures, surgery guided by intraoperative ultrasound or magnetic resonance imaging, image guided focused irradiation, robotic surgery, and any therapeutic interventions performed with the use of digital imaging technology.
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