Hirasawa Ai, Kaneko Takahito, Tanaka Naoki, Funane Tsukasa, Kiguchi Masashi, Sørensen Henrik, Secher Niels H, Ogoh Shigehiko
Graduate School of Engineering, Toyo University, Kawagoe-shi, Saitama, Japan.
Department of Biomedical Engineering, Faculty of Science and Engineering, Toyo University, 2100 Kujirai, Kawagoe-shi, Saitama, 350-8585, Japan.
J Clin Monit Comput. 2016 Apr;30(2):243-50. doi: 10.1007/s10877-015-9709-4. Epub 2015 May 29.
We estimated cerebral oxygenation during handgrip exercise and a cognitive task using an algorithm that eliminates the influence of skin blood flow (SkBF) on the near-infrared spectroscopy (NIRS) signal. The algorithm involves a subtraction method to develop a correction factor for each subject. For twelve male volunteers (age 21 ± 1 yrs) +80 mmHg pressure was applied over the left temporal artery for 30 s by a custom-made headband cuff to calculate an individual correction factor. From the NIRS-determined ipsilateral cerebral oxyhemoglobin concentration (O2Hb) at two source-detector distances (15 and 30 mm) with the algorithm using the individual correction factor, we expressed cerebral oxygenation without influence from scalp and scull blood flow. Validity of the estimated cerebral oxygenation was verified during cerebral neural activation (handgrip exercise and cognitive task). With the use of both source-detector distances, handgrip exercise and a cognitive task increased O2Hb (P < 0.01) but O2Hb was reduced when SkBF became eliminated by pressure on the temporal artery for 5 s. However, when the estimation of cerebral oxygenation was based on the algorithm developed when pressure was applied to the temporal artery, estimated O2Hb was not affected by elimination of SkBF during handgrip exercise (P = 0.666) or the cognitive task (P = 0.105). These findings suggest that the algorithm with the individual correction factor allows for evaluation of changes in an accurate cerebral oxygenation without influence of extracranial blood flow by NIRS applied to the forehead.
我们使用一种消除皮肤血流(SkBF)对近红外光谱(NIRS)信号影响的算法,对手握力运动和认知任务期间的脑氧合进行了估计。该算法涉及一种减法方法,为每个受试者制定一个校正因子。对于12名男性志愿者(年龄21±1岁),通过定制的头带袖带在左颞动脉上施加+80 mmHg的压力30秒,以计算个体校正因子。利用该算法和个体校正因子,在两个源探测器距离(15和30毫米)下,从NIRS测定的同侧脑氧合血红蛋白浓度(O2Hb)中,我们得出了不受头皮和颅骨血流影响的脑氧合情况。在脑神经激活(手握力运动和认知任务)期间,验证了估计的脑氧合的有效性。使用这两个源探测器距离时,手握力运动和认知任务会使O2Hb增加(P<0.01),但当通过对颞动脉施加压力5秒消除SkBF时,O2Hb会降低。然而,当脑氧合估计基于对颞动脉施加压力时开发的算法时,在手握力运动(P = 0.666)或认知任务(P = 0.105)期间,估计的O2Hb不受SkBF消除的影响。这些发现表明,具有个体校正因子的算法能够在不受到应用于前额的NIRS的颅外血流影响的情况下,评估准确的脑氧合变化。