Abstract:
: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.
journal_name
Comput Assist Surg (Abingdon)journal_title
Computer assisted surgery (Abingdon, England)authors
Liu X,Zhang Y,Liu D,Wang Q,Bai O,Sun J,Rolfe Pdoi
10.1080/24699322.2018.1557901subject
Has Abstractpub_date
2019-10-01 00:00:00pages
160-166issue
sup1issn
2469-9322journal_volume
24pub_type
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