Investigation of an intelligent system for fiber optic-based epidural anesthesia.
Even though there have been many approaches to assist the anesthesiologists in performing regional anesthesia, none of the prior arts may be said as an unrestricted technique. The lack of a design that is with sufficient sensitivity to the targets of interest and automatic indication of needle placement makes it difficult to all-round implementation of field usage of objectiveness. In addition, light-weight easy-to-use realization is the key point of portability. This paper reports on an intelligent system of epidural space identification using optical technique, with particular emphasis on efficiency-enhanced aspects. Statistical algorithms, implemented in a dedicated field-programmable hardware platform along with an on-platform application-specific integrated chip, used to advance real-time self decision making in needle advancement are discussed together with the feedback results. Clinicians' viewpoint of improving the correct rate of our technique is explained in detail. Our study demonstrates not only that the improved system is able to behave as if it is a skillful anesthesiologist but also it has potential to bring promising assist into clinical use under varied conditions and small amount of sample, provided that several concerns are addressed.
Department of Electrical Engineering, School of Electrical and Computer Engineering, College of Engineering and Portable Energy System Group of Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan.
Cihun-Siyong Alex
0000-0001-9414-3798
CS
Gong
Department of Anesthesiology, Taipei Veterans General Hospital and National Yang-Ming University, Taipei 112, Taiwan.
Chien-Kun
CK
Ting
D000465:Algorithms; D000767:Anesthesia, Epidural / Q000295:instrumentation / Q000379:methods*; D000818:Animals; D004824:Epidural Space; D005336:Fiber Optic Technology / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D023421:Models, Animal; D013552:Swine