From the Medical Devices and Diagnostics Division, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN. Received Oct 1, 1993, and in revised form Oct 17, 1993. Accepted for publication Oct 20, 1993. Address correspondence to Dr Martin, Medical Devices and Diagnostics Division, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285. The term "fuzzy logic" arouses a bit of amusement in those who don't know what it is and sometimes a bit of apprehension in those who do. Yet this is an area with great potential for affecting our daily lives, both as health care providers and as just ordinary consumers. While it has been treated as an outcast in the United States, fuzzy logic has been embraced in Japan, where consumers can purchase a variety of fuzzy appliances. In Japan, you can toss a load of clothes into a fuzzy washer, press a single button, and the machine automatically chooses the best cycle based on load size, fabric, and the kind of dirt or stain on the clothes. You can place a variety of frozen dinners or leftovers into a fuzzy microwave, push a single button, and it cooks for the right time at the proper power, based on temperature, humidity, and change in food shapes. They also have fuzzy camcorders, fuzzy televisions, and cars that employ fuzzy logic. This editorial describes fuzzy logic and some of its uses in anesthesia. In particular, it discusses the paper by Tsutsui and Arita [1], published in this issue of Journal of Clinical Monitoring. To understand fuzzy logic, we must first understand a fuzzy set. What is a fuzzy set? The following gives a simple numerical example. Most people would find it easy to determine membership in the set "positive integers" (PosInt). Clearly 1, 100, 10,000, 1,000,000, and 109 are all members of PosInt, while 1 , 37.4, and 3/8 are not. Now, consider three other sets: small positive integers (SmPoslnt), medium positive integers (MdPoslnt), and large positive integers (LgPoslnt). Obviously, 1 is a member of the set SmPoslnt; it is pretty safe to include 109 in the set LgPoslnt. What about 100, 10,000, or even 1,000,000? Are they all members of MdPoslnt, or is 100 a member of SmPoslnt and 1,000,000 a member of LgPoslnt? There is some vagueness regarding membership to these different sets. This vagueness is caused by the words "small," "medium," and "large." In everyday conversation, such simple adjectives may be interpreted in many ways. To resolve this problem, classical set theory requires dictating upper and lower bounds for each of the three sets:
[2]
S. Isaka,et al.
Control strategies for arterial blood pressure regulation
,
1993,
IEEE Transactions on Biomedical Engineering.
[3]
L. C. Sheppard,et al.
A Model for Design of a Blood Pressure Controller for Hypertensive Patients
,
1979
.
[4]
James F. Martin,et al.
A new cardiovascular model for real-time applications
,
1986
.
[5]
N. T. Smith,et al.
Supervisory adaptive control of arterial pressure during cardiac surgery
,
1992,
IEEE Transactions on Biomedical Engineering.
[6]
G N Kenny,et al.
Evaluation of closed-loop control of arterial pressure after cardiopulmonary bypass.
,
1987,
British journal of anaesthesia.
[7]
Lotfi A. Zadeh,et al.
Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
,
1973,
IEEE Trans. Syst. Man Cybern..
[8]
Louis C. Sheppard,et al.
Computer control of the infusion of vasoactive drugs
,
2006,
Annals of Biomedical Engineering.
[9]
John S. Packer,et al.
An Adaptive Controller for Closed-Loop Management of Blood Pressure in Seriously Ill Patients
,
1987,
IEEE Transactions on Biomedical Engineering.
[10]
L. Cohn,et al.
Automated control of postoperative hypertension: a prospective, randomized multicenter study.
,
1989,
The Annals of thoracic surgery.
[11]
N. T. Smith,et al.
Improved safety and efficacy in adaptive control of arterial blood pressure through the use of a supervisor
,
1992,
IEEE Transactions on Biomedical Engineering.