Correspondence 255
5. Finally, Dr Martin's comments that designs which performed adequately in simulations often fail in animal experiments simply support the case made in the paper, in that he is referring to traditional, trial-and-error simulations rather than the exhaustive kind proposed in the paper. A. V. Sebatd College of Engineering University of California, San Diego San Diego, California
Reference 1. Sebald AV, Quinn M, Smith NT, et al. Engineering implications o f closed-loop control during cardiac surgery. J Clin Monit 1990;6:241-248
Editorial THE ROLEOF SIMULATIONIN THE DESIGNOF CONTROLSYSTEMS In the July 1990 issue of the Journal of Clinical Monitoring, Sebald and coauthors [1] discuss the complexity of the operating room environment during cardiac surgery with regard to the design and evaluation of a closed-loop controller that adjusts the infusion rate o f sodium nitroprusside (SNP) to maintain a target blood pressure (BP) level. The authors examine many of the factors that influence the relationship between BP and SNP, including patient sensitivity to SNP, disturbances caused by sensors, and the undocumented administration of other drugs, and they briefly mention various control strategies. The proportional-integral-derivative (PID) controller, a commonly used controller with three adjustable coefficients, is designed to obtain a minimal difference between the desired set point and the actual controlled signal, hasten response to rapid changes, and minimize overshoot. A model-based controller uses a simplification (a model) of the process to be controlled to calculate the optimal infusion rate for SNP (in this case, to control BP). With rule-based controllers, which are a product of the field of artificial intelligence, expert knowledge is represented in rules. Proper inferencing with such rules leads to the desired control action. Sebald and coauthors also make a statement concerning the inadequacy of PID controllers, for which they do not provide adequate support. Their statement prompted Martin [2] to respond with criticism of their claim. Is there a controversy here? Absolutely true or false statements are very unlikely in these matters. A statement that is probably acceptable to both Sebald and coauthors and to Martin is that a straightforward PID controller for B P - S N P control will not perform well enough to be safe. If, on the other hand, a PID controller is embedded in rules, constraints, or boundary conditions, however defined, a perfectly safe system can be designed. Martin gives examples of such an approach and Blom [3] describes the function and a safe clinical application of a PID controller for SNP embedded in a real-time expert system. The focus o f the paper by Sebald and coauthors [1] are the procedures for evaluating such controllers. Many tests use models in which extensive parameter variations are introduced
to verify the robustness of the control for a large variety of patients. The authors present themselves as strong proponents of the "minimax" method of evaluation. With this technique, all potential parameters of a model representing the patientcontroller system are systematically searched; the technique is derived from Bayes' theorem and assumes that the a priori distribution of the parameters is known. In principle, all potential combinations of parameters are tested, which means that the properties of all potential patients are considered. The design process yields a single controller capable of coping with a set of patients. A number of questions can be asked at this point: (1) Are the models good enough to warrant such an approach? If the model is inadequate, even a thorough search of the parameter space may produce a false indication of reliability. (2) H o w reliably do we know the a priori distribution of the parameters in terms of the model used? (3) Are the disturbances--both the ones with known statistics (e.g., colored noise) and the aperiodic ones that take the form of steps and impulses (e.g., flushing)--properly modeled? The most fundamental question that remains, however, is whether it is a sound goal to try and design a single controller, with fixed parameter values, for a whole set of patients. The minimax method may yield "a single controller capable of coping with a set of patients," or, as Sebald states in his reply to Martin's letter, the controller may do " . . . the best possible job across all patients" [4]. This controller, however, may not necessarily be the "optimal" one for the patient who is currently on the operating table. Some on-line identification of one or more relevant patient parameters (e.g., patient sensitivity, which can vary greatly in a patient throughout an operation) will most likely perform better than a single controller for a group of patients. A general problem underlying this discussion is the performance criteria used to evaluate the different controllers. I just mentioned "perform better" and meant "better" in terms of staying more closely to the predefined pressure levels. Is this a good criterion? Is invariability of the cardiovascular system the best condition for the patient? Physiologic variability in heart rate and BP have been thought to reflect uncompromised heart function. We must, therefore, reconsider whether we have sufficient physiologic insight to answer the question, "what is optimal?" In control engineering, it is easier to define "optimal." Either a product's quality or its production cost needs to be optimized; all of the relevant factors are quantifiable. In the many medical circumstances in which we lack the proper insight to determine what is optimal, should we not defer to the (often intuitive) knowledge and experience gained by clinicians through years o f experience? Systems approaches, like the minimax method, are certainly helpful in designing control or surveillance systems when they are combined with clinical knowledge. A good example of this type of knowledge-based system is the intelligent alarm system designed by van der Aa [5] for surveillance of the ventilation of a patient on a respirator during surgery. It is clear that much work still needs to be done. The development of approaches that reduce the need for animal experimentation and limit the risk for the patient when methods are evaluated clinically should be of top priority. Engineering principles should be applied to and, if necessary, adapted for research and development to improve the quality of care and to solve complicated problems. The intricate internal relations that drive the living system, most o f which are unobservable
256
Journalof ClinicalMonitoring Vot 8 No 3 July 1992
(to use an engineering expression), however, will continue to prevent us from expressing physiologic behavior in terms of numbers and statistics. Therefore, any design for closed-loop control of a patient variable needs to allow for adjustments to the needs of individual patients. These adjustments might be made automatically, but the anesthesiologist should have the opportunity to change individual control parameters.
Announcements
MEETINGS
Jan E. W. Beneken, PhD Division of Medical Electrical Engineering Eindhoven University of Technology The Netherlands
Third International Congress on Cardiac, Thoracic, and Vascular Anesthesia, Update and Review
References
Sonesta Beach Hotel and Spa, Bermuda, September 4-7, 1992 Contact: Anita V. Guffin, MMS, Program Coordinator, PO Box 287, Port Chester, NY 10573. Tel: (212) 241-8392.
1. Sebald AV, Quinn M, Smith NT, Karini A, Schnurer G, Isaka S. Engineering implications of dosed-loop control during cardiac surgery. J Clin Monit 1990;6:241-248 2. Martin JF. Letter to the editor. J Clin Monit 1992;8:252 3. BlomJA. Expert control of the arterial blood pressure during surgery. Int J Clin Monit Comput 1991;8:25-34 4. Sebald AV. Letter to the editor. J Clin Monit 1992;8: 253 5. van der Aa JJ. Intelligent alarms in anesthesia: a real time expert system application (PhD dissertation). Eindhoven University of Technology, Eindhoven, Netherlands, 1990
1992
Annual Meeting of the Royal College of Physicians and Surgeons of Canada and the Canadian Society for Clinical Investigation Ottawa, Canada, September 11-14, 1992 Contact: A. L. Chabot, 74 Stanley, Ottawa, Canada KIM 1P4. Tel: (613) 746-8177.
Fifth International Congress of the Pain Clinic Jerusalem, Israel, September 14-18, 1992 Contact: Prof. Y. Sharav, Scientific Committee Chairman, Hadassah School of Dentistry, PO Box 1172, 91 010, Jerusalem, Israel.
Thirteenth International Congress on the Computer in Critical Care and Pulmonary Medicine Kurftirstliches Schloss Mainz, Germany, Oct 8-10, 1992 Contact Univ-Prof Dr reed W. Dick, Langenbeckstrasse 1, Postfach 3960, 6500 Mainz, Germany; (0 61 31)17 1 (phone) or (0 61 31)23 60 28 (fax).
Sixth International Symposium on Anesthesia and Intensive Care Beer-Sheva, Israel, November 4-6, 1992 Contact: Dr A. Fisher, Div of Anesthesiology, Soroka Medical Center, PO Box 151, Beer-Sheva 84101, Israel. Tel: 057-660111.
28th Meeting of the World Congress of the International College of Surgeons Cairo, Egypt, November 16-21, 1992 Contact: Emeco Travel, 2, Talaat Harb St, PO Box 1294, Cairo, Egypt. Tel: (202) 747399. 1993
Second European Congress on Ambulatory Surgery Brussels, Belgium, March 19-20, 1993 Contact: C. De Lathouwer, MD, Brussels One Day Clinic, Avenue du Duc Jean 71-73, B-1080 Brussels, Belgium. Tel: +322/424.1212; fax: + 322/425.7076.
Second Anaesthesia and Critical Care Symposium Ireland, September 11-18, 1993 Sponsored by the Department of Anesthesia, Yale University School of Medicine, and the Royal College of Surgeons in Ireland. For more information and registration, contact the Office of Postgraduate and Continuing Medical Education, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06510. Tel: (203) 785-4578.
5. Finally, Dr Martin's comments that designs which performed adequately in simulations often fail in animal experiments simply support the case made in the paper, in that he is referring to traditional, trial-and-error simulations rather than the exhaustive kind proposed in the paper. A. V. Sebatd College of Engineering University of California, San Diego San Diego, California
Reference 1. Sebald AV, Quinn M, Smith NT, et al. Engineering implications o f closed-loop control during cardiac surgery. J Clin Monit 1990;6:241-248
Editorial THE ROLEOF SIMULATIONIN THE DESIGNOF CONTROLSYSTEMS In the July 1990 issue of the Journal of Clinical Monitoring, Sebald and coauthors [1] discuss the complexity of the operating room environment during cardiac surgery with regard to the design and evaluation of a closed-loop controller that adjusts the infusion rate o f sodium nitroprusside (SNP) to maintain a target blood pressure (BP) level. The authors examine many of the factors that influence the relationship between BP and SNP, including patient sensitivity to SNP, disturbances caused by sensors, and the undocumented administration of other drugs, and they briefly mention various control strategies. The proportional-integral-derivative (PID) controller, a commonly used controller with three adjustable coefficients, is designed to obtain a minimal difference between the desired set point and the actual controlled signal, hasten response to rapid changes, and minimize overshoot. A model-based controller uses a simplification (a model) of the process to be controlled to calculate the optimal infusion rate for SNP (in this case, to control BP). With rule-based controllers, which are a product of the field of artificial intelligence, expert knowledge is represented in rules. Proper inferencing with such rules leads to the desired control action. Sebald and coauthors also make a statement concerning the inadequacy of PID controllers, for which they do not provide adequate support. Their statement prompted Martin [2] to respond with criticism of their claim. Is there a controversy here? Absolutely true or false statements are very unlikely in these matters. A statement that is probably acceptable to both Sebald and coauthors and to Martin is that a straightforward PID controller for B P - S N P control will not perform well enough to be safe. If, on the other hand, a PID controller is embedded in rules, constraints, or boundary conditions, however defined, a perfectly safe system can be designed. Martin gives examples of such an approach and Blom [3] describes the function and a safe clinical application of a PID controller for SNP embedded in a real-time expert system. The focus o f the paper by Sebald and coauthors [1] are the procedures for evaluating such controllers. Many tests use models in which extensive parameter variations are introduced
to verify the robustness of the control for a large variety of patients. The authors present themselves as strong proponents of the "minimax" method of evaluation. With this technique, all potential parameters of a model representing the patientcontroller system are systematically searched; the technique is derived from Bayes' theorem and assumes that the a priori distribution of the parameters is known. In principle, all potential combinations of parameters are tested, which means that the properties of all potential patients are considered. The design process yields a single controller capable of coping with a set of patients. A number of questions can be asked at this point: (1) Are the models good enough to warrant such an approach? If the model is inadequate, even a thorough search of the parameter space may produce a false indication of reliability. (2) H o w reliably do we know the a priori distribution of the parameters in terms of the model used? (3) Are the disturbances--both the ones with known statistics (e.g., colored noise) and the aperiodic ones that take the form of steps and impulses (e.g., flushing)--properly modeled? The most fundamental question that remains, however, is whether it is a sound goal to try and design a single controller, with fixed parameter values, for a whole set of patients. The minimax method may yield "a single controller capable of coping with a set of patients," or, as Sebald states in his reply to Martin's letter, the controller may do " . . . the best possible job across all patients" [4]. This controller, however, may not necessarily be the "optimal" one for the patient who is currently on the operating table. Some on-line identification of one or more relevant patient parameters (e.g., patient sensitivity, which can vary greatly in a patient throughout an operation) will most likely perform better than a single controller for a group of patients. A general problem underlying this discussion is the performance criteria used to evaluate the different controllers. I just mentioned "perform better" and meant "better" in terms of staying more closely to the predefined pressure levels. Is this a good criterion? Is invariability of the cardiovascular system the best condition for the patient? Physiologic variability in heart rate and BP have been thought to reflect uncompromised heart function. We must, therefore, reconsider whether we have sufficient physiologic insight to answer the question, "what is optimal?" In control engineering, it is easier to define "optimal." Either a product's quality or its production cost needs to be optimized; all of the relevant factors are quantifiable. In the many medical circumstances in which we lack the proper insight to determine what is optimal, should we not defer to the (often intuitive) knowledge and experience gained by clinicians through years o f experience? Systems approaches, like the minimax method, are certainly helpful in designing control or surveillance systems when they are combined with clinical knowledge. A good example of this type of knowledge-based system is the intelligent alarm system designed by van der Aa [5] for surveillance of the ventilation of a patient on a respirator during surgery. It is clear that much work still needs to be done. The development of approaches that reduce the need for animal experimentation and limit the risk for the patient when methods are evaluated clinically should be of top priority. Engineering principles should be applied to and, if necessary, adapted for research and development to improve the quality of care and to solve complicated problems. The intricate internal relations that drive the living system, most o f which are unobservable
256
Journalof ClinicalMonitoring Vot 8 No 3 July 1992
(to use an engineering expression), however, will continue to prevent us from expressing physiologic behavior in terms of numbers and statistics. Therefore, any design for closed-loop control of a patient variable needs to allow for adjustments to the needs of individual patients. These adjustments might be made automatically, but the anesthesiologist should have the opportunity to change individual control parameters.
Announcements
MEETINGS
Jan E. W. Beneken, PhD Division of Medical Electrical Engineering Eindhoven University of Technology The Netherlands
Third International Congress on Cardiac, Thoracic, and Vascular Anesthesia, Update and Review
References
Sonesta Beach Hotel and Spa, Bermuda, September 4-7, 1992 Contact: Anita V. Guffin, MMS, Program Coordinator, PO Box 287, Port Chester, NY 10573. Tel: (212) 241-8392.
1. Sebald AV, Quinn M, Smith NT, Karini A, Schnurer G, Isaka S. Engineering implications of dosed-loop control during cardiac surgery. J Clin Monit 1990;6:241-248 2. Martin JF. Letter to the editor. J Clin Monit 1992;8:252 3. BlomJA. Expert control of the arterial blood pressure during surgery. Int J Clin Monit Comput 1991;8:25-34 4. Sebald AV. Letter to the editor. J Clin Monit 1992;8: 253 5. van der Aa JJ. Intelligent alarms in anesthesia: a real time expert system application (PhD dissertation). Eindhoven University of Technology, Eindhoven, Netherlands, 1990
1992
Annual Meeting of the Royal College of Physicians and Surgeons of Canada and the Canadian Society for Clinical Investigation Ottawa, Canada, September 11-14, 1992 Contact: A. L. Chabot, 74 Stanley, Ottawa, Canada KIM 1P4. Tel: (613) 746-8177.
Fifth International Congress of the Pain Clinic Jerusalem, Israel, September 14-18, 1992 Contact: Prof. Y. Sharav, Scientific Committee Chairman, Hadassah School of Dentistry, PO Box 1172, 91 010, Jerusalem, Israel.
Thirteenth International Congress on the Computer in Critical Care and Pulmonary Medicine Kurftirstliches Schloss Mainz, Germany, Oct 8-10, 1992 Contact Univ-Prof Dr reed W. Dick, Langenbeckstrasse 1, Postfach 3960, 6500 Mainz, Germany; (0 61 31)17 1 (phone) or (0 61 31)23 60 28 (fax).
Sixth International Symposium on Anesthesia and Intensive Care Beer-Sheva, Israel, November 4-6, 1992 Contact: Dr A. Fisher, Div of Anesthesiology, Soroka Medical Center, PO Box 151, Beer-Sheva 84101, Israel. Tel: 057-660111.
28th Meeting of the World Congress of the International College of Surgeons Cairo, Egypt, November 16-21, 1992 Contact: Emeco Travel, 2, Talaat Harb St, PO Box 1294, Cairo, Egypt. Tel: (202) 747399. 1993
Second European Congress on Ambulatory Surgery Brussels, Belgium, March 19-20, 1993 Contact: C. De Lathouwer, MD, Brussels One Day Clinic, Avenue du Duc Jean 71-73, B-1080 Brussels, Belgium. Tel: +322/424.1212; fax: + 322/425.7076.
Second Anaesthesia and Critical Care Symposium Ireland, September 11-18, 1993 Sponsored by the Department of Anesthesia, Yale University School of Medicine, and the Royal College of Surgeons in Ireland. For more information and registration, contact the Office of Postgraduate and Continuing Medical Education, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06510. Tel: (203) 785-4578.
