1. Roles of Clinician and Engineer in Design and Evaluation of Autonomous Critical Care Devices What are the knowledge gaps? 1 University of Maryland 1 Lex Schultheis, M.D., Ph.D. Research Professor, Fischell Dept.of Bioengineering

2. 2 University of Maryland 2 When a clinician identifies a pattern that could be managed the same way each time, Mayo Clinic spin-off’s software K143372 a machine may be used to aid clinical management. http://ambientclinical.com/aware/ http://graphics8.nytimes.com/images/2008/11/13/health/chen_600.jpg

3. 3 University of Maryland 3 Components of a Simple PCLC The goal is to make the Response match the Command 3 + - e Command (C) Response (R) + Disturbance (D) Controller Sensor Plant Gain (multiplication factor) error R R = C{G/1 +G} + D/(1 + G) Closed loop control makes R  C, Despite changes in G or an external disturbance.

4. How Do Clinicians Think About PCLC?

5. 5 University of Maryland 5 Meaningful “Sensors” Are Often Qualitative Rather Than Quantitative A clinical sensor does a whole lot of interpretation… by Frank Netter

6. 6 University of Maryland 6 “Actuator” Success Is Also Often Qualitative http://sports.yahoo.com/highschool/blog/prep_rally/post/Tennis-star-returns-from-arm-amputation-to- reach?urn=highschool-wp2374

7. 7 University of Maryland 7 Clinicians Can Be Suggestible, But Have Learned To Be Wary Of Surrogate Markers.. Routine use of pulmonary artery catheters in heart surgery is no longer widespread. Monitoring processed EEG in uncomplicated cases of general anesthesia has declined in acceptance.. http://www.covidien.com/rms/products/oem-monitoring-solutions/bis-brain-monitoring- technology-oem-solutions/bis-loc-2-channel-oem-module http://www.nytimes.com/health/guides/test/swan-ganz-right-heart- catheterization/overview.html

8. 8 University of Maryland 8 Even A Common Quantitative Variable Like Blood Pressure Is Interpreted Differently By Various Clinicians, Depending On Context. http://ec.pond5.com/s3/010687752_prevstill.jpeg http://www.medicine.virginia.edu/clin ical/departments/anesthesiology/educa tion/copy_of_portalresidency/resident -life/day-tee http://images.wisegeek.com/surg eons-performing-open- surgery.jpg

9. 9 University of Maryland 9 Physicians Follow Multiple Inputs And Sometimes Perform Many Tasks Simultaneously. Could PCLC help manage the workload? We are MIMO PCLCs Me http://www.unmc.edu/anesthesia/echo/advanced/index.html

10. 10 University of Maryland 10 Physicians Internalize An Encyclopedia Of Experience That We Can Match To The Condition Of A New Patient. No machine algorithm processes as complex information, filters data and improvises as well as human being in the loop. However, clinicians can also be dogmatic… http://i1.mirror.co.uk/incoming/article4736848.ece/ALTERNATES /s615/Cancer-Treatment.jpg http://www.physiciansweekly.com/wp- content/themes/twentyten/timthumb.php?src=http://www.physiciansweekly.com/wp- content/uploads/2013/03/anger-management.1.86541190.png&w=620&

11. 11 University of Maryland 11 Clinicians Are Tool Users—They Expect That Their Tools Will Work And Be Easy To Use. http://www.flyheight.com/videos/doctors-try-to-hammer-out-surgical-instrument-that-got-stuck-in-a-patients-kneegraphic/

12. How Do Engineers Think About PCLC?

13. 13 University of Maryland 13 Engineers Will First Want To Characterize The Relevant Signals. Signals are the quantitative energies that propagate through a System. The System is, the device that processes or controls signals. Signals are either Energy signals (finite) or Power signals (infinite in duration). System commandresponse https://s17-us2.ixquick.com/cgi- bin/serveimage?url=http%3A%2F%2Ftse2.mm.bing.net%2Fth%3Fid%3DOIP.M6f03c1f6916c4cbe2533da88e752003co0%26pid%3D15.1%26f%3D1 &sp=1a0645b7c031b15af624d2b7cd9966eb

14. 14 University of Maryland 14 Power signals may be reconstructed from mathematically simple, periodic functions as components (orthogonal basis set). Sinusoids are the most widely used orthogonal basis set, e.g. Fourier methodology. Physiologic signals may be described as a sum of sinusoids characterized by amplitude, period and phase. Engineers Always Manipulate Signals Quantitatively, More Often The Frequency Domain Than As Time Functions.

15. 15 University of Maryland 15 Real world signals are composed of information and noise. Finite signals may be approximated with an arbitrary degree of resolution. Bandlimiting a signal may reduce noise and is essential when using sampled data (digital processing) to avoid aliasing. Engineer designers know:

16. 16 University of Maryland 16 Engineers Will Want Quantitative Specifications Before Designing A PCLC. * Specifications may be defined in the time domain, but in general should be able to be transformed into the frequency domain. What are the maximum allowed transient and steady state errors? What is the maximum speed of response needed? System Command Response

17. 17 University of Maryland 17 Engineers Use High Gain To Minimize Error and Compensators to Improve Response. 17 + - e Command (C) Response (R) + Disturbance (D) Controller Sensor Open-loop failure can cause saturation! Processing delay in the loop can cause oscillation!!! Patient Actuator Plant Compensator Gain e R

18. 18 University of Maryland 18 If A PCLC Is Linear, Stationary And Causal, System Performance Is Completely Characterized By The Impulse Response And Transfer Function. System(t) System(s)

19. 19 University of Maryland 19 PCLC May Also Be Designed Around State Variables Meet Some Prespecified Optimum Of Performance. The internal state variables are the smallest possible subset of system variables that can represent the entire state of the system at any given time for all commands. This approach is equivalent to design by transfer function provided that all of the state variables are observable and controllable.

20. 20 University of Maryland 20 Patient state variables may not be either observable or controllable. The patient will also change (non-stationary). An “optimum” system response may vary with the patient’s condition. Clinical signals are noisy. Patients may appear similar, but they are all different, so a compensator design may not be comprehensive. Challenges to Analytical Design of PCLC

21. 21 University of Maryland 21 Rule-based control: a simple example 21 + - e Command (C) Response (R) + Disturbance (D) Sensor Tends to oscillate around the decision point Works best for slowly changing environments Patient Actuator Plant Bang-bang controller

22. Patient Actuator Plant 22 University of Maryland 22 Model-based control example: The physiologic sensor is not in the tissue of interest. 22 + - e + Disturbance (D) Sensor in Blood Signal In Blood Command (C) Signal In Blood Response (R) Signal in Blood Signal in Target Tissue Relational Model Accuracy and stability of the PCLC depends on the relevance of the signal where it is measured compared to the signal in the tissue of interest.

23. Patient Actuator Plant 23 University of Maryland 23 Another model-based control example: A pharmacodynamic sensor is used to control drug delivery. 23 + - e + Disturbance (D) Pharmacodynamic Sensor Desired PD Command (C) PD Outcome Response (R) ADME Model Accuracy and stability of the PCLC depends on the completeness of PK/PD in terms of predicting clinical outcome and the quality of ADME models for the patient population to be exposed.

24. How Can Clinicians and Engineers Think About PCLP Together?

25. 25 University of Maryland 25 Clinicians must Understand the clinical outcomes that are worthwhile from the patient’s perspective Validate surrogate markers against clinical outcomes Identify clinical consequences of system failure Engineers must Describe how component failure will affect machine signal processing Develop mitigations against failure that do not rely on human intervention so they do not introduce new risks. Keep systems simple and robust to meet conditions of actual use.

26. Thank you!