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Control of Postoperative Pain by Self-Administered Opioids
Published in Robert B. Northrop, Endogenous and Exogenous Regulation and Control of Physiological Systems, 2020
Liu and Northrop investigated the performance of four different controllers using the patient pain model described above. PAIN1 was a conventional proportional controller which injected IV 2 μg of fentanyl for every button press. This model was used to tune the patient pain model’s variable parameters to match actual patient data from Reasbeck.116PAIN2 used the IPFM/SDC controller shown in Figure 9.11 with Ts = 1 min, Do = 4 μg, and TH2 = 0.05 for the IPFM pulse generator. The PAIN3 controller was the same as PAIN2 except Ts = 0.5 min. PAIN4 was a hybrid system in which the PAIN1 proportional algorithm was used for the first hour after the simulated patient awoke, and the PAIN2 controller was used for the next 7 hr. Some of the results are summarized in Table 9.4.
Simulated Practice
Published in Christopher M. Hayre, William A. S. Cox, General Radiography, 2020
Facilitators can use several techniques to add to the realism or fidelity. Availability of setting may dictate the level of work required to add to the realism. In-situ simulations held in an X-ray room or in resuscitation addresses many of the senses by offering real background noise opposed to recorded noise in a Higher Education Institute (HEI) setting. Patients may be simulated using higher end simulators, such as SimMan 3G, which are programmed to have physiological metrics and responses mimicking normal or abnormal disease. These mannequins are limited where interpersonal relationships are required as they lack nonverbal expression and physical movement. This can be introduced by using actors to role play as the patient. Here, the situation may ‘feel’ more natural allowing participants to interact more readily. In this scenario, pure use of a simulated patient means assessment of this individual would fail to offer the physiological metrics offered by a mannequin. Both offer elements of realism; therefore, it is important to consider the main learning outcomes intended for the simulation to guide the planning stage.
Simulation: A Tool to Detect and Traverse Boundaries
Published in Jeffrey Braithwaite, Erik Hollnagel, Garth S Hunte, Working Across Boundaries, 2019
Mary D. Patterson, Peter Dieckmann, Ellen S. Deutsch
To these essential elements, we consider adding the necessity of expert facilitators. Depending on the goal of the simulation experience, facilitators may represent clinical subject matter experts (nurses and physicians, for example) as well as facilitators with specific expertise in the debriefing process – often the same person brings both aspects of ability to the table. In the example of the simulated patient with a tracheostomy obstruction, the facilitators needed to recognise, expose and explore the boundaries that were uncovered. In this way, the facilitators serve as translators or guides for the diverse clinical team members. Facilitators support the emergence of understanding from the insights of the participants, and the participants develop insights into their own assumptions and capabilities as well as those of others. Explicitly describing and exploring these boundaries during debriefing supports the goal of improving clinicians’ performance in the clinical environment. The facilitator as translator is crucial to elucidating the boundaries between groups as well as assisting the health care workers in understanding system performance boundaries.
Development of AR training systems for Humanitude dementia care
Published in Advanced Robotics, 2022
Ryo Kurazume, Tomoki Hiramatsu, Masaya Kamei, Daiji Inoue, Akihiro Kawamura, Shoko Miyauchi, Qi An
Before and after approaching the simulated patient or the soft doll in step 3), participants recorded their emotion using an affect grid [48], which has a pleasant-unpleasant axis and an arousal-sleepiness axis. The pleasure point (displeasure 1 to pleasure 9) and the arousal point (sleepiness 1 to arousal 9) were obtained by evaluating each axis independently before and after each experiment. The affect grid, which measures emotions using two axes (pleasure–unpleasure and arousal-sleepiness), is a widely used technique based on the theoretically circumplex model of affect processes introduced by Russell [49]. The affect grid has been used in a variety of fields, including usability tests or user experience evaluations, and we adopted the affect grid to evaluate the difference of impressions quantitatively.