scholarly journals Accuracy assessment methods for physiological model selection toward evaluation of closed-loop controlled medical devices

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0251001
Author(s):  
Ramin Bighamian ◽  
Jin-Oh Hahn ◽  
George Kramer ◽  
Christopher Scully

Physiological closed-loop controlled (PCLC) medical devices are complex systems integrating one or more medical devices with a patient’s physiology through closed-loop control algorithms; introducing many failure modes and parameters that impact performance. These control algorithms should be tested through safety and efficacy trials to compare their performance to the standard of care and determine whether there is sufficient evidence of safety for their use in real care setting. With this aim, credible mathematical models have been constructed and used throughout the development and evaluation phases of a PCLC medical device to support the engineering design and improve safety aspects. Uncertainties about the fidelity of these models and ambiguities about the choice of measures for modeling performance need to be addressed before a reliable PCLC evaluation can be achieved. This research develops tools for evaluating the accuracy of physiological models and establishes fundamental measures for predictive capability assessment across different physiological models. As a case study, we built a refined physiological model of blood volume (BV) response by expanding an original model we developed in our prior work. Using experimental data collected from 16 sheep undergoing hemorrhage and fluid resuscitation, first, we compared the calibration performance of the two candidate physiological models, i.e., original and refined, using root-mean-squared error (RMSE), Akiake information criterion (AIC), and a new multi-dimensional approach utilizing normalized features extracted from the fitting error. Compared to the original model, the refined model demonstrated a significant improvement in calibration performance in terms of RMSE (9%, P = 0.03) and multi-dimensional measure (48%, P = 0.02), while a comparable AIC between the two models verified that the enhanced calibration performance in the refined model is not due to data over-fitting. Second, we compared the physiological predictive capability of the two models under three different scenarios: prediction of subject-specific steady-state BV response, subject-specific transient BV response to hemorrhage perturbation, and leave-one-out inter-subject BV response. Results indicated enhanced accuracy and predictive capability for the refined physiological model with significantly larger proportion of measurements that were within the prediction envelope in the transient and leave-one-out prediction scenarios (P < 0.02). All together, this study helps to identify and merge new methods for credibility assessment and physiological model selection, leading to a more efficient process for PCLC medical device evaluation.

Author(s):  
Mark Jansen ◽  
Gerald Montague ◽  
Andrew Provenza ◽  
Alan Palazzolo

Closed loop operation of a single, high temperature magnetic radial bearing to 30,000 RPM (2.25 million DN) and 540°C (1,000°F) is discussed. Also, high temperature, fault tolerant operation for the three axis system is examined. A novel, hydrostatic backup bearing system was employed to attain high speed, high temperature, lubrication free support of the entire rotor system. The hydrostatic bearings were made of a high lubricity material and acted as journal-type backup bearings. New, high temperature displacement sensors were successfully employed to monitor shaft position throughout the entire temperature range and are described in this paper. Control of the system was accomplished through a stand alone, high speed computer controller and it was used to run both the fault-tolerant PID and active vibration control algorithms.


Author(s):  
Zhihao Jiang ◽  
Miroslav Pajic ◽  
Rajeev Alur ◽  
Rahul Mangharam

2016 ◽  
Vol 8 (5) ◽  
pp. 540-547
Author(s):  
Tomas Eglynas ◽  
Audrius Senulis ◽  
Marijonas Bogdevičius ◽  
Arūnas Andziulis ◽  
Mindaugas Jusis

The main control object of Quay crane, which is operating in seaport intermodal terminal cargo loading and unloading process, is the crane trolley. One of the main frequent problem, which occurs, is the swinging of the container. This swinging is caused not only by external forces but also by the movement of the trolley. The research results of recent years produced various types of control algorithms by the other researchers. The control algorithms are solving separate control problems of Quay crane in laboratory environment. However, there is still complex control algorithm design and the controller’s parameter estimation problems to be solved. This paper presents mathematical model of the Quay crane trolley mechanism with the suspended cargo. The mathematical model is implemented in Matlab Simulink environment and using Dormand-Prince solving method. The presented model of laboratory quay crane mathematical model is dedicated to parameter estimation of PID controller of closed loop system with the usage of S –form speed input profile. The article includes the dynamic model of the presented system, the description of closed loop system and modeling results. These results will be used as an initial information for the PID parameters estimation in real quay crane control system. The simu-lation of the model was performed using estimated values of controller. The sway influence of the cargo, the usage of the trolley speed input S-shaper and the PID controller was used to control the trolley speed. Jūriniame įvairiarūšiame terminale atliekant konteinerių krovos procesus, vienas iš krantinės kranų valdymo objektų yra vežimėlis. Viena iš problemų, su kuria susiduriama dažniausiai, yra konteinerio svyravimai, kuriuos, be išorinių veiksnių, taip pat sukelia ir vežimėlio judėji-mas. Remdamiesi paskutinių kelerių metų tyrimais, mokslininkai sukūrė įvairių valdymo algoritmų, kurie laboratorinėmis sąlygomis spren-džia atskiras krantinės kranų valdymo problemas. Tačiau kompleksinių ir efektyvių valdymo algoritmų ir jų valdymo sistemos parametrų nustatymo metodai vis dar kuriami ir tobulinami. Šiame darbe sudarytas krantinės krano vežimėlio su kabančiu kroviniu mechanizmo sis-temos matematinis modelis. Šis modelis realizuotas Matlab Simulink aplinkoje ir sprendžiamas taikant Dormand-Prince metodą. Sukurtas laboratorinio krantinės krano valdymo sistemos kompiuterinis modelis skirtas uždarosios valdymo sistemos PID valdiklio parametrams nustatyti, kai užduoties signalui taikomas S formos greičio kitimo profilis. Darbe pateiktas sistemos dinaminis modelis, aprašyta uždaroji valdymo sistema, pateikti kompiuterinio modeliavimo rezultatai, kuriuos planuojama panaudoti kaip pradinę informaciją realaus krano PID valdiklio parametrams derinti. Atlikta simuliacija naudojant nustatytas vertes ir įvertinti krovinio svyravimai taikant S formos greičio kitimo profilį kartu su PID valdikliu vežimėlio greičiui valdyti.


Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3896
Author(s):  
Mario Munoz-Organero

Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the base for control algorithms in glucose regulating systems such as the artificial pancreas. Numerous research studies have already been conducted in order to provide predictions for blood glucose levels with particularities in the input signals and underlying models used. These models can be categorized into two major families: those based on tuning glucose physiological-metabolic models and those based on learning glucose evolution patterns based on machine learning techniques. This paper reviews the state of the art in blood glucose predictions for T1DM patients and proposes, implements, validates and compares a new hybrid model that decomposes a deep machine learning model in order to mimic the metabolic behavior of physiological blood glucose methods. The differential equations for carbohydrate and insulin absorption in physiological models are modeled using a Recurrent Neural Network (RNN) implemented using Long Short-Term Memory (LSTM) cells. The results show Root Mean Square Error (RMSE) values under 5 mg/dL for simulated patients and under 10 mg/dL for real patients.


2006 ◽  
Vol 38 (3) ◽  
pp. 257-274 ◽  
Author(s):  
Emad El-Samahy ◽  
Mahdi Mahfouf ◽  
Derek A. Linkens

1983 ◽  
Vol 105 (3) ◽  
pp. 204-206 ◽  
Author(s):  
H. Inooka ◽  
G. Obinata ◽  
M. Takeshima

By considering the rapid growth of microcomputer technology, it is now possible to implement various control algorithms into a microcomputer and to use it as a single-loop digital controller. This paper considers a design of a digital controller which achieves an arbitrarily specified closed-loop response. A linear equation is obtained for unknown parameters of such a controller based on series expansions of relevant pulse transfer functions. Some examples are given to show the characteristic features of the method.


2016 ◽  
Vol 25 (4) ◽  
pp. 623-633 ◽  
Author(s):  
PHILIPP KELLMEYER ◽  
THOMAS COCHRANE ◽  
OLIVER MÜLLER ◽  
CHRISTINE MITCHELL ◽  
TONIO BALL ◽  
...  

Abstract:Closed-loop medical devices such as brain-computer interfaces are an emerging and rapidly advancing neurotechnology. The target patients for brain-computer interfaces (BCIs) are often severely paralyzed, and thus particularly vulnerable in terms of personal autonomy, decisionmaking capacity, and agency. Here we analyze the effects of closed-loop medical devices on the autonomy and accountability of both persons (as patients or research participants) and neurotechnological closed-loop medical systems. We show that although BCIs can strengthen patient autonomy by preserving or restoring communicative abilities and/or motor control, closed-loop devices may also create challenges for moral and legal accountability. We advocate the development of a comprehensive ethical and legal framework to address the challenges of emerging closed-loop neurotechnologies like BCIs and stress the centrality of informed consent and refusal as a means to foster accountability. We propose the creation of an international neuroethics task force with members from medical neuroscience, neuroengineering, computer science, medical law, and medical ethics, as well as representatives of patient advocacy groups and the public.


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