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Applied Sciences
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Control Systems Approaches and Applications for Biomedical Systems
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Control Systems Approaches and Applications for Biomedical Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 8657

Special Issue Editor

Dr. Hossam S. Abbas

E-Mail Website
Guest Editor
Institute for Electrical Engineering in Medicine, University of Lübeck, Moislinger Allee 53-55, 23558 Lübeck, Germany
Interests: control systems; model predictive control; system identification; modeling and control of biomedical systems; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Applications of control systems have dramatically increased in recent years due to advances in digital processing hardware, yielding faster sampling rates and increased control scheme complexity. In addition, the development of improved sensors and actuators makes practical control systems more feasible. This Special Issue seeks papers that deal with the modeling, control, and monitoring of biomedical systems. The scope of this Special Issue includes, but is not limited to, the modeling of physiological systems, the modeling of drug pharmacokinetics and pharmacodynamics, the use of advanced or novel sensors and actuators, control algorithms, and fault detection and isolation. This Special Issue is focused on new developments in the field of control system concepts and approaches in biomedical engineering.

Dr. Hossam S. Abbas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • physiological control systems
  • physiological models
  • control applications for biomedical systems
  • medical devices
  • data-driven modeling and control techniques for biomedical systems
  • control engineering tools in medical technology
  • machine learning for decision-support systems
  • advances in sensing and signal processing
  • biosignal analysis

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Published Papers (3 papers)

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Research

17 pages, 6868 KiB  
Article
Closed-Loop Current Stimulation Feedback Control of a Neural Mass Model Using Reservoir Computing
by Alexander Pei and Barbara G. Shinn-Cunningham
Appl. Sci. 2023, 13(3), 1279; https://doi.org/10.3390/app13031279 - 18 Jan 2023
Viewed by 2225
Abstract
Transcranial electrical stimulation (tES) is a non-invasive neuromodulatory technique that alters ongoing neural dynamics by injecting an exogenous electrical current through the scalp. Although tES protocols are becoming more common in both clinical and experimental settings, the neurophysiological mechanisms through which tES modulates [...] Read more.
Transcranial electrical stimulation (tES) is a non-invasive neuromodulatory technique that alters ongoing neural dynamics by injecting an exogenous electrical current through the scalp. Although tES protocols are becoming more common in both clinical and experimental settings, the neurophysiological mechanisms through which tES modulates cortical dynamics are unknown. Most existing tES protocols ignore the potential effect of phasic interactions between endogenous and exogenous currents by stimulating in an open-looped fashion. To better understand the mechanisms of closed-loop tES, we first instantiated a two-column Jansen and Rit model to simulate neuronal dynamics of pyramidal cells and interneurons. An echo-state network (ESN) reservoir computer inverted the dynamics of the model without access to the internal state equations. After inverting the model dynamics, the ESN was used as a closed-loop feedback controller for the neural mass model by predicting the current stimulation input for a desired future output. The ESN was used to predict the endogenous membrane currents of the model from the observable pyramidal cell membrane potentials and then inject current stimulation to destructively interfere with endogenous membrane currents, thereby reducing the energy of the PCs. This simulation approach provides a framework for a model-free closed-loop feedback controller in tES experiments. Full article
(This article belongs to the Special Issue Control Systems Approaches and Applications for Biomedical Systems)
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11 pages, 4595 KiB  
Article
Controlling Laser Irradiation with Tissue Temperature Feedback Enhances Photothermal Applications: Ex-Vivo Evaluation on Bovine Liver
by Özgür Kaya, İpek Düzgören, İnci Çilesiz and Murat Gülsoy
Appl. Sci. 2023, 13(1), 237; https://doi.org/10.3390/app13010237 - 24 Dec 2022
Cited by 1 | Viewed by 2153
Abstract
Achieving repeatable and successful results without causing excessive collateral damage is of paramount importance for photothermal laser applications. Predetermined laser parameters cannot ensure patient safety and treatment success due to variance between optical and thermal characteristics among subjects. Controlling laser irradiation with tissue [...] Read more.
Achieving repeatable and successful results without causing excessive collateral damage is of paramount importance for photothermal laser applications. Predetermined laser parameters cannot ensure patient safety and treatment success due to variance between optical and thermal characteristics among subjects. Controlling laser irradiation with tissue temperature feedback is the current gold standard for various photothermal treatments (PTT) which are rate processes described by the Arrhenius temperature integral. This study establishes the validity of our low-cost design that makes tissue surface temperature control during photothermal laser applications more accessible in resource limited clinical environments. We demonstrated the practical performance and potential of our system with ex-vivo bovine liver irradiation using an ytterbium fiber laser (λ=1071 nm) with two independent variables: laser power (3.4 W, 6.8 W and 10.2 W) and target surface temperature (55 °C, 65 °C and 75 °C). Our system efficiently maintained tissue surface temperatures at target values in all laser power groups. In contrast, fixed-dose application groups displayed a high final temperature range and variation in the control experiment. Temperature–time responses of samples varied significantly, in agreement with a wide range of optical and thermal coefficients. Long exposure duration groups (lower power, higher target temperature) displayed more radical differences suggesting a dominance of optical and thermal characteristics over the response. The low-cost surface-temperature-controlled medical laser system we have developed is capable of ensuring the success and reproducibility of PTT modalities and patient safety. Full article
(This article belongs to the Special Issue Control Systems Approaches and Applications for Biomedical Systems)
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17 pages, 2097 KiB  
Article
Evaluation of Different Control Algorithms for Carbon Dioxide Removal with Membrane Oxygenators
by Martin Elenkov, Benjamin Lukitsch, Paul Ecker, Christoph Janeczek, Michael Harasek and Margit Gföhler
Appl. Sci. 2022, 12(23), 11890; https://doi.org/10.3390/app122311890 - 22 Nov 2022
Viewed by 1949
Abstract
Membrane oxygenators are devices that benefit from automatic control. This is especially true for implantable membrane oxygenators—a class of wearable rehabilitation devices that show high potential for fast recovery after lung injury. We present a performance comparison for reference tracking of carbon dioxide [...] Read more.
Membrane oxygenators are devices that benefit from automatic control. This is especially true for implantable membrane oxygenators—a class of wearable rehabilitation devices that show high potential for fast recovery after lung injury. We present a performance comparison for reference tracking of carbon dioxide partial pressure between three control algorithms—a classical proportional-integral (PI) controller, a modern non-linear model predictive controller, and a novel deep reinforcement learning controller. The results are based on simulation studies of an improved compartmental model of a membrane oxygenator. The compartmental model of the oxygenator was improved by decoupling the oxygen kinetics from the system and only using the oxygen saturation as an input to the model. Both the gas flow rate and blood flow rate were used as the manipulated variable of the controllers. All three controllers were able to track references satisfactorily, based on several performance metrics. The PI controller had the fastest response, with an average rise time and settling time of 1.18 s and 2.24 s and the lowest root mean squared error of 1.06 mmHg. The NMPC controller showed the lowest steady state error of 0.17 mmHg and reached the reference signal with less than 2% error in 90% of the cases within 15 s. The PI and RL reached the reference with less than 2% error in 84% and 50% of the cases, respectively, and showed a steady state error of 0.29 mmHg and 0.5 mmHg. Full article
(This article belongs to the Special Issue Control Systems Approaches and Applications for Biomedical Systems)
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