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Tutorial for Using control systems engineering to Optimize Adaptive Mobile Health Interventions

JOURNAL OF MEDICAL INTERNET RESEARCH 2018年第6期20卷 e214-e214页

作者： Hekler, Eric B. Rivera, Daniel E. Martin, Cesar A. Phatak, Sayali S. Freigoun, Mohammad T. Korinek, Elizabeth Klasnja, Predrag Adams, Marc A. Buman, Matthew P. Univ Calif San Diego Dept Family Med & Publ Hlth 9500 Gilman DrAtkinson HallMail Code 0811 La Jolla CA 92093 USA Arizona State Univ Sch Nutr & Hlth Promot Phoenix AZ USA Arizona State Univ Ira A Fulton Sch Engn Sch Engn Matter Transport & Energy Tempe AZ USA ESPOL Polytech Univ Escuela Super Politecn Litoral Fac Ingn Elect & Computac Guayaquil Ecuador Kaiser Permanente Washington Hlth Res Inst Seattle WA USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA

Background: Adaptive behavioral interventions are individualized interventions that vary support based on a person's evolving needs. Digital technologies enable these adaptive interventions to function at scale. Adaptive interventions show great promise for producing better results compared with static interventions related to health outcomes. Our central thesis is that adaptive interventions are more likely to succeed at helping individuals meet and maintain behavioral targets if its elements can be iteratively improved via data-driven testing (ie, optimization). control systems engineering is a discipline focused on decision making in systems that change over time and has a wealth of methods that could be useful for optimizing adaptive interventions. Objective: The purpose of this paper was to provide an introductory tutorial on when and what to do when using control systems engineering for designing and optimizing adaptive mobile health (mHealth) behavioral interventions. Overview: We start with a review of the need for optimization, building on the multiphase optimization strategy (MOST). We then provide an overview of control systems engineering, followed by attributes of problems that are well matched to control engineering. Key steps in the development and optimization of an adaptive intervention from a control engineering perspective are then summarized, with a focus on why, what, and when to do subtasks in each step.

关键词： adaptive interventions mHealth eHealth digital health control systems engineering behavior change optimization multiphase optimization strategy physical activity behavioral maintenance

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control engineering of China Special Issue on "control systems engineering"

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控制工程 2016年第12期23卷 1859-1860页

control systems contribute to every aspect of modem *** our life control systems exist in almost everywhere such as toasters,VCRs and smart *** science and technology,control systems already have widespread applications,for example,steering ships,guiding missiles and driving driverless cars in the near *** all the control systems,systems are the key platform where control should be put *** is at the system level that control shows its *** and formulating

关键词： control engineering of China Special Issue on control systems engineering

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A control systems engineering approach for adaptive behavioral interventions: illustration with a fibromyalgia intervention (vol 4, pg 275, 2014)

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TRANSLATIONAL BEHAVIORAL MEDICINE 2014年第4期4卷 439-439页

作者： Deshpande, Sunil Rivera, Daniel E. Younger, Jarred W. Nandola, Naresh N. Arizona State Univ Sch Engn Matter Control Syst Engn Lab Tempe AZ 85287 USA Univ Alabama Birmingham Dept Psychol Neuroinflammat Pain & Fatigue Lab Birmingham AL 35294 USA ABB Corp Res Ctr Bangalore Karnataka India

The term adaptive intervention has been used in behavioral medicine to describe operationalized and individually tailored strategies for prevention and treatment of chronic, relapsing disorders. control systems engineering offers an attractive means for designing and implementing adaptive behavioral interventions that feature intensive measurement and frequent decision-making over time. This is illustrated in this paper for the case of a low-dose naltrexone treatment intervention for fibromyalgia. System identification methods from engineering are used to estimate dynamical models from daily diary reports completed by participants. These dynamical models then form part of a model predictive control algorithm which systematically decides on treatment dosages based on measurements obtained under real-life conditions involving noise, disturbances, and uncertainty. The effectiveness and implications of this approach for behavioral interventions (in general) and pain treatment (in particular) are demonstrated using informative simulations.

关键词： Adaptive behavioral interventions Pain treatment Fibromyalgia Dynamical systems System identification control systems engineering Model predictive control

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Deep learning prediction of non-perfused volume without contrast agents during prostate ablation therapy

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BIOMEDICAL engineering LETTERS 2023年第1期13卷 31-40页

作者： Wright, Cameron Makela, Pietari Bigot, Alexandre Anttinen, Mikael Bostrom, Peter J. Sequeiros, Roberto Blanco Univ Turku Dept Urol Turku Finland Turku Univ Hosp Turku Finland Univ Turku Dept Diagnost Radiol Turku Finland Profound Med Corp Mississauga ON Canada

The non-perfused volume (NPV) is an important indicator of treatment success immediately after prostate ablation. However, visualization of the NPV first requires an injection of MRI contrast agents into the bloodstream, which has many downsides. Purpose of this study was to develop a deep learning model capable of predicting the NPV immediately after prostate ablation therapy without the need for MRI contrast agents. A modified 2D deep learning UNet model was developed to predict the post-treatment NPV. MRI imaging data from 95 patients who had previously undergone prostate ablation therapy for treatment of localized prostate cancer were used to train, validate, and test the model. Model inputs were T1/T2-weighted and thermometry MRI images, which were always acquired without any MRI contrast agents and prior to the final NPV image on treatment-day. Model output was the predicted NPV. Model accuracy was assessed using the Dice-Similarity Coefficient (DSC) by comparing the predicted to ground truth NPV. A radiologist also performed a qualitative assessment of NPV. Mean (std) DSC score for predicted NPV was 85% +/- 8.1% compared to ground truth. Model performance was significantly better for slices with larger prostate radii (> 24 mm) and for whole-gland rather than partial ablation slices. The predicted NPV was indistinguishable from ground truth for 31% of images. Feasibility of predicting NPV using a UNet model without MRI contrast agents was clearly established. If developed further, this could improve patient treatment outcomes and could obviate the need for contrast agents altogether. Trial Registration Numbers Three studies were used to populate the data: NCT02766543, NCT03814252 and NCT03350529.

关键词： High intensity focused ultrasound Deep learning Contrast-enhanced MRI UNet model Clinical trials-thermal ablation control systems engineering Treatment optimization

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Introduction of a Multicopter Platform for multiand transdisciplinary Education with Emphasis on Embedded and Cyber-Physical systems 15

Introduction of a Multicopter Platform for multiand transdis...

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15th IEEE Global engineering Education Conference (IEEE EDUCON)

作者： Schmitt, Patrick Beneder, Roman Univ Appl Sci Tech Wien Dept Elect Engn Vienna Austria

ISBN: (纸本)9798350394023;9798350394030

The rapid advancements in machine learning, environmental sensing hardware, modern aviation, robotics, and embedded systems highlight the need for a forward-thinking approach to interdisciplinary education. These advancements are closely linked, leading to challenges that need a comprehensive and joined-up approach. In response, this paper presents an educational platform that seamlessly blends theory with hands-on application, providing students an immersive learning experience. By interacting with a tangible representation of cyber-physical systems, students can better grasp abstract concepts, grounding their theoretical knowledge in observable outcomes. Its design emphasizes real-time interactions between embedded sensors, actuators, and onboard processors. With its modular nature, the platform supports customization to suit diverse educational objectives and spur creativity. As an open-source tool, the platform encourages a global community of learners and educators to contribute, refine, and adapt, ensuring that the tool remains relevant and up-to-date with the ever-evolving technological landscape. It features AI-on-the-edge capable hardware, a variety of environmental scanning sensors, and an embedded microcontroller hosting an open-source flight controller. This platform's adaptability fosters collaboration among students from different academic backgrounds, leading to a synergy of expertise and innovation. Beyond individual learning, the platform cultivates a community where peer-to-peer learning flourishes. AI postgraduates can exploit its robust features to craft aerial algorithms, while electronic engineering students refine motor controls, power systems, and signal processing. Such an approach promotes cross-disciplinary teamwork, bridging classroom teachings with realworld applications. The platform thus emerges as a hub for collaboration, idea exchange, and solution-seeking, underscoring the essence of modern interdisciplinary education.

关键词： Multicopter Interdisciplinary Education Embedded systems Artificial Intelligence Environmental Sensing control systems engineering

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The hot-to-cold spot quotient for SAR-based treatment planning in deep microwave hyperthermia

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INTERNATIONAL JOURNAL OF HYPERTHERMIA 2022年第1期39卷 1421-1439页

作者： Zanoli, Massimiliano Trefna, Hana Dobsicek Chalmers Univ Technol Dept Elect Engn Gothenburg Sweden

Background A necessary precondition for a successful microwave hyperthermia (HT) treatment delivered by phased arrays is the ability of the HT applicator to selectively raise the temperature of the entire tumor volume. SAR-based treatment plan (HTP) optimization methods exploit the correlation between specific absorption rate (SAR) and temperature increase in order to determine the set of steering parameters for optimal focusing, while allowing for lower model complexity. Several cost functions have been suggested in the past for this optimization problem. However, their correlation with high and homogeneous tumor temperatures remains sub-optimal in many cases. Previously, we proposed the hot-to-cold spot quotient (HCQ) as a novel cost function for SAR-based HTP optimization and showed its potential to address these issues. Materials and methods In this work, we validate the HCQ on a standard ESHO patient repository within single and multi-frequency contexts. We verify its correlation with clinical SAR and temperature indexes, and compare it to HTPs obtained using a commonly accepted cost-function for SAR-based HTP (hot-spot to target quotient, HTQ). Results and discussion The results show that low HCQ values produce better SAR (TC50, TC75) and temperature metrics (T-50, T-90) than HTQ in most patient models and frequency settings. For the deep-seated tumors, the correlation between the clinical indicators and 1/HCQ is more favorable than the correlation exhibited by 1/HTQ. Conclusion The validation confirms the ability of HCQ to promote target coverage and hot-spot suppression in SAR-based HTP optimization, resulting in higher SAR and temperature indexes for deep-seated tumors.

关键词： Hyperthermia computational modeling treatment planning cost function control systems engineering treatment optimization SAR radiofrequency microwave temperature

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Reactive Particle Swarm control Architecture and Application for Scalar Field Adaptive Navigation

Reactive Particle Swarm Control Architecture and Application...

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作者： Hart, Shae Taylor Santa Clara University

学位级别：Ph.D., Doctor of Philosophy

Adaptive navigation is a subcategory of navigation techniques that attempts to identify goal locations that satisfy specific criteria in an unknown area. In 2D scalar field adaptive navigation (SFAN), primitives navigate to or along features of interest in an unknown, possibly time-varying, planar scalar field. Features include extrema, contours, and fronts. This work solves the 2D SFAN problem using swarm robotic techniques. Robotic swarms are a subset of multi-robot systems that use decentralized control of simple interchangeable robots to perform collective actions. A subgroup of swarms is the Reactive Particle Swarm (RPS), characterized based on its simplicity, reactivity to its current environment, and flexibility of applications. Previous work in RPS lacks a unified implementation for RPS behaviors making cross-comparison and reuse challenging. This work presents a novel 1) RPS control architecture that streamlines the development of novel RPS behaviors, 2) elliptical aggregation algorithm that meets the four tenets of elliptical aggregation, and 3) series of 2D RPS SFAN primitives, and verifies all RPS base and composite behaviors using simulated and hardware-in-the-loop case studies. The architecture unifies the development of new RPS behaviors. The weighted summation of simple base behaviors and external command inputs form complex composite behaviors. This plug-and-play design concept allows for the rapid development of novel combinations of base behaviors, and emphasizes the top-down design of composite behaviors. A series of simulated and on-hardware case studies demonstrate the utility and flexibility of the architecture while establishing a library of verified RPS base behaviors. The four tenets of elliptical aggregation are 1) guidelines for swarm and ellipse parameter selection to ensure successful aggregation, 2) commandable ellipse parameters, 3) simplicity for scaling in the number of robots, and 4) adaptive sizing. The elliptical attraction behav

关键词： control architecture control systems engineering Scalar field adaptive navigation Swarm aggregation Swarm robotics

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A new fitness function for tuning parameters of Peripheral Integral Derivative controllers

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ICT EXPRESS 2022年第3期8卷 463-467页

作者： Odili, Julius Beneoluchi Noraziah, A. Babalola, Asegunloluwa Eunice Anchor Univ Lagos Dept Math Sci Lagos Nigeria Univ Malaysia Pahang Fac Comp Ctr Software Dev & Integrated Comp Pekan 26600 Pahang Malaysia

In recent years, the need for greater effectiveness and efficiency in industrial processes and procedures has made control system engineering a favored area of scientific investigation, especially the proper tuning of the parameters of Peripheral Integral Derivative (PID) controllers. This paper critically examines some issues with the present fitness functions being used by different researchers involved in metaheuristic tuning of PID controllers. It concludes with the introduction of a fitness function called the Inverse Integrated Squared Absolute Error whose experimental outcome using the African Buffalo Optimization algorithm was able to obtain zero (0) steady state error, zero (0) overshoot, 1.77 s rise time and 2.87 s steady time which is quite competitive. The paper opines that further appropriate investigations of the metaheuristic tuning of PID controllers using this latest fitness function are highly recommended since it is very simple to both implement and use. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.

关键词： control systems engineering Metaheuristic-tuning PID controllers Fitness function Inverse Integral Squared Error Computational Intelligence

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Idiographic Models of Walking Behavior for Personalized mHealth Interventions: Some Novel Approaches

Idiographic Models of Walking Behavior for Personalized mHea...

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作者： Kha, Rachael T. Arizona State University

学位级别：M.S., Master of Science/Master of Surgery

This thesis presents the development of idiographic models (i.e., single subject or N = 1) of walking behavior as a means of facilitating the design of control systems to optimize mobile health (mHealth) interventions for sedentary adults. Model-on-Demand (MoD), an adaptive modeling technique, is demonstrated as an ideal method for modeling nonlinear systems with noise on a simulated continuously stirred tank reactor (CSTR). Comparing MoD to AutoRegressive with eXogenous input (ARX) estimation, MoD outperforms ARX in terms of addressing both nonlinearity and noise in the CSTR system. With the CSTR system as an initial proof of concept, MoD is then used to model individual walking behavior using intervention data from participants of HeartSteps, a walking intervention that studies the effect of within-day suggestions. Given the number of possible measured features from which to design the MoD models, as well as the number of model parameters that influence the model’s performance, optimizing MoD models through exhaustive search is infeasible. Consequently, a discrete implementation of simultaneous perturbation stochastic approximation (DSPSA) is shown to be an efficient algorithm to find optimal models of walking behavior. Combining MoD with DSPSA, models of walking behavior were developed using participant data from Just Walk, a day-to-day walking intervention; MoD outperformed ARX models on both estimation and validation data. DSPSA was also applied to ARX modeling, highlighting the use of DSPSA to not only search over model parameters and features but also data partitioning, as DSPSA was used to evaluate models under various combinations of estimation and validation data from a single participant’s walking data. Results of this thesis point to ARX with DSPSA as a routine means for dynamic model estimation in large-scale behavioral intervention settings.

关键词： Behavioral interventions Behavioral medicine Chemical engineering control systems engineering Dynamical systems

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Fiducial markers and their impact on ablation outcome for patients treated with MR-guided transurethral ablation (TULSA): a retrospective technical analysis

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INTERNATIONAL JOURNAL OF HYPERTHERMIA 2021年第1期38卷 1677-1684页

作者： Wright, Cameron Makela, Pietari Anttinen, Mikael Sainio, Teija Bostrom, Peter J. Blanco Sequeiros, Roberto Univ Turku Dept Urol Turku Finland Turku Univ Hosp Turku Finland Univ Turku Dept Diagnost Radiol Turku Finland Univ Turku Dept Med Phys & Nucl Med Turku Finland

Objectives Fiducial markers improve accuracy in external beam radiation therapy (EBRT) for treatment of prostate cancer (PCa). However, many patients recur after EBRT necessitating additional treatment, such as MR-guided transurethral ultrasound ablation (TULSA). Residual markers may compromise TULSA through ultrasound field distortions and generation of local susceptibility artifacts. The objective was to investigate how markers affect the ablation outcome during clinical TULSA treatments. Subjects and methods A retrospective analysis was performed on nine patients with radiorecurrent PCa and residual markers who received TULSA. The MR susceptibility artifact was quantified as a function of marker type, size and orientation, in particular for thermometry. The spatial distribution of markers inside the prostate was recorded, and the resulting impact on the thermal dose was measured. The thermal dose measurements were directly compared to the residual enhancing prostatic tissue observed on the immediate and control post-TULSA contrast enhanced (CE) image. Results Successful thermal dose accumulation to the target boundary occurred for 14/20 (70%) of markers, confirmed with CE imaging. Gold markers situated simultaneously close to the urethra (<= 12 mm) and far from the target boundary (>= 13 mm) reduced the ultrasound depth of heating. Nitinol markers produced large, hypointense artifacts that disrupted thermometry and compromised treatment. Artifacts from gold markers were less pronounced, but when located near the target boundary, also affected treatment. Conclusion Marker composition, orientation and location inside the prostate can all potentially impact treatment outcome. Proper patient selection through detailed MRI screening is critical to ensure successful radiorecurrent PCa treatment outcomes with TULSA.

关键词： Clinical trials-thermal ablation control systems engineering treatment optimization high intensity focused ultrasound noninvasive thermometry thermal ablation

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