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Advanced diabetes technologies have produced increasingly favorable outcomes compared to older treatments. Disparities in practice resources have led to a treatment disparity by clinical setting, where endocrinologists typically prescribe far more such technologies than primary care providers (PCPs). Fully automated artificial pancreas systems (APS), which combine technologies to deliver and adjust insulin dosing continuously in response to automatic and continuous glucose monitoring, may be more straightforward for PCPs to prescribe and manage, therefore extending their benefit to more patients. We aimed to assess willingness of PCPs to prescribe advanced diabetes technologies through a cross-sectional survey of PCPs from 4 geographically diverse centers. While respondents were uncomfortable initiating (63 of 72, 88%) or adjusting (64 of 72, 89%) traditional insulin pumps, their views on APS were quite different: 71 of 76 (93%) saw advantages to prescribing APS by PCPs rather than only endocrinologists. Most would consider prescribing APS for type 1 diabetes (58 of 76, 76%) and type 2 diabetes (52 of 76, 68%). No differences were seen among attendings, residents, or nurse practitioners. APS were much more acceptable than traditional insulin pumps among this primary care sample. If successful, primary care management of closed-loop APS would greatly increase access to such therapies and reduce disparities among those patients who face more difficulty accessing subspecialty care than they do primary care.

This article shows both theoretical and experimental analyses of a fully integrated CMOS active gate driver (AGD) developed to control the high d v /d t of GaN transistors for both 48 and 400 V applications. To mitigate negative effects in the high-frequency spectrum emission, an original technique is proposed to reduce the d v /d t with lower switching losses compared to classical solutions. The AGD technique is based on a subnanosecond delay feedback loop, which reduces the gate current only during the d v /d t sequence of the switching transients. Hence, the d v /d t and d i /d t can be actively controlled separately, and the tradeoff between the d v /d t and E ON switching energy is optimized. Since GaN transistors have typical voltage switching times on the order of a few nanoseconds, introducing a feedback loop from the high voltage drain to the gate terminal is quite challenging. In this article, we successfully demonstrate the active gate driving of GaN transistors for both 48 and 400 V applications, with initial open-loop voltage switching times of 3 ns, due to a full CMOS integration. Other methods for d v /d t active control are further discussed. The limits of these methods are explained based on both experimental and simulation results. The AGD showed a clear reduction in the peak d v /d t from –175 to –120 V/ns for the 400 V application.

With the emergence of Industry 4.0 and Big Data initiatives there is a renewed interest in leveraging the vast amounts of data collected in (bio)chemical processes to improve their operations. The objective of this manuscript is to provide a perspective of the current status of Big Data-based process control methodologies and the most effective path to further embed these methodologies in the control of (bio)chemical processes. Therefore, this manuscript provides an overview of operational requirements, the availability and the nature of data, and the role of the control structure hierarchy in (bio)chemical processes and how they constrain this endeavor. The current state of the seemingly competing methodologies of Statistical Process Monitoring and (Engineering) Process Control is examined together with hybrid methodologies that are attempting to combine tools and techniques that belong to either camp. The technical and economic considerations of a deeper integration between the two approaches is then explored and a path forward is proposed.

Artificial lung (AL) systems provide respiratory support to patients with severe lung disease, but none can adapt to the changing respiratory needs of the patients. Precisely, none can automatically adjust carbon dioxide (CO2) removal from the blood in response to changes in patient activity or disease status. Because of this, all current systems limit patient comfort, activity level, and rehabilitation. A portable servoregulation controller that automatically modulates CO2 removal in ALs to meet the real-time metabolic demands of the patient is described. The controller is based on a proportional-integral-derivative (PID) based closed-loop feedback control system that modulates sweep gas (air) flow through the AL to maintain a target exhaust gas CO2 partial pressure (target EGCO2 or tEGCO2). The presented work advances previous research by (1) using gas-side sensing that avoids complications and clotting associated with blood-based sensors, (2) incorporating all components into a portable, battery-powered package, and (3) integrating smart moisture removal from the AL to enable long term operation. The performance of the controller was tested in vitro for ∼12 h with anti-coagulated bovine blood and 5 days with distilled water. In tests with blood, the sweep gas flow was automatically adjusted by the controller rapidly (

Knowledge of the performance of microbial electrolysis cells under a wide range of operating conditions is crucial to achieve high production efficiencies. Characterizing this performance in an experiment, however, is challenging due to either the long measurement times of steady-state procedures or the transient errors of dynamic procedures. Moreover, wide parallelization of the measurements is not feasible due to the high measurement equipment cost per channel. Hence, to speedup this characterization and to facilitate low-cost, yet widely parallel measurements, this paper presents a novel rapid polarization curve measurement procedure with a dynamic measurement resolution that runs on a custom six-channel potentiostat with a current-driven topology. As case study, the procedure is used to rapidly assess the impact of altering pH values on a microbial electrolysis cell that produces H2. A $\times 2$ – $\times 12$ speedup could be obtained in comparison with the state-of-the-art, depending on the characterization resolution (16–128 levels). On top of this speedup, measurements can be parallelized up to $6\times $ on the presented, affordable—42$-per-channel—potentiostat.

Peer reviewed: True, OBJECTIVES: Type 1 diabetes can have life-shattering consequences for adolescents and parents. A closed-loop system is a cutting-edge technology which automatically regulates glucose to reduce the burden of diabetes management. We explored adolescents' and parents' experiences of using this technology to understand how it affects their biographies and everyday lives. METHODS: In-depth interviews with 18 adolescents newly diagnosed with type 1 diabetes and 21 parents after ≥12 months experience using closed-loop technology. Data were analysed thematically. RESULTS: Participants reported very few disruptions to their lives when using a closed-loop. Reports of family conflict were minimal as the closed-loop enabled dietary flexibility and glucose levels to be checked effortlessly. Adolescents described doing 'normal' activities without worrying about high/low glucose, and parents reported allowing them to do so unsupervised because the closed-loop would regulate their glucose and keep them safe. Some adolescents expressed concerns about the visibility of components and, to avoid stigma, described curtailing activities such as swimming. Participants described how the closed-loop enabled adolescents to be in control of, or create distance from, diabetes. DISCUSSION: The closed-loop has life-enhancing consequences for both adolescents and parents and helps to reduce the biographical disruption of type 1 diabetes in this age group.

This paper deals with the territorial dimension of a circular economy. We review the territorial factors shaping closed-loop systems, upon which a territorial definition of a circular economy is developed. We consider six categories of territorial factors: (1) Land-based factors emphasize the significance of physical endowment to satisfy the growing demand of secondary and biotic materials in a circular economy; (2) agglomeration factors are important determinants for a circular economy, as these provide circular businesses with the necessary access to resources, knowledge and collaboration, as well as viable markets; some of these functions are enabled by (3) hard territorial factors, in particular by accessibility and connectivity infrastructures as well as by (4) access to state-of-the-art technologies; softer territorial factors, including (5) knowledge-related factors and (6) governance and institutional arrangements, support collaboration among companies and between them, as well as among consumers and public institutions. Our review shows that agglomeration and land-based factors contribute to define the framework conditions of circular transformations, the harder territorial factors (accessibility and technologies) enable the circular economy in practice, and the softer factors (knowledge, awareness, governance and milieus) contribute to catalyse circular transformations. These findings base and complement research done in the ESPON CIRCTER project. This work was supported by ESPON 2020 Cooperation Programme.

Due to the coronavirus disease 2019 restrictions in providing diabetes services, we have developed an innovative pump training program, which consisted of technical session, pump training, one in-person practical session, and four consecutive online sessions (Skype Meet Now). A 13-year-old female patient with a 4-year history of type 1 diabetes (T1D) on multiple daily injections (MDI) with glycated hemoglobin 8.9%; 74 mmol/mol) initiated Minimed 670G system using the program. Time in range (70-180 mg/dL) of 39% and sensor glucose (SG) of 214±91 mg/dL (MDI with continuous glucose monitoring) increased to 69% in the first 2 weeks and reached 86% and SG of 140±40 mg/dL in the first month of auto mode initiation, without severe hypoglycemia or hyperglycemia. Virtual pump training program can be an effective tool to initiate a hybrid closed-loop system and to improve glycemic control in people with T1D on MDI.

Objective To evaluate the effect of a 1-year hybrid closed-loop (HCL) system on glycemic control in children and adolescents with type 1 diabetes (T1D) previously treated with multiple daily injections (MDI). Methods This was a 1-year observational study, as a continuation of the previous 3 months prospective study of pediatric patients with T1D conducted at Sidra Medicine in Qatar. The study enrolled individuals aged 7–18 years with T1D > 1 year, on MDI with self-monitoring of blood glucose or continuous glucose monitoring, with no prior pump experience, and with an HbA1c level

Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged the ability to do face-to-face training on advanced diabetes management technologies. In the United States, Medtronic Diabetes shifted from occasional to 100% virtual training on all diabetes devices in mid-March 2020. We studied the outcomes of virtual training on the MiniMed™ 670 G hybrid closed-loop system in type 1 diabetes. Methods: From March 20, 2020, to April 22, 2020 (intra-COVID-19), virtual training on the MiniMed 670 G system was completed using Zoom with satisfaction captured through online post-training surveys. Training efficiency was measuring by the days between the date of product shipment and the date of the first and final trainings. Patient satisfaction with training on the MiniMed 670 G was determined by Net Promotor Score® (NPS®). Uploads from CareLink™ Personal and CareLink Professional and calls to the Medtronic 24-h technical support team requesting educational/software assistance and/or help with health care provider telehealth visits were recorded. Continuous glucose monitoring (CGM) results were measured using the CareLink Personal database. All results except for the Zoom satisfaction survey were compared with data from January 20, 2020, to February 22, 2020, (Pre-COVID-19) when training was performed in-person. Results: The CGM metrics were comparable between pre- and intra-COVID-19 training. The Zoom video conferencing application had 98% satisfaction. The NPS rose from 78 to 84. The time between the pump shipment and the first and last (automode) training was significantly reduced from 14 ± 7 days to 11 ± 5 days (P < 0.001) and from 19 ± 7 days to 15 ± 15 days (P < 0.01), respectively. There was a decrease in the calls for educational assistance to the technical support team but an increase in requests for login and software installation support. Conclusions: Virtual training of individuals with diabetes on the MiniMed 670 G system resulted in high satisfaction and short-term glycemic results comparable with in-person training.

Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders.

Background: Clinicians mediate access to closed-loop technology for people with diabetes. Consequently, their attitudes regarding appropriate levels of closed-loop usage will play a key role in future adoption processes. This study aimed to explore clinician attitudes toward future mainstream closed-loop usage in England. Materials and Methods: We conducted 36 semistructured interviews with clinicians from a range of professional backgrounds working in outpatient clinics in England. Interview topics included clinicians' views on future pathways for closed-loop use and attitudes toward the predictability of users' technology experiences, a key factor in eligibility decision making. We analyzed transcripts using thematic and framework approaches. Results: Clinicians exhibited a range of opinions regarding future eligibility for closed-loop technology. We identified three key strands of clinician opinion, envisaging (1) tighter access for closed loop (n = 10), citing funding challenges and issues arising from user overconfidence or negative technology attitudes; (2) similar access to closed loop as for current diabetes technologies (n = 15), on the grounds that future funding and access pathways will be similar to current arrangements; and (3) wider access for closed-loop technologies (n = 9), given the potential for significant and widespread benefits arising from closed-loop usage, including downstream cost savings alongside improved glycemic control. Conclusions: Clinicians expressed a range of opinions encompassing continuity with current diabetes technologies, while others envisaged either tighter or more liberal access for closed-loop systems. To optimize technology adoption and equitable uptake, future implementation pathways should consider clinician attitudes toward technology use and access.

This review focuses on virtual coaching systems that were designed to enhance healthcare interventions, combining the available sensing and system-user interaction technologies. In total, more than 1,200 research papers have been retrieved and evaluated for the purposes of this review, which were obtained from three online databases (i.e.,PubMed, Scopus and IEEE Xplore) using an extensive set of search keywords. After applying exclusion criteria, the remaining 41 research papers were used to evaluate the status of virtual coaching systems over the past 10 years and assess current and future trends in this field. The results suggest that in home coaching systems were mainly focused in promoting physical activity and a healthier lifestyle, while a wider range of medical domains was considered in systems that were evaluated in lab environment. In home patient monitoring with IoT devices and sensors was mostly limited to activity trackers, pedometers and heart rate monitoring. Real-time evaluations and personalized patient feedback was also found to be rather lacking in home coaching systems and this is the most alarming find of this analysis. Feasibility studies in controlled environment and an ongoing active research on Horizon 2020 funded projects, show that the future trends in this field are aiming to close the loop with automated patient monitoring, real-time evaluations and more precise interventions.

Autonomous optimization refers to the design of feedback controllers that steer a physical system to a steady state that solves a predefined, possibly constrained, optimization problem. As such, no exogenous control inputs such as setpoints or trajectories are required. Instead, these controllers are modeled after optimization algorithms that take the form of dynamical systems. The interconnection of this type of optimization dynamics with a physical system is however not guaranteed to be stable unless both dynamics act on sufficiently different timescales. In this paper, we quantify the required timescale separation and give prescriptions that can be directly used in the design of this type of feedback controllers. Using ideas from singular perturbation analysis, we derive stability bounds for different feedback laws that are based on common continuous-time optimization schemes. In particular, we consider gradient descent and its variations, including projected gradient, and Newton gradient. We further give stability bounds for momentum methods and saddle-point flows. Finally, we discuss how optimization algorithms like subgradient and accelerated gradient descent, while well-behaved in offline settings, are unsuitable for autonomous optimization due to their general lack of robustness., IEEE Transactions on Automatic Control, 66 (2), ISSN:0018-9286, ISSN:1558-2523

Background: To investigate whether closed-loop systems under bispectral index anesthesia depth monitoring can reduce the intraoperative propofol dosage. Methods: All randomized controlled trials (RCTs) on reducing propofol dosage under closed-loop systems were collected, and the literature was screened out, the abstracts and full texts were carefully read, and the references were tracked, data extraction and quality evaluation were conducted on the included research, and the RevMan5.3 software was used for meta-analysis. The main results were propofol and the incidence of adverse reactions such as hypertensive hypotension and postoperative cognitive dysfunction. A total of 879 cases were included in 8 articles, including 450 occurrences in the closed-loop system group and 429 cases in the open-loop system group. Results: Compared with manual control, closed-loop systems under bispectral index anesthesia depth monitoring reduced the dose of propofol (MD: −0.62, 95% CI: −1.08–−0.16, P = .008), with heterogeneity (I2 = 80%). Closed-loop systems significantly reduced the incidence of abnormal blood pressure (MD: −0.02, 95%CI: −0.05–0.01, P = .15, I2 = 74%) and postoperative cognitive dysfunction (MD: −0.08, 95% CI: −0.14 −0.01, P = .02, I2 = 94%). Conclusion: Bispectral index monitoring of propofol closed-loop target-controlled infusion system can reduce the amount of propofol, reduce the incidence of adverse reactions such as hypertensive or hypotension and postoperative cognitive dysfunction.

Rapid, accurate and robust glucose measurements are needed to make a safe artificial pancreas for the treatment of diabetes mellitus type 1 and 2. The present gold standard of continuous glucose sensing, subcutaneous (SC) glucose sensing, has been claimed to have slow response and poor robustness towards local tissue changes such as mechanical pressure, temperature changes, etc. The present study aimed at quantifying glucose dynamics from central circulation to intraperitoneal (IP) sensor sites, as an alternative to the SC location. Intraarterial (IA) and IP sensors were tested in three anaesthetized non-diabetic pigs during experiments with intravenous infusion of glucose boluses, enforcing rapid glucose level excursions in the range 70--360 mg/dL (approximately 3.8--20 mmol/L). Optical interferometric sensors were used for IA and IP measurements. A first-order dynamic model with time delay was fitted to the data after compensating for sensor dynamics. Additionally, off-the-shelf Medtronic Enlite sensors were used for illustration of SC glucose sensing. The time delay in glucose excursions from central circulation (IA) to IP sensor location was found to be in the range 0--26 s (median: 8.5 s, mean: 9.7 s, SD 9.5 s), and the time constant was found to be 0.5--10.2 min (median: 4.8 min, mean: 4.7 min, SD 2.9 min). IP glucose sensing sites have a substantially faster and more distinctive response than SC sites when sensor dynamics is ignored, and the peritoneal fluid reacts even faster to changes in intravascular glucose levels than reported in previous animal studies. This study may provide a benchmark for future, rapid IP glucose sensors.

This paper reports human pointing behaviors in vision-based pointing interface system, to make a mathematical model of them for designing easy-to-use interface. In natural pointing situations, we point targets at distant position with various postures, for example straight arm style or bent elbow style. We analyze their difference in pointing behaviors with assuming the pointing interface system as a feedback control model including an indicator. The difference had been confirmed in the step responses and the estimated parameters in the transfer functions, and matches to our actual experiences in those pointing styles. The estimation accuracy of indicated position from indicator's posture in the intermediate styles has been also analyzed. The results said that the reference point of indication smoothly moves from indicator's eye to his or her elbow according to the elbow joint angle., 13th IFAC Symposium on Analysis, Design, and Evaluation ofHuman-Machine Systems HMS 2016: Kyoto, Japan, 30 August--2 September 2016

Objectives: We evaluated patterns of meal intake, insulin bolus delivery, and fingerstick glucose measurements during hybrid closed-loop and sensor-augmented pump (SAP) therapy, including associations with glucose control. Methods: Data were retrospectively analyzed from pump-treated adults with type 1 diabetes who underwent, in random order, 12 weeks free-living closed-loop (n = 32) and 12 weeks SAP (n = 33) periods. We quantified daily patterns of main meals, snacks, prandial insulin boluses, correction boluses, and fingerstick glucose measurements by analyzing data recorded on the study glucometer and on study insulin pump. Results: We analyzed 1942 closed-loop days and 2530 SAP days. The total number of insulin boluses was reduced during closed-loop versus SAP periods by mean 1.0 per day (95% confidence interval 0.6–1.4, P

Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson's disease (PD), dystonia, and essential tremor (ET) consist mainly of oral medication, physical therapy, and botulinum toxin injections. Recently, the more invasive method of deep brain stimulation (DBS) showed significant improvement of the physical symptoms associated with these disorders. In the past several years, the adoption of feedback control theory helped DBS protocols to take into account the progressive and dynamic nature of these neurological movement disorders that had largely been ignored so far. As a result, a more efficient and effective management of PD cardinal symptoms has emerged. In this paper, we review closed-loop systems for rehabilitation of movement disorders, focusing on PD, for which several invasive and noninvasive methods have been developed during the last decade, reducing the complications and side effects associated with traditional rehabilitation approaches and paving the way for tailored individual therapeutics. We then present a novel, transformative, noninvasive closed-loop framework based on force neurofeedback and discuss several future developments of closed-loop systems that might bring us closer to individualized solutions for neurological rehabilitation of movement disorders.

A simple method for the automatic tuning of PID controllers in closed loop is proposed. A limit cycle is generated through a nonlinear feedback path from the process output to the controller reference signal. The frequency of this oscillation is above the crossover frequency and below the critical frequency of the loop transfer function. The amplitude and frequency of the oscillation are estimated and the control parameters are adjusted iteratively such that the closed loop transfer function from the controller reference to the process output attains a specified amplitude at the oscillation frequency.

This paper concerns the filtering problem for a class of stochastic nonlinear systems where the drift term may depend either on some external function (open-loop system) or on the system output ( closed-loop system), through a controller. Such systems are denoted feedback systems. The following result is proven: for feedback systems, the optimal filter in the open-loop case remains optimal when the feedback is closed. The proof is obtained by showing equivalence of suitable expressions for the estimators of the open-loop and closed-loop systems, obtained using the Kallianpur--Striebel formula [G. Kallianpur and C. Striebel, Ann. Math. Statist., 39 (1968), pp. 785--801].

In this paper the pole assignment with constant gain output feedback is studied for a SIMO System. A reduced order system with the set of unassigned poles satisfying the constraint conditions, obtained by removing the polynomial with the set of assigned poles, simplifies the design procedure. The root locus method is adopted for the proper fixation of the feedback gain.