Continuous glucose monitoring sensors: Past, present and future algorithmic challenges

Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors’ lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management.

OBJECTIVE:Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. MATERIALS AND METHODS:An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. RESULTS:Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. DISCUSSION:By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. CONCLUSION:The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases

The bio-inspired artificial pancreas for type 1 diabetes control in the home: System architecture and preliminary results

BACKGROUND: Artificial pancreas (AP) technology has been proven to improve glucose and patient-centered outcomes for people with type 1 diabetes (T1D). Several approaches to implement the AP have been described, clinically evaluated, and in one case, commercialized. However, none of these approaches has shown a clear superiority with respect to others. In addition, several challenges still need to be solved before achieving a fully automated AP that fulfills the users' expectations. We have introduced the Bio-inspired Artificial Pancreas (BiAP), a hybrid adaptive closed-loop control system based on beta-cell physiology and implemented directly in hardware to provide an embedded low-power solution in a dedicated handheld device. In coordination with the closed-loop controller, the BiAP system incorporates a novel adaptive bolus calculator which aims at improving postprandial glycemic control. This paper focuses on the latest developments of the BiAP system for its utilization in the home environment. METHODS: The hardware and software architectures of the BiAP system designed to be used in the home environment are described. Then, the clinical trial design proposed to evaluate the BiAP system in an ambulatory setting is introduced. Finally, preliminary results corresponding to two participants enrolled in the trial are presented. RESULTS: Apart from minor technical issues, mainly due to wireless communications between devices, the BiAP system performed well (~88% of the time in closed-loop) during the clinical trials conducted so far. Preliminary results show that the BiAP system might achieve comparable glycemic outcomes to the existing AP systems (~73% time in target range 70-180 mg/dL). CONCLUSION: The BiAP system is a viable platform to conduct ambulatory clinical trials and a potential solution for people with T1D to control their glucose control in a home environment

The OmniPod Insulin Management System: the latest innovation in insulin pump therapy

This review of insulin pump therapy focuses on the OmniPod® Insulin Management System (Insulet Corp., Bedford, MA, USA). The OmniPod System is the first commercially available “patch pump.” It is a fully integrated wearable pump, controlled wirelessly through a handheld device containing a built-in blood glucose meter. This is an evaluation of the OmniPod System, with the aim of providing an educational tool for physicians who are considering recommending this product to their patients. The review includes a discussion of the traditional insulin pump configuration and its limitations, a detailed overview of the OmniPod System, references to clinical study data, planned product enhancements, its use as an insulin delivery system in the Juvenile Diabetes Research Foundation’s Artificial Pancreas Project, and its use to deliver additional compounds

Design and Validation of an Open-Source Closed-Loop Testbed for Artificial Pancreas Systems

The development of a fully autonomous artificial pancreas system (APS) to independently regulate the glucose levels of a patient with Type 1 diabetes has been a long-standing goal of diabetes research. A significant barrier to progress is the difficulty of testing new control algorithms and safety features, since clinical trials are time- and resource-intensive. To facilitate ease of validation, we propose an open-source APS testbed by integrating APS controllers with two state-of-the-art glucose simulators and a novel fault injection engine. The testbed is able to reproduce the blood glucose trajectories of real patients from a clinical trial conducted over six months. We evaluate the performance of two closed-loop control algorithms (OpenAPS and Basal Bolus) using the testbed and find that more advanced control algorithms are able to keep blood glucose in a safe region 93.49% and 79.46% of the time on average, compared with 66.18% of the time for the clinical trial. The fault injection engine simulates the real recalls and adverse events reported to the U.S. Food and Drug Administration (FDA) and demonstrates the resilience of the controller in hazardous conditions. We used the testbed to generate 2.5 years of synthetic data representing 20 different patient profiles with realistic adverse event scenarios, which would have been expensive and risky to collect in a clinical trial. The proposed testbed is a valid tool that can be used by the research community to demonstrate the effectiveness of different control algorithms and safety features for APS.Comment: 12 pages, 12 figures, to appear in the IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 202

Testing and Validation Framework for Closed-Loop Physiology Management Systems for Critical and Perioperative Care

The research aims at developing a framework for testing systems such as closed-loop physiology management systems to ensure that they are safe and effective for use with patients. Building medical devices that are both robust and safe is a challenge. There has been a tremendous increase in modernization and innovation of various medical systems but many of these systems either fail trials or are recalled due to safety issues. Medical operation rooms require care teams responsible for monitoring the patients and other technical surgical devices. The care process requires a balancing administration that takes care of the drugs and fluids administered to patients. However, the safety and efficacy of these devices have been a concern to many medical practitioners and patients. Due to the complexity of surgical procedures, more fluids are required leading to a necessity of multiple pumps. To help the team in such circumstances, systems called closed loop assistants (CLAs) have been proposed. These systems help by monitoring the patient and possibly adjust infusions while clinicians maintain supervisory control. This thesis provides a framework for testing and validating CLAs through the use of computer simulations of human physiology called in silico patients. A simulated case study based on low blood pressure management in ICU is used to show how the framework can be used in software-only fast simulations or in real-time simulations. The results show that not only can the framework show what a CLA may do in terms of managing physiology but can also give insight as to why. The hope is that this framework will be useful to researchers and practitioners as they develop CLAs since they can test ideas early and often

M-CDS: Mobile Carbohydrate Delivery System

When patients with type 1 diabetes (T1D) are physically active, they encounter an issue with keeping their blood glucose (BG) stable. Generally, their blood glucose level (BGL) will drop, causing hypoglycaemia which can have fatal consequences. The simple solution is to consume carbohydrates in the form of liquids or food, but during physical activities, it can be difficult to follow their BGL at the same time as they exercise. This thesis presents the design and implementation of a mobile carbohydrate delivery system, M-CDS. Previous work has shown that it is possible to create a stationary carbohydrate delivery system that reads the user’s BG data in real-time, gives feedback to the user when their BGL is nearing hypoglycaemia, and issues a dose of juice with 15 grams of carbohydrates. The proof-of-concept system in this thesis has the same functions but is contained within a modified CamelBak backpack. A Raspberry Pi, together with various sensors and a peristaltic pump, can transfer juice from a drinking reservoir to a drinking tube, which the user can easily drink from while physically active. The results show that the backpack works as intended and was able to avoid a BGL under 3.9 mmol/L while testing the system with a user using physical activity, thus successfully avoiding a hypoglycaemic event. As the system is a proof-of-concept, many things can be improved or modified to create a more robust, user-friendly, compact, and complex system. However, creating a prototype proved to be a time-costly project, whereas future work can use this project as a base to further improve it