Weimer, James

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Now showing 1 - 10 of 17
  • Publication
    Computer Aided Clinical Trials for Implantable Cardiac Devices
    (2018-07-12) Jang, Kuk Jin; Weimer, James; Abbas, Houssam; Jiang, Zhihao; Liang, Jackson; Dixit, Sanjay; Mangharam, Rahul
    In this paper we aim to answer the question, ``How can modeling and simulation of physiological systems be used to evaluate life-critical implantable medical devices?'' Clinical trials for medical devices are becoming increasingly inefficient as they take several years to conduct, at very high cost and suffer from high rates of failure. For example, the Rhythm ID Goes Head-to-head Trial (RIGHT) sought to evaluate the performance of two arrhythmia discriminator algorithms for implantable cardioverter defibrillators, Vitality 2 vs. Medtronic, in terms of time-to-first inappropriate therapy, but concluded with results contrary to the initial hypothesis - after 5 years, 2,000+ patients and at considerable ethical and monetary cost. In this paper, we describe the design and performance of a computer-aided clinical trial (CACT) for Implantable Cardiac Devices where previous trial information, real patient data and closed-loop device models are effectively used to evaluate the trial with high confidence. We formulate the CACT in the context of RIGHT using a Bayesian statistical framework. We define a hierarchical model of the virtual cohort generated from a physiological model which captures the uncertainty in the parameters and allows for the systematic incorporation of information available at the design of the trial. With this formulation, the CACT estimates the inappropriate therapy rate of Vitality 2 compared to Medtronic as 33.22% vs 15.62% (p
  • Publication
    Verisig: verifying safety properties of hybrid systems with neural network controllers
    (2019-04-01) Ivanov, Radoslav; Weimer, James; Alur, Rajeev; Pappas, George J.; Lee, Insup
    This paper presents Verisig, a hybrid system approach to verifying safety properties of closed-loop systems using neural networks as controllers. We focus on sigmoid-based networks and exploit the fact that the sigmoid is the solution to a quadratic differential equation, which allows us to transform the neural network into an equivalent hybrid system. By composing the network’s hybrid system with the plant’s, we transform the problem into a hybrid system verification problem which can be solved using state-of-theart reachability tools. We show that reachability is decidable for networks with one hidden layer and decidable for general networks if Schanuel’s conjecture is true. We evaluate the applicability and scalability of Verisig in two case studies, one from reinforcement learning and one in which the neural network is used to approximate a model predictive controller.
  • Publication
    Verifying the Safety of Autonomous Systems with Neural Network Controllers
    (2020-12-01) Ivanov, Radoslav; Carpenter, Taylor J.; Weimer, James; Alur, Rajeev; Pappas, George; Lee, Insup
    This paper addresses the problem of verifying the safety of autonomous systems with neural network (NN) controllers. We focus on NNs with sigmoid/tanh activations and use the fact that the sigmoid/tanh is the solution to a quadratic differential equation. This allows us to convert the NN into an equivalent hybrid system and cast the problem as a hybrid system verification problem, which can be solved by existing tools. Furthermore, we improve the scalability of the proposed method by approximating the sigmoid with a Taylor series with worst-case error bounds. Finally, we provide an evaluation over four benchmarks, including comparisons with alternative approaches based on mixed integer linear programming as well as on star sets.
  • Publication
    OpenICE-lite: Towards a Connectivity Platform for the Internet of Medical Things
    (2018-05-01) Ivanov, Radoslav; Nguyen, Hung; Weimer, James; Sokolsky, Oleg; Lee, Insup
    The Internet of Medical Things (IoMT) is poised to revolutionize medicine. However, medical device communication, coordination, and interoperability present challenges for IoMT applications due to safety, security, and privacy concerns. These challenges can be addressed by developing an open platform for IoMT that can provide guarantees on safety, security and privacy. As a first step, we introduce OpenICE-lite, a middleware for medical device interoperability that also provides security guarantees and allows other IoMT applications to view/analyze the data in real time. We describe two applications that currently utilize OpenICE-lite, namely (i) a critical pulmonary shunt predictor for infants during surgery; (ii) a remote pulmonary monitoring systems (RePulmo). Implementations of both systems are utilized by the Children’s Hospital of Philadelphia (CHOP) as quality improvements to patient care.
  • Publication
    LogSafe: Secure and Scalable Data Logger for IoT Devices
    (2018-04-01) Nguyen, Hung; Ivanov, Radoslav; Phan, Linh T.X.; Sokolsky, Oleg; Weimer, James; Lee, Insup
    As devices in the Internet of Things (IoT) increase in number and integrate with everyday lives, large amounts of personal information will be generated. With multiple discovered vulnerabilities in current IoT networks, a malicious attacker might be able to get access to and misuse this personal data. Thus, a logger that stores this information securely would make it possible to perform forensic analysis in case of such attacks that target valuable data. In this paper, we propose LogSafe, a scalable, fault-tolerant logger that leverages the use of Intel Software Guard Extensions (SGX) to store logs from IoT devices efficiently and securely. Using the security guarantees of SGX, LogSafe is designed to run on an untrusted cloud infrastructure and satisfies Confidentiality, Integrity, and Availability (CIA) security properties. Finally, we provide an exhaustive evaluation of LogSafe in order to demonstrate that it is capable of handling logs from a large number of IoT devices and at a very high data transmission rate.
  • Publication
    Cloud-Based Secure Logger for Medical Devices
    (2016-06-01) Nguyen, Hung; Ivanov, Radoslav; Haeberlen, Andreas; Phan, Linh T.X.; Sokolsky, Oleg; Weimer, James; Hanson III, C. William; Acharya, Bipeen; Lee, Insup; Walker, Jesse
    A logger in the cloud capable of keeping a secure, time-synchronized and tamper-evident log of medical device and patient information allows efficient forensic analysis in cases of adverse events or attacks on interoperable medical devices. A secure logger as such must meet requirements of confidentiality and integrity of message logs and provide tamper-detection and tamper-evidence. In this paper, we propose a design for such a cloud-based secure logger using the Intel Software Guard Extensions (SGX) and the Trusted Platform Module (TPM). The proposed logger receives medical device information from a dongle attached to a medical device. The logger relies on SGX, TPM and standard encryption to maintain a secure communication channel even on an untrusted network and operating system. We also show that the logger is resilient against different kinds of attacks such as Replay attacks, Injection attacks and Eavesdropping attacks.
  • Publication
    Willingness to Use a Wearable Device Capable of Detecting and Reversing Overdose Among People Who Use Opioids in Philadelphia
    (2021-07-01) Kanter, Katie; Gallagher, Ryan; Eweje, Feyisope; Lee, Alexander; Gordon, David; Landy, Stephen; Gasior, Julia; Soto-Calderon, Haideliza; Cronholm, Peter F; Weimer, James; Cocchiaro, Ben; Roth, Alexis; Brenner, Jacob; Lankenau, Stephen
    Background: The incidence of opioid-related overdose deaths has been rising for 30 years and has been further exacerbated amidst the COVID-19 pandemic. Naloxone can reverse opioid overdose, lower death rates, and enable a transition to medication for opioid use disorder. Though current formulations for community use of naloxone have been shown to be safe and effective public health interventions, they rely on bystander presence. We sought to understand the preferences and minimum necessary conditions for wearing a device capable of sensing and reversing opioid overdose among people who regularly use opioids. Methods: We conducted a combined cross-sectional survey and semi-structured interview at a respite center, shelter, and syringe exchange drop-in program in Philadelphia, Pennsylvania, USA during the COVID-19 pandemic in August and September 2020. The primary aim was to explore the proportion of participants who would use a wearable device to detect and reverse overdose. Preferences regarding designs and functionalities were collected via a questionnaire with items having Likert-based response options and a semi-structured interview intended to elicit feedback on prototype designs. Independent variables included demographics, opioid use habits, and previous experience with overdose. Results: A total of 97 adults with an opioid-use history of at least 3 months were interviewed. A majority of survey participants (76%) reported a willingness to use a device capable of detecting an overdose and automatically administering a reversal agent upon initial survey. When reflecting on the prototype, most respondents (75.5%) reported that they would wear the device always or most of the time. Respondents indicated discreetness and comfort as important factors that increased their chance of uptake. Respondents suggested that people experiencing homelessness and those with low tolerance for opioids would be in greatest need of the device. Conclusions: The majority of people sampled with a history of opioid use in an urban setting were interested in having access to a device capable of detecting and reversing an opioid overdose. Participants emphasized privacy and comfort as the most important factors influencing their willingness to use such a device. Trial Registration: NCT04530591
  • Publication
    Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery
    (2021-02-01) Kohl Malone, Susan; Peleckis, Amy J.; Jang, Sooyong; Grunin, Laura; Weimer, James; Yu, Gary; Lee, Insup; Rickels, Michael R.; Goel, Namni
    Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age = 58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen’s d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d = 0:47‐0:79), reduced basal insulin requirements (d = 0:48), and a smaller glucose coefficient of variation (d = 0:47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d = 0:60), lability index (d = 0:50), HYPO score (d = 1:06)). Shorter sleep onset latency (d = 1:53; p < 0:01), shorter sleep duration (d = 0:79), fewer total activity counts (d = 1:32), shorter average awakening length (d = 0:46), and delays in sleep onset (d = 1:06) and sleep midpoint (d = 0:72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914).
  • Publication
    Cyber-Physical System Checkpointing and Recovery
    (2018-04-01) Kong, Fanxin; Xu, Meng; Weimer, James; Sokolsky, Oleg; Lee, Insup
    Transitioning to more open architectures has been making Cyber-Physical Systems (CPS) vulnerable to malicious attacks that are beyond the conventional cyber attacks. This paper studies attack-resilience enhancement for a system under emerging attacks in the environment of the controller. An effective way to address this problem is to make system state estimation accurate enough for control regardless of the compromised components. This work follows this way and develops a procedure named CPS checkpointing and recovery, which leverages historical data to recover failed system states. Specially, we first propose a new concept of physical-state recovery. The essential operation is defined as rolling the system forward starting from a consistent historical system state. Second, we design a checkpointing protocol that defines how to record system states for the recovery. The protocol introduces a sliding window that accommodates attack-detection delay to improve the correctness of stored states. Third, we present a use case of CPS checkpointing and recovery that deals with compromised sensor measurements. At last, we evaluate our design through conducting simulator-based experiments and illustrating the use of our design with an unmanned vehicle case study.
  • Publication
    RePulmo: A Remote Pulmonary Monitoring System
    (2018-04-01) Nguyen, Hung; Ivanov, Radoslav; DeMauro, Sara B.; Weimer, James
    Remote physiological monitoring is increasing in popularity with the evolution of technologies in the healthcare industry. However, the current solutions for remote monitoring of blood-oxygen saturation, one of the most common continuously monitored vital signs, either have inconsistent accuracy or are not secure for transmitting over the network. In this paper, we propose RePulmo, an open-source platform for secure and accurate remote pulmonary data monitoring. RePulmo satisfies both robustness and security requirements by utilizing hospital-grade pulse oximeter devices with multiple layers of security enforcement. We describe two applications of RePulmo, namely (1) a remote pulmonary monitoring system for infants to support the Children’s Hospital of Philadelphia (CHOP) clinical trial; (2) a proof-of-concept of a low SpO2 smart alarm system.