26 papers · ranked by Valyu relevance
Sophie Templer
Closed-loop (artificial pancreas) systems for automated insulin delivery have been likened to the holy grail of diabetes management. The first iterations of glucose-responsive insulin delivery were pioneered in the 1960s and 1970s, with the development of systems that used venous glucose measurements to dictate…
Valerio Francioni, Anna Beltramini, Linlin Z Fan, Mark T. Harnett
Brain-Computer Interfaces (BCI) have catalyzed advancements in both clinical applications and basic neuroscience research. However, technical barriers such as steep learning curves and complex synchronization requirements often impede their widespread adoption. In response to the increasing demand for optical BCI…
Pankaj K. Gupta, Timothy H. Murphy
Most investigations study brain activity and behavior as separate channels that do not interact in real time. Assessments are typically made post hoc, and experimental contingencies are not dependent on regional brain activity fluctuations. In contrast, closed-loop brain stimulation/manipulation requires a continuous…
Yixuan Leng, Rujie Sun
Closed-loop control systems have emerged as transformative tools in precision therapy, enabling real-time monitoring of patient's physiological conditions and automatically adjusting treatments based on direct feedback. By seamlessly integrating sensing feedback and on-demand therapeutic interventions, these systems…
Nigel Gebodh, Vladimir Miskovic, Sarah Laszlo, Abhishek Datta + 1 more
Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and…
Authors not listed
The discovery of radiation-resistant polymers is vital for aerospace, medical, and energy applications, where ionizing radiation rapidly degrades conventional materials. Inspired by the impact of Google DeepMind’s AlphaFold in structural biology, this study presents a closed-loop generative AI framework for polymer…
Giulia Lafratta, Bernd Porr, Christopher Chandler, Alice Miller
We present a hierarchical framework to solve robot planning as an input control problem. At the lowest level are temporary closed control loops, ("tasks"), each representing a behaviour, contingent on a specific sensory input and therefore temporary. At the highest level, a supervising "Configurator" directs task…
Riichiro Hira
In the field of neuroscience, the importance of constructing closed-loop experimental systems has increased in conjunction with technological advances in measuring and controlling neural activity in live animals. We provide an overview of recent technological advances in the field, focusing on closed-loop experimental…
Nayeon Kim, Hyuk Jun Yoo, Daeho Kim, Heeseung Lee + 1 more
Autonomous laboratories hold great promise for accelerating material discovery but are often restricted by static, predefined experimental constraints. We present SPACESHIP, an AIdriven framework for dynamic, constraint-free exploration of synthesizable regions in chemical parameter spaces. SPACESHIP integrates…
Malcolm Sim, Mohammad Ghazi Vakili, Felix Strieth-Kalthoff, Han Hao + 4 more
Self-driving laboratories (SDLs), which combine automated experimental hardware with computational experiment planning, have emerged as powerful tools for accelerating materials discovery. The intrinsic complexity created by their multitude of components requires an effective orchestration platform to ensure the…
Julia Lawton, Barbara Kimbell, Mia Closs, Sara Hartnell + 8 more
To reduce risks of obstetric and neonatal complications, pregnant women with type 1 diabetes (T1D) are advised to keep glucose between 3.5 and 7.8 mmol/L [63-140.4 mg/dL] for ≥70% of the time.1 Women are acutely aware of the risks T1D poses to their babies and highly motivated to address them.2,3 However…
Rama Lakshman, Sara Hartnell, Julia Ware, Janet M. Allen + 5 more
To our knowledge, this is the first psychosocial evaluation of a fully automated closed-loop insulin delivery system. Interviewees universally reported a reduction in diabetes burden describing a sense of “normalcy,” “liberation,” and being “on holiday from diabetes.” They described improved mood and quality-of-life…
Steven Dahdah, James Richard Forbes
—This paper proposes a method to identify a Koopman model of a feedback-controlled system given a known controller. The Koopman operator allows a nonlinear system to be rewritten as an infinite-dimensional linear system by viewing it in terms of an infinite set of lifting functions. A finite-dimensional approximation…
Xugui Zhou, Maxfield Kouzel, Haotian Ren, Homa Alemzadeh
Artificial Pancreas Systems Authors: ['Xugui Zhou' 'Maxfield Kouzel' 'Haotian Ren' 'Homa Alemzadeh'] The development of fully autonomous artificial pancreas systems (APS) that independently regulate the glucose levels of patients with Type 1 diabetes has been a long-standing goal of diabetes research. A significant…
Ching-Hsiang Chang, Asterios Arampatzis, Samuel Balula, Mucun Hou + 4 more
Adaptive, closed-loop control of cellular behavior is essential for next-generation therapies, yet most current treatments operate in an open-loop manner and lack robustness to patient variability and disease dynamics. Here, we establish a controltheoretic platform for rational engineering of closed-loop cell-based…
Authors not listed
Self-driving laboratories (SDLs) are poised to transform materials discovery by integrating automation with machine learning (ML) to accelerate data-driven experimentation. However, most SDL frameworks remain limited by single-feedback optimization and lack the multi-modal diagnostics needed to resolve both optical and…
Alexander Pomberger, Antonio Pedrina McCarthy, Ahmad Khan, Simon Sung + 4 more
Multivariate chemical reaction optimization involving catalytic systems is a non-trivial task due to the high number of tuneable parameters and discrete choices. Closed-loop optimization featuring active Machine Learning (ML) represents a powerful strategy for automating reaction optimization. However, the translation…
Supraja S. Chittari, Zhiyue Lu
Simulating stochastic systems with feedback control is challenging due to the complex interplay between the system's dynamics and the feedback-dependent control protocols. We present a single-step-trajectory probability analysis to time-dependent stochastic systems. Based on this analysis, we revisit several…
Cédric Join, Jakub Orłowski, Antoine Chaillet, Madeleine M. Lowery + 2 more
Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an open-loop manner using fixed stimulation parameters, which may lead to suboptimal…
Rory Crean, Marina Corbella, Ana Rita Calixto, Alvan Hengge + 1 more
Protein tyrosine phosphatases are crucial regulators of cellular signaling. Their activity is regulated by the motion of a conserved loop, the WPD-loop, from a catalytically inactive open to a catalytically active closed conformation. WPD-loop motion optimally positions a catalytically critical residue into the active…
Heather Orser, Preston Doan
This paper describes the operation of a low-noise amplifier and neurostimulation circuit when both functions are used simultaneously. The design of this circuitry along with the circuit model used to investigate system interactions is described. Expected circuit operation is explored in conjunction with the impact of…
Xiaoyu Zhang, Zhou Fang
This paper introduces a biomolecular Linear Quadratic Regulator (LQR) to investigate the design principles of gene regulatory networks. We show that for fundamental gene regulation network, the bio-controller derived from LQR theory precisely recapitulate natural network motifs, such as auto-regulation and incoherent…
Authors not listed
Despite the promise of self-driving laboratories to accelerate discovery, their widespread implementation is hindered by prohibitive cost and technical complexity. We introduce BrickSDLab, a fully functional self-driving lab platform built entirely from LEGO® components, designed to bridge this accessibility gap.…
Willem S. van Hoogstraten, Elías M. Fernandez Santoro, Lorena M. Hähner, Chris I. De Zeeuw
Neocerebellum facilitates motor and cognitive behavior via olivocerebellar modules, in which Purkinje cells (PCs), cerebellar nuclei (CN) neurons and olivary cells are supposed to form exclusively closed-loops. Here, we show that parts of the modules can be organized in an open-loop feedforward fashion where PCs do not…
Daniel Baker, Jeremy Wojcik, Sean Phillips
Autonomy at Levels is the idea that autonomy should be embedded within and throughout a spacecraft. Using Systems Engineering methods a spacecraft is typically decomposed into systems, subsystems, assemblies, components, and so on. All these decomposition levels within all the spacecraft's systems, could and should…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…