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Objective.Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g. Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g. C and C++).Approach.To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termednodes, which communicate with each other in agraphvia streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis, an in-memory database, to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes.Main results.In our tests, BRAND achieved

BackgroundPeople living with multiple sclerosis (MS) face a higher likelihood of being diagnosed with a depressive disorder than the general population. Although many low-cost screening tools and evidence-based interventions exist, depression in people living with MS is underreported, underascertained by clinicians, and undertreated.ObjectiveThis study aims to design a closed-loop tool to improve depression care for these patients. It would support regular depression screening, tie into the point of care, and support shared decision-making and comprehensive follow-up. After an initial development phase, this study involved a proof-of-concept pilot randomized controlled trial (RCT) validation phase and a detailed human-centered design (HCD) phase.MethodsDuring the initial development phase, the technological infrastructure of a clinician-facing point-of-care clinical dashboard for MS management (BRIDGE) was leveraged to incorporate features that would support depression screening and comprehensive care (Care Technology to Ascertain, Treat, and Engage the Community to Heal Depression in people living with MS [MS CATCH]). This linked a patient survey, in-basket messages, and a clinician dashboard. During the pilot RCT phase, a convenience sample of 50 adults with MS was recruited from a single MS center with 9-item Patient Health Questionnaire scores of 5-19 (mild to moderately severe depression). During the routine MS visit, their clinicians were either asked or not to use MS CATCH to review their scores and care outcomes were collected. During the HCD phase, the MS CATCH components were iteratively modified based on feedback from stakeholders: people living with MS, MS clinicians, and interprofessional experts.ResultsMS CATCH links 3 features designed to support mood reporting and ascertainment, comprehensive evidence-based management, and clinician and patient self-management behaviors likely to lead to sustained depression relief. In the pilot RCT (n=50 visits), visits in which the clinician was randomized to use MS CATCH had more notes documenting a discussion of depressive symptoms than those in which MS CATCH was not used (75% vs 34.6%; χ21=8.2; P=.004). During the HCD phase, 45 people living with MS, clinicians, and other experts participated in the design and refinement. The final testing round included 20 people living with MS and 10 clinicians including 5 not affiliated with our health system. Most scoring targets for likeability and usability, including perceived ease of use and perceived effectiveness, were met. Net Promoter Scale was 50 for patients and 40 for clinicians.ConclusionsCreated with extensive stakeholder feedback, MS CATCH is a closed-loop system aimed to increase communication about depression between people living with MS and their clinicians, and ultimately improve depression care. The pilot findings showed evidence of enhanced communication. Stakeholders also advised on trial design features of a full year long Department of Defense-funded feasibility and efficacy trial, which is now underway.Trial registrationClinicalTrials.gov NCT05865405; http://tinyurl.com/4zkvru9x.

The objective of this research was to conduct a comprehensive analysis of the consumer decision-making process related to the disposal of goods. To achieve this, we developed an integrative model that combines theoretical approaches to consumer decision-making, a taxonomy of disposal decisions, and studies on the disposal behavior of goods with utilitarian, hedonic, and emotional value. Data for this study were collected through interviews using semi-structured scripts and the administration of forms. Subsequently, the collected data underwent content analysis, employing predefined and emergent categories, as well as descriptive statistics. The main outcome of this research is the proposed model of the consumer decision-making process for the disposal of goods. Specifically, the study emphasizes the importance of assigning residual value to goods as an intermediate step before selecting an alternative disposal method. Additionally, it identifies the post-discard evaluation, where individuals reflect on their decision and assess whether the outcome was satisfactory, leading to positive or negative feelings and emotions. Furthermore, this research sheds light on novel factors that influence the decision to discard goods. These factors encompass both environmental and individual influencers, as well as attributes associated with the goods themselves, such as altruism, visual discomfort, and the desire for a cleaner space. This article contributes to the field with its scientific value and originality, as it adopts an integrative approach to understanding consumer behavior regarding the disposal of goods. Notably, this study is the first of its kind conducted within public universities in a developing country. It specifically addresses the promotion of conscious consumption and responsible disposal of obsolete goods in the marketplace. [ABSTRACT FROM AUTHOR]

Neurological disorders affect millions globally and necessitate advanced treatments, especially with an aging population. Brain Machine Interfaces (BMIs) and neuroprostheses show promise in addressing disabilities by mimicking biological dynamics through biomimetic Spiking Neural Networks (SNNs). Central Pattern Generators (CPGs) are small neural networks that, emulated through biomimetic networks, can replicate specific locomotion patterns. Our proposal involves a real-time implementation of a biomimetic SNN on FPGA, utilizing biomimetic models for neurons, synaptic receptors and synaptic plasticity. The system, integrated into a snake-like mobile robot where the neuronal activity is responsible for its locomotion, offers a versatile platform to study spinal cord injuries. Lastly, we present a preliminary closed-loop experiment involving bidirectional interaction between the artificial neural network and biological neuronal cells, paving the way for bio-hybrid robots and insights into neural population functioning. [ABSTRACT FROM AUTHOR]

Brain-computer interfaces (BCIs) represent a groundbreaking approach to enabling direct communication for individuals with severe motor impairments, circumventing traditional neural and muscular pathways. Among the diverse array of BCI technologies, electroencephalogram (EEG)-based systems are particularly favored due to their non-invasive nature, user-friendly operation, and cost-effectiveness. Recent advancements have facilitated the development of adaptive bidirectional closed-loop BCIs, which dynamically adjust to users’ brain activity, thereby enhancing responsiveness and efficacy in neurorehabilitation. These systems support real-time modulation and continuous feedback, fostering personalized therapeutic interventions that align with users’ neural and behavioral responses. By incorporating machine learning algorithms, these BCIs optimize user interaction and promote recovery outcomes through mechanisms of activity-dependent neuroplasticity. This paper reviews the current landscape of EEG-based adaptive bidirectional closed-loop BCIs, examining their applications in the recovery of motor and sensory functions, as well as the challenges encountered in practical implementation. The findings underscore the potential of these technologies to significantly enhance patients’ quality of life and social interaction, while also identifying critical areas for future research aimed at improving system adaptability and performance. As advancements in artificial intelligence continue, the evolution of sophisticated BCI systems holds promise for transforming neurorehabilitation and expanding applications across various domains. [ABSTRACT FROM AUTHOR]

Aim Method Results Conclusion To understand experiences of using second‐generation advanced hybrid closed‐loop (AHCL) therapy in adolescents and young adults with chronically elevated glucose levels who were previously using multiple daily injections (MDI) therapy.Semi‐structured interviews with participants aged 13–25 years, on AHCL therapy for 3 months as part of a single‐arm prospective study. Key inclusions: HbA1c ≥69 mmol/mol (8.5%); diabetes duration ≥1 year; and using MDI therapy prior to the study. Qualitative content analysis was used to identify themes and subthemes.Interviews were conducted among 14 participants with mean age 19.4 ± 4.3 years and mean baseline HbA1c 90 ± 25 mmol/mol (10.4 ± 4.5%). Three themes were identified: (1) substantially improved glucose levels improved perceptions of overall health; (2) features of AHCL aid in adoption and ongoing self‐management; and (3) burden of care was reduced through automation of insulin delivery. Overall, there were positive impacts on physical, mental and social well‐being. Participants were willing to overlook minor frustrations with AHCL because of the vast benefits that they had experienced. Four participants reported transient pseudo‐hypoglycaemia: symptoms of hypoglycaemia when objectively measured glucose was in the clinically recommended range (3.9–10 mmol/L, 70–180 mg/dL).Transition to AHCL therapy positively impacted diabetes management in adolescents and youth with chronically elevated glucose levels. It appears to create a window of opportunity in which youth may re‐engage with diabetes management. Pseudo‐hypoglycaemia can occur during the transition to AHCL. This could be a barrier to AHCL uptake and is likely to require individualised support. [ABSTRACT FROM AUTHOR]

Bioelectronic implantable devices are adept at facilitating continuous monitoring of health and enabling the early detection of diseases, offering insights into the physiological conditions of various bodily organs. Furthermore, these advanced systems have therapeutic capabilities in neuromodulation, demonstrating their efficacy in addressing diverse medical conditions through the precise delivery of stimuli directly to specific targets. This comprehensive review explores developments and applications of bioelectronic devices within the biomedical field. Special emphasis is placed on the evolution of closed‐loop systems, which stand out for their dynamic treatment adjustments based on real‐time physiological feedback. The integration of Artificial Intelligence (AI) and edge computing technologies is discussed, which significantly bolster the diagnostic and therapeutic functions of these devices. By addressing elemental analyses, current challenges, and future directions in implantable devices, the review aims to guide the pathway for advances in bioelectronic devices. [ABSTRACT FROM AUTHOR]

Introduction: Closed-loop spinal cord stimulation (CL-SCS) is a recently introduced system that records evoked compound action potentials (ECAPs) from the spinal cord elicited by each stimulation pulse and uses this information to automatically adjust the stimulation strength in real time, known as ECAP-controlled SCS. This innovative system compensates for fluctuations in the distance between the epidural leads and the spinal cord by maintaining the neural response (ECAP) at a predetermined target level. This data collection study was designed to assess the performance of the first CL-SCS system in a real-world setting under normal conditions of use in multiple European centers. The study analyzes and presents clinical outcomes and electrophysiological and device data and compares these findings with those reported in earlier pre-market studies of the same system. Methods: This prospective, multicenter, observational study was conducted in 13 European centers and aimed to gather electrophysiological and device data. The study focused on the real-world application of this system in treating chronic pain affecting the trunk and/or limbs, adhering to standard conditions of use. In addition to collecting and analyzing basic demographic information, the study presents data from the inaugural patient cohort permanently implanted at multiple European centers. Results: A significant decrease in pain intensity was observed for overall back or leg pain scores (verbal numerical rating score [VNRS]) between baseline (mean ± standard error of the mean [SEM]; n = 135; 8.2 ± 0.1), 3 months (n = 93; 2.3 ± 0.2), 6 months (n = 82; 2.5 ± 0.3), and 12 months (n = 76; 2.5 ± 0.3). Comparison of overall pain relief (%) to the AVALON and EVOKE studies showed no significant differences at 3 and 12 months between the real-world data release (RWE; 71.3%; 69.6%) and the AVALON (71.2%; 73.6%) and EVOKE (78.1%; 76.7%) studies. Further investigation was undertaken to objectively characterize the physiological parameters of SCS therapy in this cohort using the metrics of percent time above ECAP threshold (%), dose ratio, and dose accuracy (µV), according to previously described methods. Results showed that a median of 90% (40.7–99.2) of stimuli were above the ECAP threshold, with a dose ratio of 1.3 (1.1–1.4) and dose accuracy of 4.4 µV (0.0–7.1), based on data from 236, 230, and 254 patients, respectively. Thus, across all three metrics, the majority of patients had objective therapy metrics corresponding to the highest levels of pain relief in previously reported studies (usage over threshold > 80%, dose ratio > 1.2, and error < 10 µV). Conclusions: In conclusion, this study provides valuable insights into the real-world application of the ECAP-controlled CL-SCS system, highlighting its potential for maintaining effective pain relief and objective neurophysiological therapy metrics at levels seen in randomized control trials, and potential for quantifying patient burden associated with SCS system use via patient–device interaction metrics. Clinical Trial Registration: In the Netherlands, the study is duly registered on the International Clinical Trials Registry Platform (Trial NL7889). In Germany, the study is duly registered as NCT05272137 and in the United Kingdom as ISCRTN27710516 and has been reviewed by the ethics committee in both countries. [ABSTRACT FROM AUTHOR]

This review outlines some of the extraordinary recent advances in diabetes technology, which are transforming the management of type 1 diabetes before, during and after pregnancy. It highlights recent improvements associated with use of continuous glucose monitoring (CGM) but acknowledges that neither CGM nor insulin pump therapy are adequate for achieving the pregnancy glucose targets. Furthermore, even hybrid closed-loop (HCL) systems that are clinically effective outside of pregnancy may not confer additional benefits throughout pregnancy. To date, there is only one HCL system, the CamAPS FX, with a strong evidence base for use during pregnancy, suggesting that the pregnancy benefits are HCL system specific. This is in stark contrast to HCL system use outside of pregnancy, where benefits are HCL category specific. The CamAPS FX HCL system has a rapidly adaptive algorithm and lower glucose targets with benefits across all maternal glucose categories, meaning that it is applicable for all women with type 1 diabetes, before and during pregnancy. For women of reproductive years living with type 2 diabetes, the relative merits of using non-insulin pharmacotherapies vs diabetes technology (dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium−glucose cotransporter 2 inhibitors) are unknown. Despite the urgent unmet need and potential benefits, studies of pharmacotherapy and technology use are extremely limited in pregnant women with type 2 diabetes. [ABSTRACT FROM AUTHOR]

The role of automated insulin delivery systems in diabetes is expanding. Hybrid closed-loop systems are being used in routine clinical practice for treating people with type 1 diabetes. Encouragingly, real-world data reflects the performance and usability observed in clinical trials. We review the commercially available hybrid closed-loop systems, their distinctive features and the associated real-world data. We also consider emerging indications for closed-loop systems, including the treatment of type 2 diabetes where variability of day-to-day insulin requirements is high, and other challenging applications for this technology. We discuss issues around access and implementation of closed-loop technology, and consider the limitations of present closed-loop systems, as well as innovative approaches that are being evaluated to improve their performance. [ABSTRACT FROM AUTHOR]

Movement is a central behavior of daily living; thus lost or compromised movement due to disease, injury, or amputation causes enormous loss of productivity and quality of life. While prosthetics have evolved enormously over the years, restoring natural sensorimotor (SM) control via a prosthesis is a difficult problem which neuroengineering has yet to solve. With a focus on upper limb prosthetics, this perspective article discusses the neurophysiology of motor control under healthy conditions and after amputation, the development of upper limb prostheses from early generations to current state-of-the art sensorimotor neuroprostheses, and how postinjury changes could complicate prosthetic control. Current challenges and future development of smart sensorimotor neuroprostheses are also discussed. [ABSTRACT FROM AUTHOR]

Grinding is a commonly employed surgical technique for the partial removal of bone. However, the grinding process often generates excessive heat at the interface, leading to localized temperature raise. This can result in irreversible damage to not only the bone but also surrounding tissues, such as nerves. Existing devices rely on the continuous application of coolant to mitigate temperature rise. With the rate and location of coolant deposition being primarily empirical, the current process brings potential risks to patients. In this study, a novel grinding device capable of continuously monitoring grinding temperatures and applying coolant precisely when needed is designed. Utilizing additive manufacturing techniques, a customized grinding tool head equipped with embedded temperature sensors and coolant channels is successfully created. This innovation has enabled the development of an intelligent closed‐loop device that provides precise temperature control during surgery. The device effectively maintains the grinding surface temperature within the user‐defined range, with a latency of less than 1 s. Furthermore, the design ensures that the coolant spray outlets remain unobstructed by debris during grinding and effectively removes debris at the interface, reducing the risk of potential complications, such as bone hyperplasia. [ABSTRACT FROM AUTHOR]

A multilevel-multiphase topology based on modified Cuk converter is proposed in this paper. This paper employs the combination of multiphase and multilevel topology which is applied to the modified dc-dc the Cuk converter serves as the fundamental cell topology to achieve low-ripple high-ratio DC-DC converter. The multiphase approach will generate smaller current ripples in the input and output sides so it will be beneficial for ripple-prone sources or load, for example photovoltaic panel or battery. Meanwhile, the multilevel approach will generate high ratio amplification for input voltage, provided by PV panel or battery, to reach typical 380-400VDC in the output voltage which is suitable for DC microgrid applications. A four levels multilevel-multiphase modified Cuk converter topology is successfully developed. The derivation of the mathematical expression of the voltages applicable to the proposed converter is conducted. Loss analysis is conducted to observe the contributing factor of losses to the total efficiency is conducted. A double-loop control system is proposed for the proposed converter to achieve the desired reference operation point for various conditions. It can be demonstrated that the proposed converter generates high ratio total output voltage while maintaining notably small current ripple. Simulation and experiment are conducted to verify the performance of the proposed converter. [ABSTRACT FROM AUTHOR]

A thermally coupled distillation technology can bring energy‐saving benefits, but it poses challenges to process control. This article explores dynamic control of different side‐stream quaternary extractive distillation configurations. One the one hand, the open‐loop controllability of these processes is analyzed in terms of various criteria by the control design interface technology of Aspen Plus Dynamics. On the other hand, their control structures are established and examined by introducing large feed flow and composition perturbations. The results show that the triple‐side‐stream distillation still performs the best state and input–output controllability in spite of the strongest nonlinearity, and is also well resistant to large feed perturbations using a simple control structure. [ABSTRACT FROM AUTHOR]

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Abstract Movement is a central behavior of daily living; thus lost or compromised movement due to disease, injury, or amputation causes enormous loss of productivity and quality of life. While prosthetics have evolved enormously over the years, restoring natural sensorimotor (SM) control via a prosthesis is a difficult problem which neuroengineering has yet to solve. With a focus on upper limb prosthetics, this perspective article discusses the neurophysiology of motor control under healthy conditions and after amputation, the development of upper limb prostheses from early generations to current state-of-the art sensorimotor neuroprostheses, and how postinjury changes could complicate prosthetic control. Current challenges and future development of smart sensorimotor neuroprostheses are also discussed.

Abstract Over the past decade, phase-targeted auditory stimulation (PTAS), a neuromodulation approach which presents auditory stimuli locked to the ongoing phase of slow waves during sleep, has shown potential to enhance specific aspects of sleep functions. However, the complexity of PTAS responses complicates the establishment of causality between specific electroencephalographic events and observed benefits. Here, we used down-PTAS during sleep to specifically evoke the early, K-complex (KC)-like response following PTAS without leading to a sustained increase in slow-wave activity throughout the stimulation window. Over the course of two nights, one with down-PTAS, the other without, high-density electroencephalography (hd-EEG) was recorded from 14 young healthy adults. The early response exhibited striking similarities to evoked KCs and was associated with improved verbal memory consolidation via stimulus-evoked spindle events nested into the up-phase of ongoing 1 Hz waves in a central region. These findings suggest that the early, KC-like response is sufficient to boost memory, potentially by orchestrating aspects of the hippocampal-neocortical dialogue.

Background: Prior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8–14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS has not been feasible so far due to stimulation artifacts preventing continuous phase tracking. Objectives and hypothesis: We aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag. Methods: We developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead. Results: WM accuracy improved in a phase lag dependent manner (p = 0.0350) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330° phase lag between tACS and ongoing alpha oscillations (p = 0.00273, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p = 0.0248) and phase (p = 0.0270) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation. Conclusions: Our results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications.

Several closed or hybrid loop controllers for Blood Glucose (BG) regulation, which are also known as Artificial Pancreas (AP) Systems or Automated Insulin Delivery systems (AIDs), are in development worldwide. Most AIDs are designed and evaluated for short-term performance, with a particular emphasis on the post-meal period. However, if controllers are not adapted properly to account for variations in physiology that affect Insulin Sensitivity (IS), the AIDs may perform inadequately. In this work, the performance of two Reinforcement Learning (RL) agents trained under both piecewise and continuous reward functions is evaluated in-silico for long-term adaptation of a Fully Automated Insulin Delivery (fAID) system. An automatic adaptive discretization scheme that expands the state space as needed is also implemented to avoid disproportionate state space exploration. The proposed agents are evaluated for long-term adaptation of the Automatic Regulation of Glucose (ARG) algorithm, considering variations in IS. Results show that both RL agents have improved performance compared to a rule-based decision-making approach and the baseline controller for the majority of the adult population. Moreover, the use of a continuous shaped reward function proves to enhance the performance of the agents further than a piecewise one. [ABSTRACT FROM AUTHOR]

Background: Gamification of behavioral intervention for tic disorders (TDs) potentially enhances compliance and offers key clinical advantages. By delivering immediate positive feedback upon tic‐suppression, games may counteract negative reinforcement, which presumably contribute to tic consolidation by relieving uncomfortable premonitory urges. Objectives: We developed a gamified protocol (XTics), which leverages this potential by combining gamified tic‐triggering with immediate feedback, and evaluated its clinical value in enhancing tic suppression. Methods: XTics encompasses two conditions: Immediate and Contingent Reward (ICR), where game progression is contingent upon successful tic suppression, and Delayed Reward (DR), where game events' outcomes are random. Employing a randomized crossover design, 35 participants (aged 7–15 years) underwent daily gaming sessions over a week per condition. Improvements in our primary measures, including the inter‐tic interval (ITI) and tic severity assessment by blinded evaluators (Yale Global Tic Severity‐Total Tic Score [YGTSS‐TTS], Rush), and parents (Parent Tic Questionnaire [PTQ]), were compared between ICR and DR, and assessed across conditions for the 4‐week protocol. Results: No participant voluntarily left the study before completing its two‐phase protocol. As expected, ITI showed significantly larger improvement (Z = 4.19, P = 2.85 × 10–5) after ICR (1442 ± 2250%) versus DR (242 ± 493%) training, increasing at a higher pace (t(67) = 3.15, P = 0.0025). Similarly, Rush tic severity scores reduced more post‐ICR versus DR (t(47) = 3.47, P = 0.002). We observed a clinically significant reduction of 25.69 ± 23.39% in YGTSS‐TTS following a f4‐week protocol including both conditions. Parent‐reported tic severity decreased by 42.99 ± 31.69% from baseline to 3 months post‐treatment. Conclusions: The combination of gamified tic‐triggering with immediate and contingent rewards demonstrates a promising approach for enhancing treatment efficacy in TDs, boosting traditional therapeutic methods. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Multi-loop coupling mechanisms (MCMs) have been widely used in architectural design antennas and space-deployable. This paper proposes a general method for actuation selection of MCMs using geometric algebra. The constraint space is obtained by collineation and dual operators of twist space. This method determines additional constraints by analyzing the linear correlation between the constrained spaces of the two limbs within the closed-loop and making corrections to the constraint space of the basic limb. Through outer and dual operators, the input screw corresponding to the transmission wrench screw and output twist screw are obtained. The input transmission index (ITI) and output transmission index (OTI) corresponding to this input are calculated, which leads to generation of a local transmission index (LTI). The actuation selection with the best performance can be obtained by comparing and analyzing the motion/force transfer performance of all input combinations. The proposed method has the advantages of simple computation and clear physical significance, and three typical MCMs are applied to validate this method. Finally, an experimental analysis compared the power consumption of a test motor at different actuation positions, further proving the accuracy of the method. [ABSTRACT FROM AUTHOR]

Background: One single-center randomized clinical trial showed that INTELLiVENT-adaptive support ventilation (ASV) is superior to conventional ventilation with respect to the quality of ventilation in post-cardiac surgery patients. Other studies showed that this automated ventilation mode reduces the number of manual interventions at the ventilator in various types of critically ill patients. In this multicenter study in patients post-cardiac surgery, we test the hypothesis that INTELLiVENT-ASV is superior to conventional ventilation with respect to the quality of ventilation. Methods: "POStoperative INTELLiVENT-adaptive support VEntilation in cardiac surgery patients II (POSITiVE II)" is an international, multicenter, two-group randomized clinical superiority trial. In total, 328 cardiac surgery patients will be randomized. Investigators screen patients aged > 18 years of age, scheduled for elective cardiac surgery, and expected to receive postoperative ventilation in the ICU for longer than 2 h. Patients either receive automated ventilation by means of INTELLiVENT-ASV or ventilation that is not automated by means of a conventional ventilation mode. The primary endpoint is quality of ventilation, defined as the proportion of postoperative ventilation time characterized by exposure to predefined optimal, acceptable, and critical (injurious) ventilatory parameters in the first two postoperative hours. One major secondary endpoint is ICU team staff workload, captured by the ventilator software collecting manual settings on alarms. Patient-centered endpoints include duration of postoperative ventilation and length of stay in ICU. Discussion: POSITiVE II is the first international, multicenter, randomized clinical trial designed to confirm that POStoperative INTELLiVENT-ASV is superior to non-automated conventional ventilation and secondary to determine if this closed-loop ventilation mode reduces ICU team staff workload. The results of POSITiVE II will support intensive care teams in their choices regarding the use of automated ventilation in postoperative care of uncomplicated cardiac surgery patients. Trial registration: Clinicaltrials.gov NCT06178510. Registered on December 4, 2023. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To establish the closed-loop management mode of rational drug use in the hospital based on the level-six standard of electronic medical record system, so as to escort the rational drug use of outpatients and provide reference for the construction of intelligent pharmacy. METHODS: Artificial intelligence technology was used to manage all aspects of rational drug use in outpatient department, such as physician prescription, pharmacist review, drug dispensing and prescription review, the closed-loop system was established in line with the level-six standard of electronic medical record system. Meanwhile, the irrational rate of outpatient prescriptions before closed-loop management (from Mar. to May 2023) and after closed-loop management ( from Jun. to Aug. 2023) were analyzed retrospectively. RESULTS: After implementation of the closed-loop management mode of rational drug use in outpatient department, the irrational rate of outpatient prescriptions was 3. 56% (40 723 / 1 145 056), which was 1. 01% lower than 4. 57% (52 681 / 1 153 154) before management, the difference was statistically significant (P < 0. 01). The number of prescriptions for other types of inappropriate drugs except for the selection of unsuitable drugs decreased significantly. The average drug cost per outpatient visit was 146. 20 RMB, with a reduction of 7. 67% compared with before management cost of 158. 35 RMB, effectively improving the performance assessment indicators of public hospitals. CONCLUSIONS: The closed-loop management mode of rational drug use in outpatients established by the hospital meets the requirements of the level-six standard of electronic medical record system, which can standardize the work flow of medical personnel and reduce irrational drug use in outpatient department. [ABSTRACT FROM AUTHOR]

Prior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8–14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS has not been feasible so far due to stimulation artifacts preventing continuous phase tracking. We aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag. We developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead. WM accuracy improved in a phase lag dependent manner (p = 0.0350) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330° phase lag between tACS and ongoing alpha oscillations (p = 0.00273, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p = 0.0248) and phase (p = 0.0270) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation. Our results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications. • TACS is phase-tuned to alpha oscillations in real-time during stimulation. • TACS enhances working memory performance. • Working memory effects are associated with frontoparietal alpha synchrony. • No phase-dependent modulation in active control condition. [ABSTRACT FROM AUTHOR]

Background: Transcutaneous auricular vagus nerve stimulation (taVNS) has garnered attention for stroke rehabilitation, with studies demonstrating its benefits when combined with motor rehabilitative training or delivered before motor training. The necessity of concurrently applying taVNS with motor training for post-stroke motor rehabilitation remains unclear. We aimed to investigate the necessity and advantages of applying the taVNS concurrently with motor training by an electromyography (EMG)-triggered closed-loop system for poststroke rehabilitation. Methods: We propose a double-blinded, randomized clinical trial involving 150 stroke patients assigned to one of three groups: concurrent taVNS, sequential taVNS, or sham control condition. In the concurrent group, taVNS bursts will synchronize with upper extremity motor movements with EMG-triggered closed-loop system during the rehabilitative training, while in the sequential group, a taVNS session will precede the motor rehabilitative training. TaVNS intensity will be set below the pain threshold for both concurrent and sequential conditions and at zero for the control condition. The primary outcome measure is the Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Secondary measures include standard upper limb function assessments, as well as EMG and electrocardiogram (ECG) features. Ethics and dissemination: Ethical approval has been granted by the Medical Ethics Committee, affiliated with Zhujiang Hospital of Southern Medical University for Clinical Studies (2023-QX-012-01). This study has been registered on ClinicalTrials (NCT05943431). Signed informed consent will be obtained from all included participants. The findings will be published in peer-reviewed journals and presented at relevant stakeholder conferences and meetings. Discussion: This study represents a pioneering effort in directly comparing the impact of concurrent taVNS with motor training to that of sequential taVNS with motor training on stroke rehabilitation. Secondly, the incorporation of an EMG-triggered closed-loop taVNS system has enabled the automation and individualization of both taVNS and diverse motor training tasks--a novel approach not explored in previous research. This technological advancement holds promise for delivering more precise and tailored training interventions for stroke patients. However, it is essential to acknowledge a limitation of this study, as it does not delve into examining the neural mechanisms underlying taVNS in the context of post-stroke rehabilitation. [ABSTRACT FROM AUTHOR]

Capacity Development of Closed-Loop Food (Rice) Farmers in East Nusa Tenggara is a training that is carried out to increase the understanding of prospective farmers who implement the food closed-loop system (rice) in Nagekeo East Nusa Tenggara regarding the bookkeeping, access to financing and marketing. The training was held in Mbay, Nagekeo Regency. Participants are 14 partner farmers of Pandawa Agri Indonesia (PAI) who are currently or have implemented PAI Innovation. Activities are implemented in several stages from coordination, training, FGD, pre-test and post-test. Primary and secondary data were obtained and analyzed descriptively, quantitatively and qualitatively. There was an increase in farmers' knowledge about farming bookkeeping, access to financing and marketing strategies. Farmers are made aware of the importance of carrying out business bookkeeping and the essential steps for taking advantage of various agricultural financing schemes. Farmers also realized the importance of institutions, and together, the group determines targets, segments and current market positions for better marketing strategy design. [ABSTRACT FROM AUTHOR]

[Article in Italian] Impianti geotermici a bassa entalpia a circuito chiuso per il geoscambio nel sottosuolo: registri pubblici, dati disponibili, implicazioni per la programmazione

BackgroundThe aim of this study is the evaluation of a closed-loop oxygen control system in pediatric patients undergoing invasive mechanical ventilation (IMV).MethodsCross-over, multicenter, randomized, single-blind clinical trial. Patients between the ages of 1 month and 18 years who were undergoing IMV therapy for acute hypoxemic respiratory failure (AHRF) were assigned at random to either begin with a 2-hour period of closed-loop oxygen control or manual oxygen titrations. By using closed-loop oxygen control, the patients' SpO2 levels were maintained within a predetermined target range by the automated adjustment of the FiO2. During the manual oxygen titration phase of the trial, healthcare professionals at the bedside made manual changes to the FiO2, while maintaining the same target range for SpO2. Following either period, the patient transitioned to the alternative therapy. The outcomes were the percentage of time spent in predefined SpO2 ranges ±2% (primary), FiO2, total oxygen use, and the number of manual adjustments.FindingsThe median age of included 33 patients was 17 (13–55.5) months. In contrast to manual oxygen titrations, patients spent a greater proportion of time within a predefined optimal SpO2 range when the closed-loop oxygen controller was enabled (95.7% [IQR 92.1–100%] vs. 65.6% [IQR 41.6–82.5%]), mean difference 33.4% [95%–CI 24.5–42%]; P < 0.001). Median FiO2 was lower (32.1% [IQR 23.9–54.1%] vs. 40.6% [IQR 31.1–62.8%]; P < 0.001) similar to total oxygen use (19.8 L/h [IQR 4.6–64.8] vs. 39.4 L/h [IQR 16.8–79]; P < 0.001); however, median SpO2/FiO2 was higher (329.4 [IQR 180–411.1] vs. 246.7 [IQR 151.1–320.5]; P < 0.001) with closed–loop oxygen control. With closed–loop oxygen control, the median number of manual adjustments reduced (0.0 [IQR 0.0–0.0] vs. 1 [IQR 0.0–2.2]; P < 0.001).ConclusionClosed-loop oxygen control enhances oxygen therapy in pediatric patients undergoing IMV for AHRF, potentially leading to more efficient utilization of oxygen. This technology also decreases the necessity for manual adjustments, which could reduce the workloads of healthcare providers.Clinical Trial RegistrationThis research has been submitted to ClinicalTrials.gov (NCT05714527).

Abstract We tested the ability of a physiologically driven minimally invasive closed-loop algorithm, called Resuscitation based on Functional Hemodynamic Monitoring (ReFit), to stabilize for up to 3 h a porcine model of noncompressible hemorrhage induced by severe liver injury and do so during both ground and air transport. Twelve animals were resuscitated using ReFit to drive fluid and vasopressor infusion to a mean arterial pressure (MAP) > 60 mmHg and heart rate

AbstractThis paper investigates the practicality of upholding supply chains’ resilience and sustainability using six aspects of closed-loop supply chain models considering circular economy (CLSMs). A plant-level survey was utilised to test the influence of CLSMs on resilience sustainability. A proposed research model and hypotheses are tested using cross-sectional face-to-face and e-mail survey data collected from manufacturing firms in Kenya. Structural equation modelling is used to test the proposed hypotheses. Cleaner production exhibits more influence on resilient sustainability on both economic and social sustainability, where the Japanese 5S approach is the most prevalent in cleaner production. Green procurement combined with design for the environment shows a positive effect on environmental sustainability, and reverse logistics shows a positive effect on resilience, unfolding the importance of devising CLSMs strategies for building both resilience and sustainability. Surprisingly, green logistics did not affect any of the resilient sustainability dimensions and reverse logistics on sustainability. These results reveal the practicality of upholding supply chains’ resilience and sustainability through CLSMs. While few studies test the direct link between CLSMs and resilient sustainability, this study is significant in the upstarting of such investigations, more so from an empirical perspective. This study contributes to extant literature, practice, and policy by showing the importance of building both resilience and sustainability of supply chains using CLSMs and adopting trade-offs as starting points as economies walk towards points of balance. From a policy perspective, this study points out the need for stringent CLSMs policy measures towards resilience and sustainability, more so in Sub-Saharan African manufacturing contexts.

BACKGROUND: Spinal cord stimulation (SCS) is an established chronic pain treatment, but the effectiveness of traditional, open-loop paradigms has been plagued by variable sustainability in a real-world setting. A new approach, utilizing evoked compound action potential (ECAP) controlled closed-loop (CL) SCS, continuously monitors spinal cord activation and automatically adjusts the stimulation amplitude of every pulse, maintaining stimulation at the prescribed ECAP level through this continual feedback mechanism. Recent studies demonstrated the long-term safety and efficacy of ECAP-controlled CL-SCS. Here, we report the design of a prospective, multicenter, single-arm feasibility study to characterize clinical outcomes in a real-world chronic pain population utilizing ECAP-controlled CL-SCS. Objective neurophysiological measurements such as device performance and patient therapy compliance, will be analyzed against baseline biopsychosocial assessments, to explore the clinical utility of these objective physiologic biomarkers in patient phenotyping. METHODS: This study will enroll up to 300 subjects with chronic, intractable trunk and/or limb pain in up to 25 United States investigation sites. Subjects meeting eligibility criteria will undergo a trial procedure and a permanent implant following a successful trial. Neurophysiological measurements (measured in-clinic and continuously during home use) and clinical outcomes including pain, quality-of-life, psychological, emotional, and functional assessments will be collected at baseline, trial end, and up to 24-months post-implantation. DISCUSSION: Associations between objective neurophysiological data, clinical evaluation and patient-reported outcomes may have important clinical and scientific implications. They may provide novel insights about the chronic pain pathophysiology, its modulation during CL-SCS, and identification of pain phenotypes and/or mechanisms associated with treatment response during SCS trials and long-term therapy. Data from the ECAP study could lead to improvements in diagnosis, assessment, patient identification and management of chronic pain. It could also provide the foundation for development of a new SCS treatment approach customized by the patients pain phenotype, unique neurophysiology, and disease severity.

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of

We tested the ability of a physiologically driven minimally invasive closed-loop algorithm, called Resuscitation based on Functional Hemodynamic Monitoring (ReFit), to stabilize for up to 3 h a porcine model of noncompressible hemorrhage induced by severe liver injury and do so during both ground and air transport. Twelve animals were resuscitated using ReFit to drive fluid and vasopressor infusion to a mean arterial pressure (MAP) > 60 mmHg and heart rate < 110 min−1 30 min after MAP < 40 mmHg following liver injury. ReFit was initially validated in 8 animals in the laboratory, then in 4 animals during air (23nm and 35nm) and ground (9 mi) to air (9.5nm and 83m) transport returning to the laboratory. The ReFit algorithm kept all animals stable for ~ 3 h. Thus, ReFit algorithm can diagnose and treat ongoing hemorrhagic shock independent to the site of care or during transport. These results have implications for treatment of critically ill patients in remote, austere and contested environments and during transport to a higher level of care. [ABSTRACT FROM AUTHOR]

Flexible high-density microelectrode arrays (HDMEAs) are emerging as a key component in closed-loop brain-machine interfaces (BMIs), providing highresolution functionality for recording, stimulation, or both. The flexibility of these arrays provides advantages over rigid ones, such as reduced mismatch between interface and tissue, resilience to micromotion, and sustained longterm performance. This review summarizes the recent developments and applications of flexible HDMEAs in closed-loop BMI systems. It delves into the various challenges encountered in the development of ideal flexible HDMEAs for closed-loop BMI systems and highlights the latest methodologies and breakthroughs to address these challenges. These insights could be instrumental in guiding the creation of future generations of flexible HDMEAs, specifically tailored for use in closed-loop BMIs. The review thoroughly explores both the current state and prospects of these advanced arrays, emphasizing their potential in enhancing BMI technology. [ABSTRACT FROM AUTHOR]

A customized atmospheric‐pressure spatial atomic layer deposition (AP‐SALD) system is designed and implemented, which enables mechatronic control of key process parameters, including gap size and parallel alignment. A showerhead depositor delivers precursors to the substrate while linear actuators and capacitance probe sensors actively maintain gap size and parallel alignment through multiple‐axis tilt and closed‐loop feedback control. Digital control of geometric process variables with active monitoring is facilitated with a custom software control package and user interface. AP‐SALD of TiO2 is performed to validate self‐limiting deposition with the system. A novel multi‐axis printing methodology is introduced using x‐y position control to define a customized motion path, which enables an improvement in the thickness uniformity by reducing variations from 8% to 2%. In the future, this mechatronic system will enable experimental tuning of parameters that can inform multi‐physics modeling to gain a deeper understanding of AP‐SALD process tolerances, enabling new pathways for non‐traditional SALD processing that can push the technology towards large‐scale manufacturing. [ABSTRACT FROM AUTHOR]

This single blinded randomized controlled trial aims to assess whether the application of a Bayesian-adjusted CePROP (effect-site of propofol) advisory tool leads towards a more stringent control of the cerebral drug effect during anaesthesia, using qCON as control variable. 100 patients scheduled for elective surgery were included and randomized into a control or intervention group (1:1 ratio). In the intervention group the advisory screen was made available to the clinician, whereas it was blinded in the control group. The settings of the target-controlled infusion pumps could be adjusted at any time by the clinician. Cerebral drug effect was quantified using processed EEG (CONOX monitor, Fresenius Kabi, Bad Homburg, Germany). The time of qCON between the desired range (35–55) during anaesthesia maintenance was defined as our primary end point. Induction parameters and recovery times were considered secondary end points and coefficient of variance of qCON and CePROP was calculated in order to survey the extent of control towards the mean of the population. The desired range of qCON between 35 and 55 was maintained in 84% vs. 90% (p = 0.15) of the case time in the control versus intervention group, respectively. Secondary endpoints showed similar results in both groups. The coefficient of variation for CePROP was higher in the intervention group. The application of the Bayesian-based CePROP advisory system in this trial did not result in a different time of qCON between 35 and 55 (84 [21] vs. 90 [18] percent of the case time). Significant differences between groups were hard to establish, most likely due to a very high performance level in the control group. More extensive control efforts were found in the intervention group. We believe that this advisory tool could be a useful educational tool for novices to titrate propofol effect-site concentrations. [ABSTRACT FROM AUTHOR]

Implantable neuromodulation devices have significantly advanced treatments for neurological disorders such as Parkinson's disease, epilepsy, and depression. Traditional open-loop devices like deep brain stimulation (DBS) and spinal cord stimulators (SCS) often lead to overstimulation and lack adaptive precision, raising safety and side-effect concerns. Next-generation closed-loop systems offer real-time monitoring and on-device diagnostics for responsive stimulation, presenting a significant advancement for treating a range of brain diseases. However, the high false alarm rates of current closed-loop technologies limit their efficacy and increase energy consumption due to unnecessary stimulations. In this study, we introduce an artificial intelligence-integrated circuit co-design that targets these issues and using an online demonstration system for closedloop seizure prediction to showcase its effectiveness. Firstly, two neural network models are obtained with neural-network search and quantization strategies. A binary neural network is optimized for minimal computation with high sensitivity and a convolutional neural network with a false alarm rate as low as 0.1/h for false alarm rejection. Then, a dedicated low-power processor is fabricated in 55 nm technology to implement the two models. With reconfigurable design and event-driven processing feature the resulting application-specific integrated circuit (ASIC) occupies only 5mm2 silicon area and the average power consumption is 142 µW. The proposed solution achieves a significant reduction in both false alarm rates and power consumption when benchmarked against state-of-the-art counterparts. [ABSTRACT FROM AUTHOR]

The concept of maintaining blood glucose levels within the 70–180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70–140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this study was to assess the efficacy and safety of hybrid closed-loop (HCL) systems for insulin delivery in children and adolescents with type 1 diabetes (T1D). We searched Embase, PubMed, and Cochrane Library for randomized controlled trials (RCTs) published until March 2023 comparing the HCL therapy with control therapies for children and adolescents with T1D. We computed weighted mean differences (WMDs) for continuous outcomes and risk ratios (RRs) with 95% confidence intervals (CIs) for binary endpoints. Four RCTs and 501 patients were included, of whom 323 were randomized to HCL therapy. Compared with control therapies, HCL significantly improved the period during which glucose level was 70-180 mg/dL (WMD 10.89%, 95% CI 8.22-13.56%) and the number of participants with glycated hemoglobin (HbA1c) level < 7% (RR 2.61, 95% CI 1.29-5.28). Also, HCL significantly reduced the time during which glucose level was > 180 mg/dL (WMD -10.46%, 95% CI -13.99 to -6.93%) and the mean levels of glucose (WMD -16.67 mg/dL, 95% CI -22.25 to -11.09 mg/dL) and HbA1c (WMD -0.50%, 95% CI -0.68 to -0.31). There were no significant differences between therapies regarding time during which glucose level was < 70 mg/dL or

Abstract Türkiye relies on coal-fired power plants for approximately 18 GW of annual electricity generation, with significantly higher CO2 emissions compared to geothermal power plants. On the other hand, geothermal energy resources, such as Enhanced Geothermal Systems (EGS) and hydrothermal systems, offer low CO2 emissions and baseload power, making them attractive clean energy sources. Radiogenic granitoid, with high heat generation capacity, is a potential and cleaner energy source using EGS. The Anatolian plateau hosts numerous tectonic zones with plutonic rocks containing high concentrations of radioactive elements, such as the Central Anatolian Massif. This study evaluates the power generation capacity of the Hamit granitoid (HG) and presents a thermo-hydraulic-mechanical (THM) model for a closed-loop geothermal well for harnessing heat from this granitoid. A sensitivity analysis based on fluid injection rates and wellbore length emphasizes the importance of fluid resident time for effective heat extraction. Closed-loop systems pose fewer geomechanical risks than fractured systems and can be developed through site selection, system design, and monitoring. Geothermal wellbore casing material must withstand high temperatures, corrosive environments, and should have low thermal conductivity. The HG exhibits the highest heat generation capacity among Anatolian granitoid intrusions and offers potential for sustainable energy development through EGS, thereby reducing CO2 emissions.

Discriminating recorded afferent neural information can provide sensory feedback for closed-loop control of functional electrical stimulation, which restores movement to paralyzed limbs. Previous work achieved state-of-the-art off-line classification of electrical activity in different neural pathways recorded by a multi-contact nerve cuff electrode, by applying deep learning to spatiotemporal neural patterns. The objective of this study was to demonstrate the feasibility of this approach in the context of closed-loop stimulation. Acute in vivo experiments were conducted on 11 Long Evans rats to demonstrate closed-loop stimulation. A 64-channel ( $8\times8$ ) nerve cuff electrode was implanted on each rat’s sciatic nerve for recording and stimulation. A convolutional neural network (CNN) was trained with spatiotemporal signal recordings associated with 3 different states of the hindpaw (dorsiflexion, plantarflexion, and pricking of the heel). After training, firing rates were reconstructed from the classifier outputs for each of the three target classes. A rule-based closed-loop controller was implemented to produce ankle movement trajectories using neural stimulation, based on the classified nerve recordings. Closed-loop stimulation was successfully demonstrated in 6 subjects. The number of successful movement sequence trials per subject ranged from 1–17 and number of correct state transitions per trial ranged from 3-53. This work demonstrates that a CNN applied to multi-contact nerve cuff recordings can be used for closed-loop control of functional electrical stimulation.

Abstract Background Preclinical models of spinal cord stimulation (SCS) are lacking objective measurements to inform translationally applicable SCS parameters. The evoked compound action potential (ECAP) represents a measure of dorsal column fiber activation. This measure approximates the onset of SCS-induced sensations in humans and provides effective analgesia when used with ECAP-controlled closed-loop (CL)-SCS systems. Therefore, ECAPs may provide an objective surrogate for SCS dose in preclinical models that may support better understanding of SCS mechanisms and further translations to the clinics. This study assessed, for the first time, the feasibility of recording ECAPs and applying ECAP-controlled CL-SCS in freely behaving rats subjected to an experimental model of neuropathic pain. Methods Adult male Sprague–Dawley rats (200–300 g) were subjected to spared nerve injury (SNI). A custom-made six-contact lead was implanted epidurally covering T11-L3, as confirmed by computed tomography or X-ray. A specially designed multi-channel system was used to record ECAPs and to apply ECAP-controlled CL-SCS for 30 min at 50 Hz 200 µs. The responses of dorsal column fibers to SCS were characterized and sensitivity towards mechanical and cold stimuli were assessed to determine analgesic effects from ECAP-controlled CL-SCS. Comparisons between SNI rats and their controls as well as between stimulation parameters were made using omnibus analysis of variance (ANOVA) tests and t-tests. Results The recorded ECAPs showed the characteristic triphasic morphology and the ECAP amplitude (mV) increased as higher currents (mA) were applied in both SNI animals and controls (SNI SCS-ON and sham SCS-ON). Importantly, the use of ECAP-based SCS dose, implemented in ECAP-controlled CL-SCS, significantly reduced mechanical and cold hypersensitivity in SNI SCS-ON animals through the constant and controlled activation of dorsal column fibers. An analysis of conduction velocities of the evoked signals confirmed the involvement of large, myelinated fibers. Conclusions The use of ECAP-based SCS dose implemented in ECAP-controlled CL-SCS produced analgesia in animals subjected to an experimental model of neuropathic pain. This approach may offer a better method for translating SCS parameters between species that will improve understanding of the mechanisms of SCS action to further advance future clinical applications.

Mesial temporal lobe epilepsy (MTLE), the most common form of focal epilepsy in adults, is often refractory to medication and associated with hippocampal sclerosis. Deep brain stimulation represents an alternative treatment option for drug-resistant patients who are ineligible for resective brain surgery. In clinical practice, closed-loop stimulation at high frequencies is applied to interrupt ongoing seizures, yet has (i) a high incidence of false detections; (ii) the drawback of delayed seizure-suppressive intervention; and (iii) limited success in sclerotic tissue. As an alternative, low-frequency stimulation (LFS) has been explored recently in patients with focal epilepsies. In preclinical epilepsy models, hippocampal LFS successfully prevented seizures when applied continuously. Since it would be advantageous to reduce the stimulation load, we developed a protocol for on-demand LFS. Given the importance of the hippocampus for navigation and memory, we investigated potential consequences of LFS on hippocampal function. To this end, we used the intrahippocampal kainate mouse model, which recapitulates the key features of MTLE, including spontaneous seizure activity and hippocampal sclerosis. Specifically, our online detection algorithm monitored epileptiform activity in hippocampal local field potential recordings and identified short epileptiform bursts preceding focal seizure clusters, triggering hippocampal LFS to stabilize the network state. To probe behavioural performance, we tested the acute influence of LFS on anxiety-like behaviour in the light-dark box test, spatial and non-spatial memory in the object location memory and novel object recognition test, as well as spatial navigation and long-term memory in the Barnes maze. On-demand LFS was almost as effective as continuous LFS in preventing focal seizure clusters but with a significantly lower stimulation load. When we compared the behavioural performance of chronically epileptic mice to healthy controls, we found that both groups were equally mobile, but epileptic mice displayed an increased anxiety level, altered spatial learning strategy and impaired memory performance. Most importantly, with the application of hippocampal LFS before behavioural training and test sessions, we could rule out deleterious effects on cognition and even show an alleviation of deficits in long-term memory recall in chronically epileptic mice. Taken together, our findings may provide a promising alternative to current therapies, overcoming some of their major limitations, and inspire further investigation of LFS for seizure control in focal epilepsy syndromes. [ABSTRACT FROM AUTHOR]

Several strategies for navigation in unfamiliar environments have been explored, notably leveraging advanced sensors and control algorithms for obstacle recognition in autonomous vehicles. This study introduces a novel approach featuring a redesigned joystick equipped with stepper motors and linear drives, facilitating WiFi communication with a four-wheel omnidirectional electric vehicle. The system's drive units integrated into the joystick and the encompassing control algorithms are thoroughly examined, including analysis of stick deflection measurement and inter-component communication within the joystick assembly. Unlike conventional setups in which the joystick is tilted by the operator, two independent linear drives are employed to generate ample tensile force, effectively "overpowering" the operator's input. Running on a Raspberry Pi, the software utilizes Python programming to enable joystick tilt control and to transmit orientation and axis deflection data to an Arduino unit. A fundamental haptic effect is achieved by elevating the minimum pressure required to deflect the joystick rod. Test measurements encompass detection of obstacles along the primary directions perpendicular to the electric vehicle's trajectory, determination of the maximum achievable speed, and evaluation of the joystick's maximum operational range within an illuminated environment. [ABSTRACT FROM AUTHOR]

More recently, soft actuators have evoked great interest in the next generation of soft robots. Despite significant progress, the majority of current soft actuators suffer from the lack of real‐time sensory feedback and self‐control functions, prohibiting their effective sensing and multitasking functions. Therefore, in this work, a near‐infrared‐driven bimorph membrane, with self‐sensing and feedback loop control functions, is produced by layer by layer (LBL) assembling MXene/PDDA (PM) onto liquid crystal elastomer (LCE) film. The versatile integration strategy successfully prevents the separation issues that arise from moduli mismatch between the sensing and the actuating layers, ultimately resulting in a stable and tightly bonded interface adhesion. As a result, the resultant membrane exhibited excellent mechanical toughness (tensile strengths equal to 16.3 MPa (||)), strong actuation properties (actuation stress equal to 1.56 MPa), and stable self‐sensing (gauge factor equal to 4.72) capabilities. When applying the near‐infrared (NIR) laser control, the system can perform grasping, traction, and crawling movements. Furthermore, the wing actuation and the closed‐loop controlled motion are demonstrated in combination with the insect microcontroller unit (MCU) models. The remote precision control and the self‐sensing capabilities of the soft actuator pave a way for complex and precise task modulation in the future. [ABSTRACT FROM AUTHOR]