Improvements in Therapy Experience with Evoked Compound Action Potential Controlled, Closed-Loop Spinal Cord Stimulation - Primary Outcome of the ECHO-MAC Randomized Clinical Trial.

Spinal cord stimulation (SCS) is a well-established treatment for chronic neuropathic pain. However, over- or under-delivery of the SCS may occur because the spacing between the stimulating electrodes and the spinal cord is not fixed; spacing changes with motion and postural shifts may result in variable delivery of the SCS dose, and in turn a sub-optimal therapy experience for the patient. The evoked compound action potential (ECAP)-a measure of neural activation - may be used as a control signal to adapt SCS parameters in real-time to compensate for this variability. In this prospective, multicenter, randomized, single-blind, crossover trial, reduction in overstimulation intensity was used as a perceptual measure to evaluate a novel ECAP-controlled, closed-loop (CL) SCS algorithm relative to traditional open-loop (OL) SCS. The primary outcome used a Likert scale to assess sensation during activities of daily living with CL versus OL SCS. Of the 42 subjects in the Intent-to-Treat Analysis set, 97.6% had a reduction in sensation with CL versus OL SCS. The primary objective was met as the lower confidence limit (87.4%) exceeded the performance goal of 50% (p < 0.001). A total of 88.1% (37/42) of subjects preferred CL and 11.9% (5/42) preferred OL SCS. SCS dose consistency during CL SCS was demonstrated by the reduced variability in ECAP amplitude with CL SCS (SD: 8.72 µV) relative to OL SCS (SD: 19.95 µV). Together, these results demonstrate that the ECAP-controlled, CL algorithm reduces or eliminates unwanted sensation, and thereby provides a more preferred and consistent SCS experience. PERSPECTIVE: Patients with chronic pain need durable and dependable options for pain relief. SCS is an important therapy option, and new technology advancements could improve long-term therapy use. Closed-loop SCS offers a preferred and more consistent therapy experience for patients that could lead to increased therapy utilization and reliable therapy outcomes.

Ageing well with diabetes: the role of technology.

Over the past two decades there has been a substantial rise in the adoption of diabetes therapeutic technology among children, adolescents and younger adults with type 1 diabetes, and its use is now also advocated for older individuals. Older people with diabetes are more prone to experience hypoglycaemia because of numerous predisposing factors and are at higher risk of hypoglycaemic events requiring third-party assistance as well as other adverse sequelae. Hypoglycaemia may also have long-term consequences, including cognitive impairment, frailty and disability. Diabetes in older people is often characterised by marked glucose variability related to age-associated changes such as variable appetite and levels of physical activity, comorbidities and polypharmacotherapy. Preventing hypoglycaemia and mitigating glucose excursions may have considerable positive impacts on physical and cognitive function and general well-being and may even prevent or improve frailty. Technology for older people includes continuous glucose monitoring systems, insulin pumps, automated insulin delivery systems and smart insulin pens. Clinical trials and real-world studies have shown that older people with diabetes benefit from technology in terms of glucose management, reductions in hypoglycaemic events, emergency department attendance and hospital admissions, and improvement in quality of life. However, ageing may bring physical impairments and other challenges that hinder the use of technology. Healthcare professionals should identify older adults with diabetes who may benefit from therapeutic technology and then adopt an individualised approach to education and follow-up for individuals and their caregivers. Future research should explore the impact of diabetes technology on outcomes relevant to older people with diabetes.

Acoustically evoked K-complexes together with sleep spindles boost verbal declarative memory consolidation in healthy adults.

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.

Motion/force coordinated trajectory tracking control of nonholonomic wheeled mobile robot via LMPC-AISMC strategy.

Nonholonomic constrained wheeled mobile robot (WMR) trajectory tracking requires the enhancement of the ground adaptation capability of the WMR while ensuring its attitude tracking accuracy, a novel dual closed-loop control structure is developed to implement this motion/force coordinated control objective in this paper. Firstly, the outer-loop motion controller is presented using Laguerre functions modified model predictive control (LMPC). Optimised solution condition is introduced to reduce the number of LMPC solutions. Secondly, an inner-loop force controller based on adaptive integral sliding mode control (AISMC) is constructed to ensure the desired velocity tracking and output driving torques by combining second-order nonlinear extended state observer (ESO) with the estimation of dynamic uncertainties and external disturbances during WMR travelling process. Then, Lyapunov stability theory is utilised to guarantee the consistent final boundedness of the designed controller. Finally, the system is numerically simulated and practically verified. The results show that the double-closed-loop control strategy devised in this paper has better control performance in terms of complex trajectory tracking accuracy, system resistance to strong interference and computational timeliness, and is able to realise effective coordinated control of WMR motion/force.

Closed-Loop Control of Melt Pool Temperature during Laser Metal Deposition.

Laser metal deposition (LMD) is a technology for the production of near-net-shape components. It is necessary to control the manufacturing process to obtain good geometrical accuracy and metallurgical properties. In the present study, a closed-loop control method of melt pool temperature for the deposition of small Ti6Al4V blocks in open environment was proposed. Based on the developed melt pool temperature sensor and deposition height sensor, a closed-loop control system and proportional-integral (PI) controller were developed and tested. The results show that with a PI temperature controller, the melt pool temperature tends to the desired value and remains stable. Compared to the deposition block without the controller, a flatter surface and no oxidation phenomenon are obtained with the controller.

State Space Representation of Jiles-Atherton Hysteresis Model and Application for Closed-Loop Control.

Hysteresis is a fundamental characteristic of magnetic materials. The Jiles-Atherton (J-A) hysteresis model, which is known for its few parameters and clear physical interpretations, has been widely employed in simulating hysteresis characteristics. To better analyze and compute hysteresis behavior, this study established a state space representation based on the primitive J-A model. First, based on the five fundamental equations of the J-A model, a state space representation was established through variable substitution and simplification. Furthermore, to address the singularity problem at zero crossings, local linearization was obtained through an approximation method based on the actual physical properties. Based on these, the state space model was implemented using the S-function. To validate the effectiveness of the state space model, the hysteresis loops were obtained through COMSOL finite element software and tested on a permalloy toroidal sample. The particle swarm optimization (PSO) method was used for parameter identification of the state space model, and the identification results show excellent agreement with the simulation and test results. Finally, a closed-loop control system was constructed based on the state space model, and trajectory tracking experiments were conducted. The results verify the feasibility of the state space representation of the J-A model, which holds significant practical implications in the development of magnetically shielded rooms, the suppression of magnetic interference in cold atom clocks, and various other applications.

Enhancing supply chain relationships in the circular economy: Strategies for a green centralized supply chain with deteriorating products.

This article introduces a green centralized supply chain in a two-stage stochastic programming model using deteriorating products. The model reduces the cost of purchasing, transporting, storing, product recovery and shortages. This cuts down on greenhouse emission related to transportation, product recovery, and recycling programs. On the basis of this, we explore the utilization of the circular economy to the damages that could occur from used products. Furthermore, revenue sharing and quantity discount contracts are examined in the business models between the members of the supply chain and the external manufacturer. Demand is assumed to be uncertain, and scenarios are created to account this. The model specifies the optimal order quantities, transportation modes and contract terms that minimize costs and environmental impacts. Numerical examples analyze the trade-offs between economic and environmental objectives under different supply chain parameters. The results provide insights for circular supply chains that reconcile economic incentives with environmental responsibility for deteriorating product.

Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept.

Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of metabolic acidosis. Data was collected from ten anesthetized, spontaneously breathing pigs divided randomly into two groups, one without dead space and the other with dead space at the beginning of the experiment. Each group underwent two equal sequences of pH lowering with pre-defined targets by continuous infusion of lactic acid. The inputs to ANNs were pH, ΔPaCO2 (variation of the arterial partial pressure of CO2), PaO2, and blood temperature which were sampled from the animal model. The output was the delta minute volume (ΔVM), (the change of minute volume as compared to the minute volume the animal had at the beginning of the experiment). The ANN performance was analyzed using mean squared error (MSE), linear regression, and the Bland-Altman (B-A) method. The animal experiment provided the necessary data to train the ANN. The best architecture of ANN had 17 intermediate neurons; the best performance of the finally trained ANN had a linear regression with R2 of 0.99, an MSE of 0.001 [L/min], a B-A analysis with bias ± standard deviation of 0.006 ± 0.039 [L/min]. ANNs can accurately estimate ΔVM using the same information that arrives at the respiratory centers. This performance makes them a promising component for the future development of closed-loop artificial ventilators.

Intraoperative Ablation Control Based on Real-Time Necrosis Monitoring Feedback: Numerical Evaluation.

Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.

Phase-Dependent Response to Electrical Stimulation of Cortical Networks during Recurrent Epileptiform Short Discharge Generation In Vitro.

The closed-loop control of pathological brain activity is a challenging task. In this study, we investigated the sensitivity of continuous epileptiform short discharge generation to electrical stimulation applied at different phases between the discharges using an in vitro 4-AP-based model of epilepsy in rat hippocampal slices. As a measure of stimulation effectiveness, we introduced a sensitivity function, which we then measured in experiments and analyzed with different biophysical and abstract mathematical models, namely, (i) the two-order subsystem of our previous Epileptor-2 model, describing short discharge generation governed by synaptic resource dynamics; (ii) a similar model governed by shunting conductance dynamics (Epileptor-2B); (iii) the stochastic leaky integrate-and-fire (LIF)-like model applied for the network; (iv) the LIF model with potassium M-channels (LIF+KM), belonging to Class II of excitability; and (v) the Epileptor-2B model with after-spike depolarization. A semi-analytic method was proposed for calculating the interspike interval (ISI) distribution and the sensitivity function in LIF and LIF+KM models, which provided parametric analysis. Sensitivity was found to increase with phase for all models except the last one. The Epileptor-2B model is favored over other models for subthreshold oscillations in the presence of large noise, based on the comparison of ISI statistics and sensitivity functions with experimental data. This study also emphasizes the stochastic nature of epileptiform discharge generation and the greater effectiveness of closed-loop stimulation in later phases of ISIs.

Sustainable and scalable synthesis of acetal-containing polyols as a platform for circular polyurethanes.

Polyurethanes (PUs) are highly versatile polymers widely utilized across industries. However, chemical recycling of PU possess significant challenges due to the harsh conditions required, and the formation of complex mixtures of oligomers upon depolymerization. Addressing this inherent lack of recyclability, we developed closed-loop recyclable PU materials by integrating cleavable acetal groups. We present a sustainable and scalable synthesis method for acetal-containing polyols (APs) through aldehyde-diol polycondensation, utilizing reusable heterogeneous catalysis. Three APs with different hydrolytic stabilities depending on the structure of acetal groups were synthesized from formaldehyde, acetaldehyde, and propionaldehyde with 1,6-hexanediol (H16). These APs were employed alongside 4,4'-methylene diisocyanate (MDI) for preparation of PU materials. The resulting PUs exhibited mechanical properties comparable to or surpassing those of conventional PUs, while demonstrating excellent recyclability under acidic conditions. Notably, hydrolysis of PU materials based on acetaldehyde-derived APs yielded remarkable monomer recovery rates, with 89% for H16 and 84% for 4,4'-methylenedianiline, a precursor to MDI. Furthermore, we successfully demonstrated closed-loop recycling by synthesizing APs from recovered H16, resulting in PU materials with identical properties to the original PU. This achievement highlights the potential for establishing a closed-loop recycling system for acetal-containing PUs, contributing to the advancement of a sustainable and circular economy.

Context-dependence of deterministic and nondeterministic contributions to closed-loop steering control.

In natural circumstances, sensory systems operate in a closed loop with motor output, whereby actions shape subsequent sensory experiences. A prime example of this is the sensorimotor processing required to align one's direction of travel, or heading, with one's goal, a behavior we refer to as steering. In steering, motor outputs work to eliminate errors between the direction of heading and the goal, modifying subsequent errors in the process. The closed-loop nature of the behavior makes it challenging to determine how deterministic and nondeterministic processes contribute to behavior. We overcome this by applying a nonparametric, linear kernel-based analysis to behavioral data of monkeys steering through a virtual environment in two experimental contexts. In a given context, the results were consistent with previous work that described the transformation as a second-order linear system. Classically, the parameters of such second-order models are associated with physical properties of the limb such as viscosity and stiffness that are commonly assumed to be approximately constant. By contrast, we found that the fit kernels differed strongly across tasks in these and other parameters, suggesting context-dependent changes in neural and biomechanical processes. We additionally fit residuals to a simple noise model and found that the form of the noise was highly conserved across both contexts and animals. Strikingly, the fitted noise also closely matched that found previously in a human steering task. Altogether, this work presents a kernel-based analysis that characterizes the context-dependence of deterministic and non-deterministic components of a closed-loop sensorimotor task.

A compact solution for vibrotactile proprioceptive feedback of wrist rotation and hand aperture.

BACKGROUND: Closing the control loop between users and their prostheses by providing artificial sensory feedback is a fundamental step toward the full restoration of lost sensory-motor functions. METHODS: We propose a novel approach to provide artificial proprioceptive feedback about two degrees of freedom using a single array of 8 vibration motors (compact solution). The performance afforded by the novel method during an online closed-loop control task was compared to that achieved using the conventional approach, in which the same information was conveyed using two arrays of 8 and 4 vibromotors (one array per degree of freedom), respectively. The new method employed Gaussian interpolation to modulate the intensity profile across a single array of vibration motors (compact feedback) to convey wrist rotation and hand aperture by adjusting the mean and standard deviation of the Gaussian, respectively. Ten able-bodied participants and four transradial amputees performed a target achievement control test by utilizing pattern recognition with compact and conventional vibrotactile feedback to control the Hannes prosthetic hand (test conditions). A second group of ten able-bodied participants performed the same experiment in control conditions with visual and auditory feedback as well as no-feedback. RESULTS: Conventional and compact approaches resulted in similar positioning accuracy, time and path efficiency, and total trial time. The comparison with control condition revealed that vibrational feedback was intuitive and useful, but also underlined the power of incidental feedback sources. Notably, amputee participants achieved similar performance to that of able-bodied participants. CONCLUSIONS: The study therefore shows that the novel feedback strategy conveys useful information about prosthesis movements while reducing the number of motors without compromising performance. This is an important step toward the full integration of such an interface into a prosthesis socket for clinical use.

Applying technologies to simplify strategies for exercise in type 1 diabetes.

Challenges and fears related to managing glucose levels around planned and spontaneous exercise affect outcomes and quality of life in people living with type 1 diabetes. Advances in technology, including continuous glucose monitoring, open-loop insulin pump therapy and hybrid closed-loop (HCL) systems for exercise management in type 1 diabetes, address some of these challenges. In this review, three research or clinical experts, each living with type 1 diabetes, leverage published literature and clinical and personal experiences to translate research findings into simplified, patient-centred strategies. With an understanding of limitations in insulin pharmacokinetics, variable intra-individual responses to aerobic and anaerobic exercise, and the features of the technologies, six steps are proposed to guide clinicians in efficiently communicating simplified actions more effectively to individuals with type 1 diabetes. Fundamentally, the six steps centre on two aspects. First, regardless of insulin therapy type, and especially needed for spontaneous exercise, we provide an estimate of glucose disposal into active muscle meant to be consumed as extra carbohydrates for exercise ('ExCarbs'; a common example is 0.5 g/kg body mass per hour for adults and 1.0 g/kg body mass per hour for youth). Second, for planned exercise using open-loop pump therapy or HCL systems, we additionally recommend pre-emptive basal insulin reduction or using HCL exercise modes initiated 90 min (1-2 h) before the start of exercise until the end of exercise. Modifications for aerobic- and anaerobic-type exercise are discussed. The burden of pre-emptive basal insulin reductions and consumption of ExCarbs are the limitations of HCL systems, which may be overcome by future innovations but are unquestionably required for currently available systems.

Systematic review of disparities in continuous glucose monitoring and insulin pump utilization in the United States: Key themes and evidentiary gaps.

AIM: This study aims to provide a comprehensive overview of real-world evidence pertaining to disparities in the utilization of continuous glucose monitors (CGMs)/insulin pumps to highlight potential evidentiary gaps and discern emerging themes from the literature. MATERIALS AND METHODS: A systematic review of published manuscripts and abstracts was conducted from: MEDLINE, EMBASE, Nursing and Allied Health, Web of Science and CINHAL. Attributes related to patients, outcomes, interventions (CGMs/pumps/both) and study type were captured. In addition, factors associated with disparities in device utilization were examined. RESULTS: Thirty-six studies were included in the final analysis; the studies predominantly focused on people living with type 1 diabetes. Only two studies included individuals with type 2 diabetes. Almost two-thirds of the studies reported outcomes associated with disparities (e.g. glycated haemoglobin, diabetic ketoacidosis, resource utilization). Most studies highlighted disparities across race, ethnicity and insurance type. Evidentiary gaps were identified, particularly in the evidence for people with type 2 diabetes, the continuation of CGM/pump use and limited studies addressing disparities among Native Americans/American Indians. CONCLUSION: This study reveals critical disparities in diabetes technology use across race, ethnicity and insurance type, particularly among people with type 1 diabetes. Evidentiary gaps assessing disparities in diabetes technology use persist, particularly concerning people with type 2 diabetes, Native American/American Indian and LGBTQ+ populations, and in outcomes related to continuation of use. Social and digital determinants of health, such as income, transportation, residential location and technological literacy, are crucial to achieving equitable access. Future research should focus on the patient journey to identify opportunities for equitable access to diabetes technology as its use grows.

Real-time closed-loop brainstem stimulation modality for enhancing temporal blood pressure reduction.

BACKGROUND: Traditional pharmacological interventions are well tolerated in the management of elevated blood pressure (BP) for individuals with resistant hypertension. Although neuromodulation has been investigated as an alternative solution, its open-loop (OL) modality cannot follow the patient's physiological state. In fact, neuromodulation for controlling highly fluctuating BP necessitates a closed-loop (CL) stimulation modality based on biomarkers to monitor the patient's continuously varying physiological state. OBJECTIVE: By leveraging its intuitive linkage with BP responses in ongoing efforts aimed at developing a CL system to enhance temporal BP reduction effect, this study proposes a CL neuromodulation modality that controls nucleus tractus solitarius (NTS) activity to effectively reduce BP, thus reflecting continuously varying physiological states. METHOD: While performing neurostimulation targeting the NTS in the rat model, the arterial BP response and neural activity of the NTS were simultaneously measured. To evaluate the temporal BP response effect of CL neurostimulation, OL (constant parameter; 20 Hz, 200 µA) and CL (Initial parameter; 11 Hz, 112 µA) stimulation protocols were performed with stimulation 180 s and rest 600 s, respectively, and examined NTS activity and BP response to the protocols. RESULTS: In-vivo experiments for OL versus CL protocol for direct NTS stimulation in rats demonstrated an enhancement in temporal BP reduction via the CL modulation of NTS activity. CONCLUSION: This study proposes a CL stimulation modality that enhances the effectiveness of BP control using a feedback control algorithm based on neural signals, thereby suggesting a new approach to antihypertensive neuromodulation.

Sustainability of new energy vehicles from a battery recycling perspective: A bibliometric analysis.

In recent years, new energy vehicles (NEVs) have taken the world by storm. A large number of NEV batteries have been scrapped, and research on NEV battery recycling is important for promoting the sustainable development of NEVs. Battery recycling is an important aspect of the sustainable development of NEVs. In this study, we conducted an in-depth analysis of the current status of research on NEV battery recycling from a new perspective using bibliometric methods and visualization software. This study shows that research targeting the recycling of NEV batteries is growing rapidly, and collaborative networks exist among researchers from different countries, institutions, and fields. The focus of research has shifted from lead-acid batteries to lithium batteries, and the supply chain and circular economy related to NEV battery recycling is an emerging research hotspot. Based on our analysis, we propose that the government should establish policies to improve the recycling networks at the collection stage and provide subsidies to attract consumers. Enterprises should develop low-cobalt and cobalt-free technologies, utilize green solvents, and develop new battery swap modes. The establishment of an information platform is conducive to the further development of collaborative networks.