Abbas Erfanian

Despite widespread clinical adoption for disorders of incontinence such as overactive bladder, there remain unknowns surrounding the mechanism that underpins tibial nerve stimulation (TNS). Current understanding suggests that TNS counteracts incontinence by the inhibition of brainstem and spinal cord activity. How this inhibition alters bladder function is not fully understood. We hypothesize that the supraspinal components of the system act as a high-pass filter, allowing voiding signals to proceed only when bladder filling reaches a critical level. Testing this hypothesis may explain how TNS is able to induce both an inhibitory and a little-explored excitatory effect on bladder activity in response to high-frequency (20 Hz) and low-frequency (1 Hz) stimulation, respectively. We performed a single-blinded trial in healthy human participants administered high- and low-frequency transcutaneous TNS. We also developed a computational model of the lower-urinary tract and control circuit to study the frequency-dependent effects of TNS. For the first time, we report a frequency-dependent effect of TNS via the ability to alter urge perception and upregulate and downregulate bladder activity, corroborating model predictions. These results provide a foundation for the development of targeted and effective TNS therapies, benefiting from in silico models. We hope that future clinical research will determine the efficacy of low-frequency TNS as a non-invasive treatment option for urinary retention.

Despite widespread clinical adoption for disorders of incontinence such as overactive bladder, there remain unknowns surrounding the mechanism that underpins Tibial Nerve Stimulation (TNS). Current understanding suggests that TNS counteracts incontinence by the inhibition of brainstem and spinal cord activity. How this inhibition alters bladder function is not fully understood. We hypothesize that the supraspinal components of the system act as a high-pass filter, allowing voiding signals to proceed only when bladder filling reaches a critical level. Testing this hypothesis may explain how TNS is able to induce both an inhibitory and a little-explored excitatory effect on bladder activity in response to high-frequency (20 Hz) and low-frequency (1 Hz) stimulation, respectively. We performed a single-blinded trial in healthy human participants administered high and low-frequency Transcutaneous TNS. We also developed a computational model of the lower-urinary tract and control circuit to study the frequency-dependent effects of TNS. For the first time, we report a frequency-dependent effect of TNS via the ability to alter urge perception and up-regulate and down-regulate bladder activity, corroborating model predictions. These results provide a foundation for the development of targeted and effective TNS therapies, benefiting from in silico models. We hope that future clinical research will determine the efficacy of low-frequency TNS as a non-invasive treatment option for urinary retention.

Lower urinary tract symptoms affect a significant proportion of the population. In silico medicine can help understand these conditions and develop treatments. However, many of the current lower urinary tract computational models are closed source, too deterministic and do not allow for simple use of modelling neural intervention. An open-source Python-based model was developed to simulate bladder, sphincter and kidney dynamics using normalized neural signals to predict pressure and volume. The model was verified against animal bladder data from adult male Wistar rats, assessed for noise sensitivity and evaluated against known physiological factors. The animal data comparison yielded a significantly more similar pattern than existing models, with a correlation coefficient of r = 0.93 ( p < 0.001). All physiological factors were within bounds, and the model remained stable with noise under the described boundaries. The proposed model advances the field of computational medicine by providing an open-source model for researchers and developers. It improves upon existing models by being accessible, including a built-in neural model that better replicates smooth bladder filling results, and incorporating a novel kidney function that alters bladder function by time of day in line with circadian rhythm. Future applications include personalized medicine, treating lower urinary tract symptoms with in silico models and adaptive neural interventions.

This article introduces a fully automated, continuous nonsingular terminal sliding mode (TSM) control technique to control uncertain, nonlinear, and time-varying second-order systems with both structured and unstructured uncertainties. This proposed TSM control approach is not only continuous, chattering-free, and finite-time stable but also eliminates the necessity of offline identification of the system dynamics and of any assumptions about the upper bounds of the uncertainty. In most practical applications, estimating these boundaries is difficult and challenging. Consequently, large values are chosen and assigned to the control gains to guarantee finite-time convergence. Nevertheless, overestimating the controller gains increases chattering and results in noticeable performance degradation. In this article, TSM-based adaptive laws are proposed for estimating the upper bound of the uncertainties. Moreover, TSM-based control law is proposed such that the finite-time convergence is guaranteed. To evaluate the efficacy of the proposed method, it is applied for the control of an uncertain two-link rigid robotic manipulator as well as for the regulation of admittance and cadence in a real motorized functional electrical stimulation (FES) cycling system. The simulation and experimental studies corroborate that the proposed strategy can provide favorable control performance without chattering under system parameter variations and unknown bounded disturbances.

In this paper, a new high-voltage and high-current compliance integrated electrical neurostimulator with charge balancing stimuli is presented. The proposed stimulator uses a stacked structure to provide the 11.2 V power supply delivering a biphasic stimulation current of 3.2 mA. It includes a novel charge balancing method to secure safe symmetric and asymmetric biphasic pulse trains with a low charge mismatch of 0.21%. Also, the proposed device properly cancels the switching current spikes generating biphasic stimuli. In addition, two methods based on a gate driver circuit and zero current switching are proposed securing advanced stimulator feature which are validated through extensive testing phase, including a simulation of 29 million periodic stimulation cycles delivering a current of 3.2 mA. The stimulator demonstrates robust performance with an average residual DC current of 11.4 nA after the charge balancing phase. The stimulator is implemented using the standard TSMC 180 nm 1.8 V/3.3 V LV CMOS technology. It operates at a low power budget of 90 μW. The main core of the circuit occupies an area of 0.181mm2. The fabricated chip has been packaged and successfully tested in a motor function of intraspinal paralysis application.

Objective: Electrical stimulation of the pudendal nerve, pelvic nerve, sacral dorsal root ganglion (DRG), and spinal cord has been explored to treat urinary incontinence and overactive bladder (OAB). This study introduces sacral intraspinal microstimulation (ISMS) as a novel method to inhibit spontaneous bladder reflexes in anesthetized cats. In addition, we investigated the effects of intermittent and switching stimulation patterns on bladder inhibition.Methods: The electrode was implanted in the dorsal horn of the S2 spinal cord. Bladder pressure was recorded under isovolumetric conditions, and the stimulation parameters were adjusted to inhibit spontaneous bladder contractions. Nonlinear dynamic methods, including chaos theory, were employed to analyze the complexity of bladder reflexes.Results: Results demonstrated that ISMS targeting the dorsal horn of the S2 spinal segment effectively suppressed high-amplitude spontaneous contractions. Furthermore, bladder reflexes exhibited complex dynamics, ranging from regular to chaotic patterns, with transitions between these states. Importantly, ISMS was able to stabilize these chaotic dynamics, leading to more controlled bladder behavior.Conclusion: These findings suggest that sacral ISMS offers a promising, targeted alternative to traditional stimulation therapies, potentially providing a new therapeutic approach for managing OAB and urinary incontinence by regulating chaotic bladder activity.

Background: Lower urinary tract (LUT) symptoms affect a significant proportion of the population. In-silico medicine can help understand these conditions and develop treatments. However, current LUT computational models are closed source, too deterministic, and do not allow for simple use of modelling neural intervention. Methods: An open-source Python-based model was developed to simulate bladder, sphincter, and kidney dynamics using normalised neural signals to predict pressure and volume. The model was verified against animal bladder data, assessed for noise sensitivity, and evaluated against known physiological factors. Results: The animal data comparison yielded a significantly more similar pattern than existing models, with a correlation coefficient of r = 0.93 ( p < 0.001). All physiological factors were within bounds, and the model remained stable with noise under the described boundaries. Conclusion: The proposed model advances the field of computational medicine by providing an open-source model for researchers and developers. It improves upon existing models by being accessible, including a built-in neural model that better replicates smooth bladder filling results, and incorporating a novel kidney function that alters bladder function by time of day in line with circadian rhythm. Future applications include personalised medicine, treating LUT symptoms with in-silico models and adaptive neural interventions.

Electrical neural stimulators (ENS) play a crucial role in medical applications and have emerged as promising therapeutic techniques for neurological disorders. The purpose of designing this device in medicine and research is to provide therapeutic benefits, aid in rehabilitation, restore sensory perception, advance scientific knowledge, and enable personalized treatment approaches. The utilization of ENS can significantly improve the quality of life for individuals with neurological disorders and contribute to advancements in neuroscience. Recently, there has been a growing inclination towards implantable biomedical microsystems, which has enticed biomedical engineers and researchers to integrate and implement electrical neural stimulators using CMOS technology. Thus, we present this review to provide a comprehensive overview of integrated circuits in the ENS field. The review aims to discuss the operational principles, design considerations, and approaches while highlighting advancements, applications, and future directions. The review begins with an introduction, emphasizing the necessity of stimulation and the fundamental principles of the ENS. It then discusses the various stimulation patterns, exploring how these patterns can modify neural circuits and restore normal function, as well as the circuit implementations involved in generating the stimulation. Design considerations specific to stimulators are also discussed. Furthermore, the review summarizes the state-of-the-art circuits and systems for the ENS, employing a top-down approach that covers specifications, circuits, and system design. Additionally, it briefly provides an overview of experimental approaches and results from various biomedical tests. Finally, this review outlines future directions, trends, and challenges for enhancing precision, safety, and patient outcomes in stimulation therapies.