The state of pelvic floor muscle dynamometry: A scoping review.

AIMS: To discuss the advantages and limitation of the different pelvic floor muscle (PFM) dynamometers available, both in research and industry, and to present the extent of variation between them in terms of structure, functioning, psychometric properties, and assessment procedures. METHODS: We identified relevant studies from four databases (MEDLINE, Compendex, Web of Science, and Derwent Innovations Index) up to December 2020 using terms related to dynamometry and PFM. In addition, we conducted a hand search of the bibliographies of all relevant reports. Peer-reviewed papers, conference proceedings, patents and user's manuals for commercial dynamometers were included and assessed by two independent reviewers. RESULTS: One hundred and one records were included and 23 PFM dynamometers from 15 research groups were identified. From these, 20 were considered as clinical dynamometers (meant for research settings) and three as personal dynamometers (developed by the industry). Overall, significant heterogeneity was found in their structure and functioning, which limits development of normative data for PFM force in women. Further research is needed to assess the psychometric properties of PFM dynamometers and to standardize assessment procedures. CONCLUSION: This review points up to the heterogeneity of existing dynamometers and methods of assessing PFM function. It highlights the need to better document their design and assessment protocol methods. Additionally, this review recommends standards for new dynamometers to allow the establishment of normalized data.

Epileptic Prodromes: Insights from Surveying 196 Patients and 150 Caregivers.

OBJECTIVE: Uncontrolled epilepsy creates a constant source of worry for patients and puts them at a high risk of injury. Identifying recurrent "premonitory" symptoms of seizures and using them to recalibrate seizure prediction algorithms may improve prediction performances. This study aimed to investigate patients' ability to predict oncoming seizures based on preictal symptoms. METHODS: Through an online survey, demographics and clinical characteristics (e.g., seizure frequency, epilepsy duration, and postictal symptom duration) were collected from people with epilepsy and caregivers across Canada. Respondents were asked to answer questions regarding their ability to predict seizures through warning symptoms. A total of 196 patients and 150 caregivers were included and were separated into three groups: those who reported warning symptoms within the 5 minutes preceding a seizure, prodromes (symptoms earlier than 5 minutes before seizure), and no warning symptoms. RESULTS: Overall, 12.2% of patients and 12.0% of caregivers reported predictive prodromes ranging from 5 minutes to more than 24 hours before the seizures (median of 2 hours). The most common were dizziness/vertigo (28%), mood changes (26%), and cognitive changes (21%). Statistical testing showed that respondents who reported prodromes also reported significantly longer postictal recovery periods compared to those who did not report predictive prodromes (P < 0.05). CONCLUSION: Findings suggest that patients who present predictive seizure prodromes may be characterized by longer patient-reported postictal recovery periods. Studying the correlation between seizure severity and predictability and investigating the electrical activity underlying prodromes may improve our understanding of preictal mechanisms and ability to predict seizures.

A nanoplatform-based aptasensor to electrochemically detect epinephrine produced by living cells.

A novel aptasensor has been designed for quantitative monitoring of epinephrine (EP) based on cerium metal-organic framework (CeMOF) loaded gold nanoparticles (AuNPs). The aptamer, specific to EP, is immobilized on a flexible screen-printed electrode modified with AuNPs@CeMOF, enabling highly selective binding to the target biomolecule. Under optimized operational conditions, the peak currents using voltammetric detection measured at voltage of 83 mV (vs. Ag/AgCl) for epinephrine exhibit a linear increase within concentration in the range 1 pM-10 nM. Following this detection strategy, a boasted limit of detection of 0.3 pM was achieved, surpassing the sensitivity of most reported methods. The developed biosensor showcased exceptional performance in detection of EP in spiked serum sample, with remarkable recovery range of  95.8-113% and precision reflected by low relative standard deviation (RSD) ranging from 2.23 to 6.19%. These results indicate the potential utility of this biosensor as a valuable clinical diagnostic tool. Furthermore, in vitro experiments were carried out using the presented biosensor to monitor the release of epinephrine from PC12 cells upon extracellular stimulation with K+ ions.

Minimally Invasive Hypoglossal Nerve Stimulator Enabled by ECG Sensor and WPT to Manage Obstructive Sleep Apnea.

A hypoglossal nerve stimulator (HGNS) is an invasive device that is used to treat obstructive sleep apnea (OSA) through electrical stimulation. The conventional implantable HGNS device consists of a stimuli generator, a breathing sensor, and electrodes connected to the hypoglossal nerve via leads. However, this implant is bulky and causes significant trauma. In this paper, we propose a minimally invasive HGNS based on an electrocardiogram (ECG) sensor and wireless power transfer (WPT), consisting of a wearable breathing monitor and an implantable stimulator. The breathing external monitor utilizes an ECG sensor to identify abnormal breathing patterns associated with OSA with 88.68% accuracy, achieved through the utilization of a convolutional neural network (CNN) algorithm. With a skin thickness of 5 mm and a receiving coil diameter of 9 mm, the power conversion efficiency was measured as 31.8%. The implantable device, on the other hand, is composed of a front-end CMOS power management module (PMM), a binary-phase-shift-keying (BPSK)-based data demodulator, and a bipolar biphasic current stimuli generator. The PMM, with a silicon area of 0.06 mm2 (excluding PADs), demonstrated a power conversion efficiency of 77.5% when operating at a receiving frequency of 2 MHz. Furthermore, it offers three-voltage options (1.2 V, 1.8 V, and 3.1 V). Within the data receiver component, a low-power BPSK demodulator was ingeniously incorporated, consuming only 42 µW when supplied with a voltage of 0.7 V. The performance was achieved through the implementation of the self-biased phase-locked-loop (PLL) technique. The stimuli generator delivers biphasic constant currents, providing a 5 bit programmable range spanning from 0 to 2.4 mA. The functionality of the proposed ECG- and WPT-based HGNS was validated, representing a highly promising solution for the effective management of OSA, all while minimizing the trauma and space requirements.

Superparamagnetic iron oxide nanoparticles-based detection of neuronal activity.

Precise detection of brain regions harboring heightened electrical activity plays a central role in the understanding and treatment of diseases such as epilepsy. Superparamagnetic iron oxide nanoparticles (SPIONs) react to magnetic fields by aggregating and represent interesting candidates as new sensors for neuronal magnetic activity. We hypothesized that SPIONs in aqueous solution close to active brain tissue would aggregate proportionally to neuronal activity. We tested this hypothesis using an in vitro model of rat brain slice with different levels of activity. Aggregation was assessed with dynamic light scattering (DLS) and magnetic resonance imaging (MRI). We found that increasing brain slice activity was associated with higher levels of aggregation as measured by DLS and MRI, suggesting that the magnetic fields from neuronal tissue could induce aggregation in nearby SPIONs in solution. MRI signal change induced by SPIONs aggregation could serve as a powerful new tool for detection of brain electrical activity.

Surface Optimization and Design Adaptation toward Spheroid Formation On-Chip.

Spheroids have become an essential tool in preclinical cancer research. The uniformity of spheroids is a critical parameter in drug test results. Spheroids form by self-assembly of cells. Hence, the control of homogeneity of spheroids in terms of size, shape, and density is challenging. We developed surface-optimized polydimethylsiloxane (PDMS) biochip platforms for uniform spheroid formation on-chip. These biochips were surface modified with 10% bovine serum albumin (BSA) to effectively suppress cell adhesion on the PDMS surface. These surface-optimized platforms facilitate cell self-aggregations to produce homogenous non-scaffold-based spheroids. We produced uniform spheroids on these biochips using six different established human cell lines and a co-culture model. Here, we observe that the concentration of the BSA is important in blocking cell adhesion to the PDMS surfaces. Biochips treated with 3% BSA demonstrated cell repellent properties similar to the bare PDMS surfaces. This work highlights the importance of surface modification on spheroid production on PDMS-based microfluidic devices.

Rapid Optical Biosensing of SARS-CoV-2 Spike Proteins in Artificial Samples.

Tests for SARS-CoV-2 are crucial for the mass surveillance of the incidence of infection. The long waiting time for classic nucleic acid test results highlights the importance of developing alternative rapid biosensing methods. Herein, we propose a fiber-optic biolayer interferometry-based biosensor (FO-BLI) to detect SARS-CoV-2 spike proteins, extracellular domain (ECD), and receptor-binding domain (RBD) in artificial samples in 13 min. The FO-BLI biosensor utilized an antibody pair to capture and detect the spike proteins. The secondary antibody conjugated with horseradish peroxidase (HRP) reacted with the enzyme substrate for signal amplification. Two types of substrates, 3,3'-diaminobenzidine (DAB) and an advanced 3-Amino-9-ethylcarbazole (i.e., AMEC), were applied to evaluate their capabilities in enhancing signals and reaching high sensitivity. After careful comparison, the AMEC-based FO-BLI biosensor showed better assay performance, which detected ECD at a concentration of 32-720 pM and RBD of 12.5-400 pM in artificial saliva and serum, respectively. The limit of detection (LoD) for SARS-CoV-2 ECD and RBD was defined to be 36 pM and 12.5 pM, respectively. Morphology of the metal precipitates generated by the AMEC-HRP reaction in the fiber tips was observed using field emission scanning electron microscopy (SEM). Collectively, the developed FO-BLI biosensor has the potential to rapidly detect SARS-CoV-2 antigens and provide guidance for "sample-collect and result-out on-site" mode.

Sex differences in the developing brain impact stress-induced epileptogenicity following hyperthermia-induced seizures.

Febrile seizures (FS) are common, affecting 2-5% of children between the ages of 3 months and 6 years. Complex FS occur in 10% of patients with FS and are strongly associated with mesial temporal lobe epilepsy. Current research suggests that predisposing factors, such as genetic and anatomic abnormalities, may be necessary for complex FS to translate to mesial temporal lobe epilepsy. Sex hormones are known to influence seizure susceptibility and epileptogenesis, but whether sex-specific effects of early life stress play a role in epileptogenesis is unclear. Here, we investigate sex differences in the activity of the hypothalamic-pituitary-adrenal (HPA) axis following chronic stress and the underlying contributions of gonadal hormones to the susceptibility of hyperthermia-induced seizures (HS) in rat pups. Chronic stress consisted of daily injections of 40 mg/kg of corticosterone (CORT) subcutaneously from postnatal day (P) 1 to P9 in male and female rat pups followed by HS at P10. Body mass, plasma CORT levels, temperature threshold to HS, seizure characteristics, and electroencephalographic in vivo recordings were compared between CORT- and vehicle (VEH)-injected littermates during and after HS at P10. In juvenile rats (P18-P22), in vitro CA1 pyramidal cell recordings were recorded in males to investigate excitatory and inhibitory neuronal circuits. Results show that daily CORT injections increased basal plasma CORT levels before HS and significantly reduced weight gain and body temperature threshold of HS in both males and females. CORT also significantly lowered the generalized convulsions (GC) latency while increasing recovery time and the number of electrographic seizures (>10s), which had longer duration. Furthermore, sex-specific differences were found in response to chronic CORT injections. Compared to females, male pups had increased basal plasma CORT levels after HS, longer recovery time and a higher number of electrographic seizures (>10s), which also had longer duration. Sex-specific differences were also found at baseline conditions with lower latency to generalized convulsions and longer duration of electrographic seizures in males but not in females. In juvenile male rats, the amplitude of evoked excitatory postsynaptic potentials, as well as the amplitude of inhibitory postsynaptic currents, were significantly greater in CORT rats when compared to VEH littermates. These findings not only validate CORT injections as a stress model, but also show a sex difference in baseline conditions as well as a response to chronic CORT and an impact on seizure susceptibility, supporting a potential link between sustained early-life stress and complex FS. Overall, these effects also indicate a putatively less severe phenotype in female than male pups. Ultimately, studies investigating the biological underpinnings of sex differences as a determining factor in mental and neurologic problems are necessary to develop better diagnostic, preventative, and therapeutic approaches for all patients regardless of their sex.

Contact and Remote Breathing Rate Monitoring Techniques: A Review.

Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients' comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared.

Clinical and Research Solutions to Manage Obstructive Sleep Apnea: A Review.

Obstructive sleep apnea (OSA), a common sleep disorder disease, affects millions of people. Without appropriate treatment, this disease can provoke several health-related risks including stroke and sudden death. A variety of treatments have been introduced to relieve OSA. The main present clinical treatments and undertaken research activities to improve the success rate of OSA were covered in this paper. Additionally, guidelines on choosing a suitable treatment based on scientific evidence and objective comparison were provided. This review paper specifically elaborated the clinically offered managements as well as the research activities to better treat OSA. We analyzed the methodology of each diagnostic and treatment method, the success rate, and the economic burden on the world. This review paper provided an evidence-based comparison of each treatment to guide patients and physicians, but there are some limitations that would affect the comparison result. Future research should consider the consistent follow-up period and a sufficient number of samples. With the development of implantable medical devices, hypoglossal nerve stimulation systems will be designed to be smart and miniature and one of the potential upcoming research topics. The transcutaneous electrical stimulation as a non-invasive potential treatment would be further investigated in a clinical setting. Meanwhile, no treatment can cure OSA due to the complicated etiology. To maximize the treatment success of OSA, a multidisciplinary and integrated management would be considered in the future.

Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction.

We review in this paper the wearable-based technologies intended for real-time monitoring of stroke-related physiological parameters. These measurements are undertaken to prevent death and disability due to stroke. We compare the various characteristics, such as weight, accessibility, frequency of use, data continuity, and response time of these wearables. It was found that the most user-friendly wearables can have limitations in reporting high-precision prediction outcomes. Therefore, we report also the trend of integrating these wearables into the internet of things (IoT) and combining electronic health records (EHRs) and machine learning (ML) algorithms to establish a stroke risk prediction system. Due to different characteristics, such as accessibility, time, and spatial resolution of various wearable-based technologies, strategies of applying different types of wearables to maximize the efficacy of stroke risk prediction are also reported. In addition, based on the various applications of multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) on stroke patients, the perspective of using this technique to improve the prediction performance is elaborated. Expected prediction has to be dynamically delivered with high-precision outcomes. There is a need for stroke risk stratification and management to reduce the resulting social and economic burden.

Energy Solutions for Wearable Sensors: A Review.

Wearable sensors have gained popularity over the years since they offer constant and real-time physiological information about the human body. Wearable sensors have been applied in a variety of ways in clinical settings to monitor health conditions. These technologies require energy sources to carry out their projected functionalities. In this paper, we review the main energy sources used to power wearable sensors. These energy sources include batteries, solar cells, biofuel cells, supercapacitors, thermoelectric generators, piezoelectric and triboelectric generators, and radio frequency (RF) energy harvesters. Additionally, we discuss wireless power transfer and some hybrids of the above technologies. The advantages and drawbacks of each technology are considered along with the system components and attributes that make these devices function effectively. The objective of this review is to inform researchers about the latest developments in this field and present future research opportunities.

Real-time in vivo detection techniques for neurotransmitters: a review.

Functional synapses in the central nervous system depend on a chemical signal exchange process that involves neurotransmitter delivery between neurons and receptor cells in the neuro system. Abnormal neurotransmitter levels and distributions can cause intractable diseases involving descending/ascending modulatory pathways or dysfunctional organs. The detection of abnormal neurotransmitter levels is one of the most promising techniques in the diagnosis of brain diseases. Also, numerous effective methods for the detection of neurotransmitters in vivo have been fabricated. Nowadays, electrochemical, optical, magnetic, and microdialysis methods are among the main techniques used to detect neurotransmitters. Herein, we review current techniques for detecting eight types of neurotransmitters with a focus on in vivo neurotransmitter tracking methods intended for the real-time diagnosis of brain disorders.

Multi-Channel Neural Recording Implants: A Review.

The recently growing progress in neuroscience research and relevant achievements, as well as advancements in the fabrication process, have increased the demand for neural interfacing systems. Brain-machine interfaces (BMIs) have been revealed to be a promising method for the diagnosis and treatment of neurological disorders and the restoration of sensory and motor function. Neural recording implants, as a part of BMI, are capable of capturing brain signals, and amplifying, digitizing, and transferring them outside of the body with a transmitter. The main challenges of designing such implants are minimizing power consumption and the silicon area. In this paper, multi-channel neural recording implants are surveyed. After presenting various neural-signal features, we investigate main available neural recording circuit and system architectures. The fundamental blocks of available architectures, such as neural amplifiers, analog to digital converters (ADCs) and compression blocks, are explored. We cover the various topologies of neural amplifiers, provide a comparison, and probe their design challenges. To achieve a relatively high SNR at the output of the neural amplifier, noise reduction techniques are discussed. Also, to transfer neural signals outside of the body, they are digitized using data converters, then in most cases, the data compression is applied to mitigate power consumption. We present the various dedicated ADC structures, as well as an overview of main data compression methods.

A GaN-Based Wireless Monitoring System for High-Temperature Applications.

A fully-integrated data transmission system based on gallium nitride (GaN) high-electron-mobility transistor (HEMT) devices is proposed. This system targets high-temperature (HT) applications, especially those involving pressure and temperature sensors for aerospace in which the environmental temperature exceeds 350 °C. The presented system includes a front-end amplifying the sensed signal (gain of 50 V/V), followed by a novel analog-to-digital converter driving a modulator exploiting the load-shift keying technique. An oscillation frequency of 1.5 MHz is used to ensure a robust wireless transmission through metallic-based barriers. To retrieve the data, a new demodulator architecture based on digital circuits is proposed. A 1 V amplitude difference can be detected between a high-amplitude (data-on) and a low-amplitude (data-off) of the received modulated signal. Two high-voltage supply levels (+14 V and -14 V) are required to operate the circuits. The layout of the proposed system was completed in a chip occupying 10.8 mm2. The HT characterization and modeling of integrated GaN devices and passive components are performed to ensure the reliability of simulation results. The performance of the various proposed building blocks, as well as the whole system, have been validated by simulation over the projected wide operating temperature range (25-350 °C).

Multichannel wearable fNIRS-EEG system for long-term clinical monitoring.

Continuous brain imaging techniques can be beneficial for the monitoring of neurological pathologies (such as epilepsy or stroke) and neuroimaging protocols involving movement. Among existing ones, functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) have the advantage of being noninvasive, nonobstructive, inexpensive, yield portable solutions, and offer complementary monitoring of electrical and local hemodynamic activities. This article presents a novel system with 128 fNIRS channels and 32 EEG channels with the potential to cover a larger fraction of the adult superficial cortex than earlier works, is integrated with 32 EEG channels, is light and battery-powered to improve portability, and can transmit data wirelessly to an interface for real-time display of electrical and hemodynamic activities. A novel fNIRS-EEG stretchable cap, two analog channels for auxiliary data (e.g., electrocardiogram), eight digital triggers for event-related protocols and an internal accelerometer for movement artifacts removal contribute to improve data acquisition quality. The system can run continuously for 24 h. Following instrumentation validation and reliability on a solid phantom, performance was evaluated on (1) 12 healthy participants during either a visual (checkerboard) task at rest or while pedalling on a stationary bicycle or a cognitive (language) task and (2) 4 patients admitted either to the epilepsy (n = 3) or stroke (n = 1) units. Data analysis confirmed expected hemodynamic variations during validation recordings and useful clinical information during in-hospital testing. To the best of our knowledge, this is the first demonstration of a wearable wireless multichannel fNIRS-EEG monitoring system in patients with neurological conditions. Hum Brain Mapp 39:7-23, 2018. © 2017 Wiley Periodicals, Inc.

Microelectronics-based biosensors dedicated to the detection of neurotransmitters: a review.

Dysregulation of neurotransmitters (NTs) in the human body are related to diseases such as Parkinson's and Alzheimer's. The mechanisms of several neurological disorders, such as epilepsy, have been linked to NTs. Because the number of diagnosed cases is increasing, the diagnosis and treatment of such diseases are important. To detect biomolecules including NTs, microtechnology, micro and nanoelectronics have become popular in the form of the miniaturization of medical and clinical devices. They offer high-performance features in terms of sensitivity, as well as low-background noise. In this paper, we review various devices and circuit techniques used for monitoring NTs in vitro and in vivo and compare various methods described in recent publications.

Challenges and Perspectives on Impulse Radio-Ultra-Wideband Transceivers for Neural Recording Applications.

Brain-machine interfaces (BMI) are widely adopted in neuroscience investigations and neural prosthetics, with sensing channel counts constantly increasing. These Investigations place increasing demands for high data rates and low-power implantable devices despite high tissue losses. The Impulse radio ultra-wideband (IR-UWB), a revived wireless technology for short-range radios, has been widely used in various applications. Since the requirements and solutions are application-oriented, in this review paper we focus on neural recording implants with high-data rates and ultra-low power requirements. We examine in detail the working principle, design methodology, performance, and implementations of different architectures of IR-UWB transceivers in a quantitative manner to draw a deep comparison and extract the bottlenecks and possible solutions concerning the dedicated application. Our analysis shows that current solutions rely on enhanced or combined modulation techniques to improve link margin. An in-depth study of prior-art publications that achieved Gbps data rates concludes that edge-combination architecture and non-coherent detectors are remarkable for transmitter and receiver, respectively. Although the aim to minimize power and improve data rate - defined as energy efficiency (pJ/b) - extending communication distance despite high tissue losses and limited power budget, good narrow-band interference (NBI) tolerance coexisted in the same frequency band of UWB systems, and compatibility with energy harvesting designs are among the critical challenges remained unsolved. Furthermore, we expect that the combination of artificial intelligence (AI) and the inherent advantages of UWB radios will pave the way for future improvements in BMIs.

Neuro-BERT: Rethinking Masked Autoencoding for Self-Supervised Neurological Pretraining.

Deep learning associated with neurological signals is poised to drive major advancements in diverse fields such as medical diagnostics, neurorehabilitation, and brain-computer interfaces. The challenge in harnessing the full potential of these signals lies in the dependency on extensive, high-quality annotated data, which is often scarce and expensive to acquire, requiring specialized infrastructure and domain expertise. To address the appetite for data in deep learning, we present Neuro-BERT, a self-supervised pre-training framework of neurological signals based on masked autoencoding in the Fourier domain. The intuition behind our approach is simple: frequency and phase distribution of neurological signals can reveal intricate neurological activities. We propose a novel pre-training task dubbed Fourier Inversion Prediction (FIP), which randomly masks out a portion of the input signal and then predicts the missing information using the Fourier inversion theorem. Pre-trained models can be potentially used for various downstream tasks such as sleep stage classification and gesture recognition. Unlike contrastive-based methods, which strongly rely on carefully hand-crafted augmentations and siamese structure, our approach works reasonably well with a simple transformer encoder with no augmentation requirements. By evaluating our method on several benchmark datasets, we show that Neuro-BERT improves downstream neurological-related tasks by a large margin.

Alzheimer's Disease Diagnosis in the Preclinical Stage: Normal Aging or Dementia.

Alzheimer's disease (AD) progressively impairs the memory and thinking skills of patients, resulting in a significant global economic and social burden each year. However, diagnosis of this neurodegenerative disorder can be challenging, particularly in the early stages of developing cognitive decline. Current clinical techniques are expensive, laborious, and invasive, which hinders comprehensive studies on Alzheimer's biomarkers and the development of efficient devices for Point-of-Care testing (POCT) applications. To address these limitations, researchers have been investigating various biosensing techniques. Unfortunately, these methods have not been commercialized due to several drawbacks, such as low efficiency, reproducibility, and the lack of accurate identification of AD markers. In this review, we present diverse promising hallmarks of Alzheimer's disease identified in various biofluids and body behaviors. Additionally, we thoroughly discuss different biosensing mechanisms and the associated challenges in disease diagnosis. In each context, we highlight the potential of realizing new biosensors to study various features of the disease, facilitating its early diagnosis in POCT. This comprehensive study, focusing on recent efforts for different aspects of the disease and representing promising opportunities, aims to conduct the future trend toward developing a new generation of compact multipurpose devices that can address the challenges in the early detection of AD.