Advanced Sensing System for Sleep Bruxism across Multiple Postures via EMG and Machine Learning.

Diagnosis of bruxism is challenging because not all contractions of the masticatory muscles can be classified as bruxism. Conventional methods for sleep bruxism detection vary in effectiveness. Some provide objective data through EMG, ECG, or EEG; others, such as dental implants, are less accessible for daily practice. These methods have targeted the masseter as the key muscle for bruxism detection. However, it is important to consider that the temporalis muscle is also active during bruxism among masticatory muscles. Moreover, studies have predominantly examined sleep bruxism in the supine position, but other anatomical positions are also associated with sleep. In this research, we have collected EMG data to detect the maximum voluntary contraction of the temporalis and masseter muscles in three primary anatomical positions associated with sleep, i.e., supine and left and right lateral recumbent positions. A total of 10 time domain features were extracted, and six machine learning classifiers were compared, with random forest outperforming others. The models achieved better accuracies in the detection of sleep bruxism with the temporalis muscle. An accuracy of 93.33% was specifically found for the left lateral recumbent position among the specified anatomical positions. These results indicate a promising direction of machine learning in clinical applications, facilitating enhanced diagnosis and management of sleep bruxism.

A Hybrid Approach for Energy Consumption and Improvement in Sensor Network Lifespan in Wireless Sensor Networks.

In this paper, we propose an improved clustering algorithm for wireless sensor networks (WSNs) that aims to increase network lifetime and efficiency. We introduce an enhanced fuzzy spider monkey optimization technique and a hidden Markov model-based clustering algorithm for selecting cluster heads. Our approach considers factors such as network cluster head energy, cluster head density, and cluster head position. We also enhance the energy-efficient routing strategy for connecting cluster heads to the base station. Additionally, we introduce a polling control method to improve network performance while maintaining energy efficiency during steady transmission periods. Simulation results demonstrate a 1.2% improvement in network performance using our proposed model.

Preparation and Performance Analysis of 3D Thermoformed Fluidic Polymer Temperature Sensors for Aquatic and Terrestrial Applications.

Employing a combination of Polyethylene terephthalate (PET) thermoforming and 3D-printed cylindrical patterns, we carefully engineer a linear resistive temperature sensor. This intricate process involves initial PET thermoforming, yielding a hollow cylindrical chamber. This chamber is then precisely infused with a composite fluid of graphite and water glue. Ensuring electrical connectivity, both ends are affixed with metal wires and securely sealed using a hot gun. This cost-effective, versatile sensor adeptly gauges temperature shifts by assessing composite fluid resistance alterations. Its PET outer surface grants immunity to water and solubility concerns, enabling application in aquatic and aerial settings without extra encapsulation. Rigorous testing reveals the sensor's linearity and stability within a 10 °C to 60 °C range, whether submerged or airborne. Beyond 65 °C, plastic deformation arises. To mitigate hysteresis, a 58 °C operational limit is recommended. Examining fluidic composite width and length effects, we ascertain a 12 Ω/°C sensitivity for these linear sensors, a hallmark of their precision. Impressive response and recovery times of 4 and 8 s, respectively, highlight their efficiency. These findings endorse thermoforming's potential for fabricating advanced temperature sensors. This cost-effective approach's adaptability underscores its viability for diverse applications.

Decade of 2D-materials-based RRAM devices: a review.

Two dimensional (2D) materials have offered unique electrical, chemical, mechanical and physical properties over the past decade owing to their ultrathin, flexible, and multilayer structure. These layered materials are being used in numerous electronic devices for various applications, and this review will specifically focus on the resistive random access memories (RRAMs) based on 2D materials and their nanocomposites. This study presents the device structures, conduction mechanisms, resistive switching properties, fabrication technologies, challenges and future aspects of 2D-materials-based RRAMs. Graphene, derivatives of graphene and MoS2 have been the major contributors among 2D materials for the application of RRAMs; however, other members of this family such as hBN, MoSe2, WS2 and WSe2 have also been inspected more recently as the functional materials of nonvolatile RRAM devices. Conduction in these devices is usually dominated by either the penetration of metallic ions or migration of intrinsic species. Most prominent advantages offered by RRAM devices based on 2D materials include fast switching speed (<10 ns), less power losses (10 pJ), lower threshold voltage (<1 V) long retention time (>10 years), high electrical endurance (>108 voltage cycles) and extended mechanical robustness (500 bending cycles). Resistive switching properties of 2D materials have been further enhanced by blending them with metallic nanoparticles, organic polymers and inorganic semiconductors in various forms.

3D printing for soft robotics - a review.

Soft robots have received an increasing attention due to their advantages of high flexibility and safety for human operators but the fabrication is a challenge. Recently, 3D printing has been used as a key technology to fabricate soft robots because of high quality and printing multiple materials at the same time. Functional soft materials are particularly well suited for soft robotics due to a wide range of stimulants and sensitive demonstration of large deformations, high motion complexities and varied multi-functionalities. This review comprises a detailed survey of 3D printing in soft robotics. The development of key 3D printing technologies and new materials along with composites for soft robotic applications is investigated. A brief summary of 3D-printed soft devices suitable for medical to industrial applications is also included. The growing research on both 3D printing and soft robotics needs a summary of the major reported studies and the authors believe that this review article serves the purpose.

Self-Powered Humidity Sensor Driven by Triboelectric Nanogenerator Composed of Bio-Wasted Peanut Skin Powder.

The increasing number of IoT devices has led to more electronic waste production, which harms the environment and human health. Self-powered sensor systems are a solution, but they often use toxic materials. We propose using biocompatible peanut skin as the active material for a self-powered humidity sensor (PSP-SPHS) through integration with a peanut-skin-based triboelectric nanogenerator (PSP-TENG). The PSP-TENG was characterized electrically and showed promising results, including an open circuit voltage (162 V), short circuit current (0.2 µA), and instantaneous power (2.2 mW) at a loading resistance of 20 MΩ. Peanut skin is a great choice for the sensor due to its porous surface, large surface area, eco-friendliness, and affordability. PSP-TENG was further used as a power source for the PSP-humidity sensor. PSP-SPHS worked as a humidity-dependent resistor, whose resistance decreased with increasing relative humidity (%RH), which further resulted in decreasing voltage across the humidity sensor. This proposed PSP-SPHS exhibited a good sensitivity (0.8 V/RH%), fast response/recovery time (4/10 s), along with excellent stability and repeatability, making it a potential candidate for self-powered humidity sensor technology.

Highly Sensitive and Stable Humidity Sensor Based on the Bi-Layered PVA/Graphene Flower Composite Film.

Two-dimensional (2D) materials and their composites have gained significant importance as the functional layer of various environmental sensors and nanoelectronics owing to their unique properties. This work reports for the first time a highly sensitive, fast, and stable humidity sensor based on the bi-layered active sensing area composed of graphene flower (GF) and poly (vinyl alcohol) PVA thin films for multifunctional applications. The GF/PVA humidity sensor exhibited stable impedance response over 15 days, for a relative humidity (RH) range of (40-90% RH) under ambient operating conditions. The proposed bi-layered humidity sensor also exhibited an ultra-high capacitive sensitivity response of the 29 nF/%RH at 10 kHz and fast transient response of 2 s and 3.5 s, respectively. Furthermore, the reported sensor also showed a good response towards multi-functional applications such as non-contact skin humidity and mouth breathing detection.

All-Printed Flexible Memristor with Metal-Non-Metal-Doped TiO2 Nanoparticle Thin Films.

A memristor is a fundamental electronic device that operates like a biological synapse and is considered as the solution of classical von Neumann computers. Here, a fully printed and flexible memristor is fabricated by depositing a thin film of metal-non-metal (chromium-nitrogen)-doped titanium dioxide (TiO2). The resulting device exhibited enhanced performance with self-rectifying and forming free bipolar switching behavior. Doping was performed to bring stability in the performance of the memristor by controlling the defects and impurity levels. The forming free memristor exhibited characteristic behavior of bipolar resistive switching with a high on/off ratio (2.5 × 103), high endurance (500 cycles), long retention time (5 × 103 s) and low operating voltage (±1 V). Doping the thin film of TiO2 with metal-non-metal had a significant effect on the switching properties and conduction mechanism as it directly affected the energy bandgap by lowering it from 3.2 eV to 2.76 eV. Doping enhanced the mobility of charge carriers and eased the process of filament formation by suppressing its randomness between electrodes under the applied electric field. Furthermore, metal-non-metal-doped TiO2 thin film exhibited less switching current and improved non-linearity by controlling the surface defects.

High-Performance Humidity Sensor Based on the Graphene Flower/Zinc Oxide Composite.

Performance of an electronic device relies heavily on the availability of a suitable functional material. One of the simple, easy, and cost-effective ways to obtain novel functional materials with improved properties for desired applications is to make composites of selected materials. In this work, a novel composite of transparent n-type zinc oxide (ZnO) with a wide bandgap and a unique structure of graphene in the form of a graphene flower (GrF) is synthesized and used as the functional layer of a humidity sensor. The (GrF/ZnO) composite was synthesized by a simple sol-gel method. Morphological, elemental, and structural characterizations of GrF/ZnO composite were performed by a field emission scanning electron microscope (FESEM), energy-dispersive spectroscopy (EDS), and an x-ray diffractometer (XRD), respectively, to fully understand the properties of this newly synthesized functional material. The proposed humidity sensor was tested in the relative humidity (RH) range of 15% RH% to 86% RH%. The demonstrated sensor illustrated a highly sensitive response to humidity with an average current change of 7.77 µA/RH%. Other prominent characteristics shown by this device include but were not limited to high stability, repeatable results, fast response, and quick recovery time. The proposed humidity sensor was highly sensitive to human breathing, thus making it a promising candidate for various applications related to health monitoring.

Highly Efficient and Wide Range Humidity Response of Biocompatible Egg White Thin Film.

Biopolymers are a solution to solve the increasing problems caused by the advances and revolution in the electronic industry owing to the use of hazardous chemicals. In this work, we have used egg white (EW) as the low-cost functional layer of a biocompatible humidity sensor and deposited it on gold (Au) interdigitated electrodes (IDEs) patterned through the state-of-the-art fabrication technology of thermal vacuum evaporation. The presence of hydrophilic proteins inside the thin film of EW makes it an attractive candidate for sensing humidity. Usually, the dependence of the percentage of relative humidity (%RH) on the reliability of measurement setup is overlooked for impedimetric humidity sensors but we have used a modified experimental setup to enhance the uniformity of the obtained results. The characteristics of our device include almost linear response with a quick response time (1.2 s) and fast recovery time (1.7 s). High sensitivity of 50 kΩ/%RH was achieved in the desirable detection range of 10-85%RH. The device size was intentionally kept small for its potential integration in a marketable chip. Results for the response of our fabricated sensor for dry and wet fingertips, along with determining the rate of breathing through the mouth, are part of this study, making it a potential device for health monitoring.

A Full-Range Flexible and Printed Humidity Sensor Based on a Solution-Processed P(VDF-TrFE)/Graphene-Flower Composite.

A novel composite based on a polymer (P(VDF-TrFE)) and a two-dimensional material (graphene flower) was proposed as the active layer of an interdigitated electrode (IDEs) based humidity sensor. Silver (Ag) IDEs were screen printed on a flexible polyethylene terephthalate (PET) substrate followed by spin coating the active layer of P(VDF-TrFE)/graphene flower on its surface. It was observed that this sensor responds to a wide relative humidity range (RH%) of 8-98% with a fast response and recovery time of 0.8 s and 2.5 s for the capacitance, respectively. The fabricated sensor displayed an inversely proportional response between capacitance and RH%, while a directly proportional relationship was observed between its impedance and RH%. P(VDF-TrFE)/graphene flower-based flexible humidity sensor exhibited high sensitivity with an average change of capacitance as 0.0558 pF/RH%. Stability of obtained results was monitored for two weeks without any considerable change in the original values, signifying its high reliability. Various chemical, morphological, and electrical characterizations were performed to comprehensively study the humidity-sensing behavior of this advanced composite. The fabricated sensor was successfully used for the applications of health monitoring and measuring the water content in the environment.

Resistive Switching in All-Printed, Flexible and Hybrid MoS2-PVA Nanocomposite based Memristive Device Fabricated by Reverse Offset.

Owing to the increasing interest in the nonvolatile memory devices, resistive switching based on hybrid nanocomposite of a 2D material, molybdenum disulphide (MoS2) and polyvinyl alcohol (PVA) is explored in this work. As a proof of concept, we have demonstrated the fabrication of a memory device with the configuration of PET/Ag/MoS2-PVA/Ag via an all printed, hybrid, and state of the art fabrication approach. Bottom Ag electrodes, active layer of hybrid MoS2-PVA nanocomposite and top Ag electrode are deposited by reverse offset, electrohydrodynamic (EHD) atomization and electrohydrodynamic (EHD) patterning respectively. The fabricated device displayed characteristic bistable, nonvolatile and rewritable resistive switching behavior at a low operating voltage. A decent off/on ratio, high retention time, and large endurance of 1.28 × 102, 105 sec and 1000 voltage sweeps were recorded respectively. Double logarithmic curve satisfy the trap controlled space charge limited current (TCSCLC) model in high resistance state (HRS) and ohmic model in low resistance state (LRS). Bendability test at various bending diameters (50-2 mm) for 1500 cycles was carried out to show the mechanical robustness of fabricated device.