Multi channel monitor

Hand function rehabilitation training typically requires monitoring the activation status of muscles directly related to hand function. However, due to factors such as the small surface area for hand-back electrode placement and significant skin deformation, the continuous real-time monitoring of high-quality surface electromyographic (sEMG) signals on the hand-back skin still poses significant challenges. We report a stretchable, flexible, breathable, and self-adhesive epidermal sEMG sensor system. The optimized serpentine structure exhibits a sufficient stretchability and filling ratio, enabling the high-quality monitoring of signals...

Paper-based analytical devices (PADs) integrated with smartphones have shown great potential in various fields, but they also face challenges such as single signal reading, complex data processing and significant environmental impacting. In this study, a colorimetric PAD platform has been proposed using bimetallic nickel-cobalt selenides as highly active peroxidase mimic, smartphone with 3D-printing dark-cavity as a portable detector and an artificial neural network (ANN) model as multi-signal processing tool...

The current challenges in Synthetic Aperture Radar (SAR) ship detection tasks revolve around handling significant variations in target sizes and managing high computational expenses, which hinder practical deployment on satellite or mobile airborne platforms. In response to these challenges, this research presents YOLOv7-LDS, a lightweight yet highly accurate SAR ship detection model built upon the YOLOv7 framework. In the core of YOLOv7-LDS's architecture, we introduce a streamlined feature extraction network that strikes a delicate balance between detection precision and computational efficiency...

Ship fire may result in significant damage to its structure and large economic loss. Hence, the prompt identification of fires is essential in order to provide prompt reactions and effective mitigation strategies. However, conventional detection systems exhibit limited efficacy and accuracy in detecting targets, which has been mostly attributed to limitations imposed by distance constraints and the motion of ships. Although the development of deep learning algorithms provides a potential solution, the computational complexity of ship fire detection algorithm pose significant challenges...

Fetal electrocardiogram (fECG) monitoring is crucial for assessing fetal condition during pregnancy. However, current fECG extraction algorithms are not suitable for wearable devices due to their high computational cost and multi-channel signal requirement. The paper introduces a novel and efficient algorithm called Adaptive Improved Permutation Entropy (AIPE), which can extract fetal QRS from a single-channel abdominal ECG (aECG). The proposed algorithm is robust and computationally efficient, making it a reliable and effective solution for wearable devices...

Single-channel continuous wave (CW) radar is widely used and has gained popularity due to its simple architecture despite its inability to measure the range and angular location of the target. Its popularity arises in the industry due to the simplicity of the required components, the low demands on the sampling rate, and their low costs. Through-the-wall life signs detection using microwave Doppler Radar is an active area of research and investigation. Most of the work in the literature focused on utilizing multi-channel frequency modulated continuous wave (FMCW), CW, and ultra-wideband (UWB) radar for their capability of range and direction of arrival (DOA) estimation...

Under-oil open microfluidic system, utilizing liquid-liquid boundaries for confinements, offers inherent advantages including clogging-free flow channels, flexible access to samples, and adjustable gas permeation, making it well-suited for studying multi-phase chemical reactions that are challenging for closed microfluidics. However, reports on the novel system have primarily focused on device fabrication and functionality demonstrations within biology, leaving their application in broader chemical analysis underexplored...

Effective condition monitoring can improve the reliability of the turbine and reduce its downtime. However, due to the complexity of the operating conditions, the monitoring data is always mixed with poor-quality data. Poor-quality data mixed in monitoring tasks disrupts long-term dependency on data, which challenges traditional condition monitoring methods to work. To solve it, a joint reparameterization feature pyramid network (JRFPN) is proposed. Firstly, three different reparameterization tricks are designed to reform temporal information and exchange cross-temporal information, to alleviate the damage of long-term dependency...

Portable, low-cost, and accurate monitoring of hazardous mono-aromatic pollutants, such as phenol or benzene group of compounds in water is a challenging task due to the lack of suitable detectable functional groups and complex matrix of environmental samples. Here, we use a series of protein-based biosensing recognition scaffolds to enable specific detection of several mono-aromatic classes of xenobiotics. The biosensor is tuned to perform in intricate environmental conditions and is interfaced with an in-house manufactured, multi-channel device (AroTrack) capable of direct and sensitive detection of several of these aromatic contaminants, such as phenol, benzene, and 2,3-dimethylphenol (2,3-DMP) in the low ppb range (10-200 ppb)...

In recent years, the nitrogen-vacancy (NV) center in diamonds has been demonstrated to be a high-performance multiphysics sensor, where a lock-in amplifier (LIA) is often adopted to monitor photoluminescence changes around the resonance. It is rather complex when multiple resonant points are utilized to realize a vector or temperature-magnetic joint sensing. In this article, we present a novel scheme to realize multipoint lock-in detection with only a single-channel device. This method is based on a direct digital synthesizer (DDS) and frequency-shift keying (FSK) technique, which is capable of freely hopping frequencies with a maximum of 1...

As an important endogenous gasotransmitter, hydrogen sulfide (H2 S) plays a critical role in various physiological functions and has been regarded as a biomarker of cancer due to its overexpression in cancer cells. In addition, the early stages of cancer are often accompanied by abnormalities in the intracellular microenvironments, and distinguishing between cancer cell/tissues and normal cell/tissues is of great significance to the accuracy of cancer diagnosis. However, deep insights into the simultaneous detection of H2 S and viscosity/polarity variations in cancer cells/tissues are rarely reported...

The Muriganga River, also known as channel creek, underwent morphological changes often since it is an alluvial as well as a tidal river. The present study analyses the morphological changes in the Muriganga River and its islands with the help of the Remote Sensing and Geographical Information System (GIS) and digital shoreline analysis tool (DSAS 5.0). Moreover, the computation of morphological changes was also performed on two islands, i.e. Sagar and Ghoramara, which are situated just outside the river reach...

In-ear acquisition of physiological signals, such as electromyography (EMG), electrooculography (EOG), electroencephalography (EEG), and electrocardiography (ECG), is a promising approach to mobile health (mHealth) due to its non-invasive and user-friendly nature. By providing a convenient and comfortable means of physiological signal monitoring, in-ear signal acquisition could potentially increase patient compliance and engagement with mHealth applications. The development of reliable and comfortable soft dry in-ear electrode systems could, therefore, have significant implications for both mHealth and human-machine interface (HMI) applications...

Automatic seizure detection plays a key role in assisting clinicians for rapid diagnosis and treatment of epilepsy. In view of the parallelism of temporal convolutional network (TCN) and the capability of bidirectional long short-term memory (BiLSTM) in mining the long-range dependency of multi-channel time-series, we propose an automatic seizure detection method with a novel end-to-end TCN-BiLSTM model in this work. First, raw EEG is filtered with a 0.5-45 Hz band-pass filter, and the filtered data are input into the proposed TCN-BiLSTM network for feature extraction and classification...

Dapoxetine (DPX) belongs to the selective serotonin reuptake inhibitor (SSRI) class and functions by blocking the serotonin transporter and increasing serotonin activity, thereby delaying ejaculation. Therefore, monitoring of the concentration of DPX in human biofluids is important for clinicians. In this study, application of silver nanoparticles with the morphology of prisms (AgNPrs) for the sensitive measurement of DPX using colorimetric chemosensing and the spectrophotometric method was investigated. Also, DPX was determined in real samples using the spectrophotometry method...

The global production and consumption of plastics, as well as their deposition in the environment, are experiencing exponential growth. In addition, mismanaged plastic waste (PW) losses into drainage channels are a growing source of microplastic (MP) pollution concern. However, the complete understanding of their environmental implications throughout their life cycle is yet to be fully understood. Determining the potential extent to which MPs contribute to overall ecotoxicity is possible through the monitoring of PW release and MP removal during remediation...

In the fields of industrial production or safety monitoring, wireless sensor networks are often content with unreliable and time-varying channels that are susceptible to interference. Consequently, ensuring both transmission reliability and data accuracy has garnered substantial attention in recent years. Although multipath routing-based schemes can provide transmission reliability for wireless sensor networks, achieving high data accuracy simultaneously remains challenging. To address this issue, an Energy-efficient Multipath Routing algorithm balancing data Accuracy and transmission Reliability (EMRAR) is proposed to balance the reliability and accuracy of data transmission...

Infantile spasms (IS) is a neurological disorder causing mental and/or developmental retardation in many infants. Hypsarrhythmia is a typical symptom in the electroencephalography (EEG) signals with IS. Long-term EEG/video monitoring is most frequently employed in clinical practice for IS diagnosis, from which manual screening of hypsarrhythmia is time consuming and lack of sufficient reliability. This study aims to identify potential biomarkers for automatic IS diagnosis by quantitative analysis of the EEG signals...

Zinc ferrite (ZnFe2O4) nanoparticles were synthesised via solution combustion method using urea as a fuel. The synthesised samples were characterised with various techniques. The cubic structure with Fd-3 m space group is confirmed by Powder X-ray Diffraction and Bragg's reflection. The crystallite size estimated from Scherrer's method was found to be 40 nm. The agglomerated irregular shape and sized surface morphology was confirmed by Scanning Electron Microscopy image. The direct energy band gap determined from Wood and Tauc's relation was found to be 5...

Visual object detection has emerged as a critical technology for Unmanned Arial Vehicle (UAV) use due to advances in computer vision. New developments in fields like communication technology and the UAV needs to be able to act autonomously by gathering data and then making choices. These tendencies have brought us to cutting-edge levels of health care, transportation, energy, monitoring, and security for visual image detection and manufacturing endeavors. These include coordination in communication via IoT, sustainability of IoT network, and optimization challenges in path planning...