Real-time Activity Monitoring Research Articles

NMR spectroscopy for metabolomics in the living system: recent progress and future challenges.

Metabolism is a fundamental process that underlies human health and diseases. Nuclear magnetic resonance (NMR) techniques offer a powerful approach to identify metabolic processes and track the flux of metabolites at the molecular level in living systems. An in vitro study through in-cell NMR tracks metabolites in real time and investigates protein structures and dynamics in a state close to their most natural environment. This technique characterizes metabolites and proteins involved in metabolic pathways in prokaryotic and eukaryotic cells. In vivo magnetic resonance spectroscopy (MRS) enables whole-organism metabolic monitoring by visualizing the spatial distribution of metabolites and targeted proteins. One limitation of these NMR techniques is the sensitivity, for which a possible improved approach is through isotopic enrichment or hyperpolarization methods, including dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP). DNP involves the transfer of high polarization from electronic spins of radicals to surrounding nuclear spins for signal enhancements, allowing the detection of low-abundance metabolites and real-time monitoring of metabolic activities. PHIP enables the transfer of nuclear spin polarization from parahydrogen to other nuclei for signal enhancements, particularly in proton NMR, and has been applied in studies of enzymatic reactions and cell signaling. This review provides an overview of in-cell NMR, in vivo MRS, and hyperpolarization techniques, highlighting their applications in metabolic studies and discussing challenges and future perspectives.

Antibacterial highly sensitive eco-friendly wearable piezoresistive sensor for monitoring multiple physiological parameters

Recent progress in wearable biomedical devices has made real-time monitoring possible through non-invasive wearable strain sensors, which can transform physical or biological signals into electrical responses. This work has fabricated multifunctional wearable strain sensors by coating composites (SiE-µG) of electrochemically exfoliated micro-sized multi-layer graphene flakes (µG) and Silicone elastomer (SiE) onto stretchable textile-based orthopedic bandage having ZnO adhesive (SiE-µG@Bandage). The composite coated textile sensors exhibited a remarkable sensitivity of 18330, large stretchability of 35%, superior mechanical durability of 50000 cycles, minute detection limit of 0.04% strain, and fast response time of 400 and recovery time 900 ms. The SiE-µG@Bandage also showed antibacterial properties against Escherichia coli (E. coli) bacteria. Additionally, zinc oxide-based skin-friendly and non-toxic adhesive on the backside of the bandage allowed stable and conformal attachment with the skin. Owing to the above merits, the sensors have shown applicability in real-time monitoring of various physical activities, physiological signals, joint movements, yoga postures, and meditation. Furthermore, the relevance of the sensors in the man-machine interaction has been demonstrated via real-time monitoring of traffic signals by finger movements. Moreover, the exceptional performance and specific features of the SiE-µG@Bandage sensors have enabled their application as electronics skins in health care and preventive care.

Feasibility of a remote heart rate variability biofeedback intervention for reducing anxiety in cardiac arrest survivors: A pilot trial

BackgroundHeart rate variability biofeedback (HRVB) is a promising non-pharmacologic approach for reducing anxiety. This intervention's feasibility needs testing in psychologically distressed cardiac patients for whom heart-related anxiety is a core concern. To enhance scalability and convenience, remote delivery of HRVB also needs to be assessed. Accordingly, we evaluated the feasibility of remote HRVB in survivors of cardiac arrest (CA) with elevated CA-related psychological distress. MethodsThe intervention was comprised of daily sessions of diaphragmatic paced breathing and real-time monitoring of cardiac activity guided by a smartphone app and heart rate monitor. This single-arm feasibility trial assessed the percentage of eligible contacted patients who consented and engaged in the study and the self-reported acceptability, feasibility, appropriateness, and usability of the intervention. Exploratory analyses assessed pre-to-post changes in trait anxiety, negative affect, cardiac-related interoceptive fear, and resting-state HRV. ResultsOf 12 eligible CA survivors contacted, 10 enrolled. All 10 patients completed the virtual study visits and the majority (>50 %) of prescribed training sessions. Ninety percent reported good scores for intervention acceptability and feasibility, and 80 % reported good scores for its appropriateness and usability for reducing fear. Trait anxiety decreased significantly pre-to-post intervention. There were no changes in negative affect, interoceptive fear, or resting state HRV. ConclusionA remotely delivered HRVB intervention was acceptable, feasible, and useable for cardiac patients with CA-related psychological distress. A phase 2 randomized controlled trial evaluating the efficacy of HRVB on cardiac patients’ psychological distress, health behaviors, and autonomic dysfunction may be warranted.

Stretchable, Self-Rolled, Microfluidic Electronics Enable Conformable Neural Interfaces of Brain and Vagus Neuromodulation.

Implantable neuroelectronic interfaces have gained significant importance in long-term brain-computer interfacing and neuroscience therapy. However, due to the mechanical and geometrical mismatches between the electrode-nerve interfaces, personalized and compatible neural interfaces remain serious issues for peripheral neuromodulation. This study introduces the stretchable and flexible electronics class as a self-rolled neural interface for neurological diagnosis and modulation. These stretchable electronics are made from liquid metal-polymer conductors with a high resolution of 30 μm using microfluidic printing technology. They exhibit high conformability and stretchability (over 600% strain) during body movements and have good biocompatibility during long-term implantation (over 8 weeks). These stretchable electronics offer real-time monitoring of epileptiform activities with excellent conformability to soft brain tissue. The study also develops self-rolled microfluidic electrodes that tightly wind the deforming nerves with minimal constraint (160 μm in diameter). The in vivo signal recording of the vagus and sciatic nerve demonstrates the potential of self-rolled cuff electrodes for sciatic and vagus neural modulation by recording action potential and reducing heart rate. The findings of this study suggest that the robust, easy-to-use self-rolled microfluidic electrodes may provide useful tools for compatible neuroelectronics and neural modulation.

Real-Time Monitoring of RAS Activity Using In Vitro and In-Cell NMR Spectroscopy.

The activation level of RAS can be determined by GTP hydrolysis rate (khy) and GDP-GTP exchange rates (kex). Either impaired GTP hydrolysis or enhanced GDP-GTP exchange causes the aberrant activation of RAS in oncogenic mutants. Therefore, it is important to quantify the khy and kex for understanding the mechanisms of RAS oncogenesis and drug development. Conventional methods have individually measured the kex and khy of RAS. However, within the intracellular environment, GTP hydrolysis and GDP-GTP exchange reactions occur simultaneously under conditions where GTP concentration is kept constant. In addition, the intracellular activity of RAS is influenced by endogenous regulatory proteins, such as RAS GTPase activating proteins (GAPs) and the guanine-nucleotide exchange factors (GEFs). Here, we describe the in vitro and in-cell NMR methods to estimate the khy and kex simultaneously by measuring the time-dependent changes of the fraction of GTP-bound ratio under the condition of constant GTP concentration.

A stand-alone proximity-based gaming wearable for remote physical activity monitoring

Abstract The Internet of Things (IoT) and wearable computing are crucial elements of modern information systems and applications in which advanced features for user interactivity and monitoring are required. However, in the fields of pervasive gaming, IoT has had limited real-world applications. In this work, we present a prototype of a wearable platform for pervasive games that combines IoT with wearable computing to enable the real-time monitoring of physical activity. The main objective of the solution is to promote the utilization of gamification techniques to enhance the physical activity of users through challenges and quests. This aims to create a symbolic link between the virtual gameplay and the real-world environment without the requirement of a smartphone. With the integration of sensors and wearable devices by design, the platform has the capability of real-time monitoring the users’ physical activity during the game. The system performance results highlight the efficiency and attractiveness of the wearable platform for gamifying physical activity.

The Prospect of Using Artificial Intelligence in TNI Ship Information Systems as a Manifestation of a Resilient Maritime Defense Industry

This research investigates the prospects of using Artificial Intelligence (AI) in the Indonesian Navy's ship information system as a crucial step in developing a robust and innovative maritime defense industry. The primary focus is on the application of AI technology in the ship information system, analyzing various aspects, including the potential implementation of AI in monitoring and analyzing maritime waters, technical and security challenges that may arise, expected benefits, and the strategic impact of AI implementation in Indonesia's maritime defense industry. The research method employs the Systematic Literature Review (SLR) method, providing a systematic and comprehensive approach to collecting, evaluating, and analyzing relevant literature in a specific field. This study involves literature searches using keywords such as artificial intelligence, information systems, maritime defense industry, Indonesian defense, and Indonesian Navy ships from 2011 to 2023 in various sources such as scholarly journals, conferences, and online databases. The research findings indicate that the use of artificial intelligence in the Indonesian Navy's ship information system has significant potential to improve maritime monitoring, threat detection, operational efficiency, and international collaboration. The integration of AI with advanced sensors such as radar, sonar, and thermal cameras enables more accurate real-time monitoring of activities in maritime waters. Higher accuracy in monitoring and threat detection also contributes to increased situational awareness and smarter decision-making by operational leaders in the Indonesian Navy. Despite the substantial benefits, AI implementation faces several challenges, including initial investment costs, infrastructure availability, personnel training, data security, ethical regulations, dependence on foreign technology, integration and compatibility issues, AI technology reliability, cultural and organizational changes, and long-term benefits. To address these challenges, it is recommended that the government allocates budgets wisely, develops adequate technological infrastructure, provides personnel training, and formulates ethical regulations. Strengthening independence in the development of domestic AI technology is also crucial.

Smart Lithium-Ion Battery Monitoring in Electric Vehicles: An AI-Empowered Digital Twin Approach

This paper presents a transformative methodology that harnesses the power of digital twin (DT) technology for the advanced condition monitoring of lithium-ion batteries (LIBs) in electric vehicles (EVs). In contrast to conventional solutions, our approach eliminates the need to calibrate sensors or add additional hardware circuits. The digital replica works seamlessly alongside the embedded battery management system (BMS) in an EV, delivering real-time signals for monitoring. Our system is a significant step forward in ensuring the efficiency and sustainability of EVs, which play an essential role in reducing carbon emissions. A core innovation lies in the integration of the digital twin into the battery monitoring process, reshaping the landscape of energy storage and alternative power sources such as lithium-ion batteries. Our comprehensive system leverages a cloud-based IoT network and combines both physical and digital components to provide a holistic solution. The physical side encompasses offline modeling, where a long short-term memory (LSTM) algorithm trained with various learning rates (LRs) and optimized by three types of optimizers ensures precise state-of-charge (SOC) predictions. On the digital side, the digital twin takes center stage, enabling the real-time monitoring and prediction of battery activity. A particularly innovative aspect of our approach is the utilization of a time-series generative adversarial network (TS-GAN) to generate synthetic data that seamlessly complement the monitoring process. This pioneering use of a TS-GAN offers an effective solution to the challenge of limited real-time data availability, thus enhancing the system’s predictive capabilities. By seamlessly integrating these physical and digital elements, our system enables the precise analysis and prediction of battery behavior. This innovation—particularly the application of a TS-GAN for data generation—significantly contributes to optimizing battery performance, enhancing safety, and extending the longevity of lithium-ion batteries in EVs. Furthermore, the model developed in this research serves as a benchmark for future digital energy storage in lithium-ion batteries and comprehensive energy utilization. According to statistical tests, the model has a high level of precision. Its exceptional safety performance and reduced energy consumption offer promising prospects for sustainable and efficient energy solutions. This paper signifies a pivotal step towards realizing a cleaner and more sustainable future through advanced EV battery management.

Real-time Interpretation of EEG Signals for Consciousness State Assessment

Assessing the level of consciousness is critical in clinical practice, especially for patients with traumatic brain injuriesor those in a coma or vegetative state. Traditional methods like the Glasgow Coma Scale have limitations, such asinter-observer variability and low sensitivity. In recent years, electroencephalography (EEG) has emerged as a promisingapproach for assessing consciousness, offering non-invasive, real-time monitoring of brain activity. In this study, we propose a real-time analysis system for assessing consciousness levels using a portable EEG device. Our system analyzes EEG signals and provides valuable insights into consciousness levels, enabling prompt clinical interventions. The real-time nature of our system allows for continuous monitoring and immediate assessment of consciousness levels. Compared to traditional methods, our system offers advantages in terms of real-time functionality, providing a comprehensive evaluation of consciousness. Through extensive experiments using real patient data, our systemdemonstrates its value as a valuable tool for assessing consciousness levels in clinical practice. It offers healthcare professionals an efficient and reliable method for evaluating consciousness.

Multiobjective optimization-based decision support for building digital twin maturity measurement

The digital twin (DT) represents a powerful tool for advancing construction industry to provide a cyber–physical integration that enables real-time monitoring of assets and activities and facilitates decision-making. Due to the inherent characteristics of the construction industry and the diverse possibilities with DT, proliferation of building digital twin (BDT) necessitates a comprehensive comprehension of its evolution and the creation of roadmaps. This paper aims to contribute to the formalization and standardization of BDT. It designs a novel assessment framework for the overall maturity measurement of existing BDT projects. The developed BDT maturity model incorporates a collective opinion generation paradigm based on a fairness-aware multiobjective optimization model to provide an expert-based evaluation system for evaluating the maturity of BDT projects. The effectiveness and feasibility of the proposed framework have been validated through a case study of an experimental BDT initiative. This paper establishes a generalizable framework for BDT maturity assessment that can offer insights into BDT maturity standards to construction practitioners to create effective strategies for the diffusion, development, and maturation of BDT.

SENSING MECHANISM AND APPLICATION OF MECHANICAL STRAIN SENSOR: A MINI-REVIEW

This study reviews the potential of flexible strain sensors based on nanomaterials such as carbon nanotubes (CNTs), graphene, and metal nanowires (NWs). These nanomaterials have excellent flexibility, conductivity, and mechanical properties, which enable them to be integrated into clothing or attached to the skin for the real-time monitoring of various activities. However, the main challenge is balancing high stretchability and sensitivity. This paper explains the basic concept of strain sensors that can convert mechanical deformation into electrical signals. Moreover, this paper focuses on simple, flexible, and stretchable resistive and capacitive sensors. It also discusses the important factors in choosing materials and fabrication methods, emphasizing the crucial role of suitable polymers in high-performance strain sensing. This study reviews the fabrication processes, mechanisms, performance, and applications of stretchable strain sensors in detail. It analyzes key aspects, such as sensitivity, stretchability, linearity, response time, and durability. This review provides useful insights into the current status and prospects of stretchable strain sensors in wearable technology and human–machine interfaces.

Hydrophobic deep eutectic solvent-based eutectogels for underwater sensing

Eutectogels derived from deep eutectic solvents (DESs) exhibit great potential for the fabrication of flexible sensors. However, the hygroscopicity of eutectogels hinders their applications in underwater sensing. In this work, a hydrophobic eutectogel with exceptional long-term underwater stability is produced through one-step polymerization of lauryl methacrylate and glycidyl methacrylate in a hydrophobic DES. The hydrophobic gel network and hydrophobic DES fulfill the eutectogel with outstanding water resistance (water contact angle > 110°) and excellent mechanical properties in an aqueous environment, thus leading to extraordinary durability (over 1000 testing cycles). Additionally, based on this eutectogel, underwater strain and pressure sensors with high sensitivity, rapid responsiveness, and superior durability were fabricated for accurate real-time monitoring of human activity. Furthermore, it has been demonstrated that the eutectogel sensor can transmit information through Morse code, performing as a wearable underwater communicator. This research provides an exemplary way for a demonstration method of hydrophobic eutectogel for durable underwater applications.

Discovery of Potential Antituberculosis Agents Targeted Methionine Aminopeptidase 1 of Mycobacterium tuberculosis by the Developed Fluorescent Probe.

Tuberculosis (TB) is a chronic systemic infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis). Methionine aminopeptidase 1 (MtMET-AP1) is a hydrolase that mediates the necessary post-translational N-terminal methionine excision (NME) of peptides during protein synthesis, which is necessary for bacterial proliferation and is a potential target for the treatment of tuberculosis. Based on the functional characteristics of MtMET-AP1, we developed an enzymatic activated near-infrared fluorescent probe DDAN-MT for rapid, highly selective, and real-time monitoring of endogenous MtMET-AP1 activity in M. tuberculosis. Using the probe DDAN-MT, a visually high-throughput screening technique was established, which obtained three potential inhibitors (GSK-J4 hydrochchloride, JX06, and lavendustin C) against MtMET-AP1 from a 2560 compounds library. More importantly, these inhibitors could inhibit the growth of M. tuberculosis H37Ra especially (MICs < 5 μM), with low toxicities on intestinal bacteria strains and human cells. Therefore, the visual sensing of MtMET-AP1 was successfully performed by DDAN-MT, and MtMET-AP1 inhibitors were discovered as potential antituberculosis agents.

Real-Time Electrochemical Monitoring of the Progress of Sulfate Reducing Bacterially Induced Corrosion of Carbon Steel

Microbiologically influenced corrosion (MIC) is a widespread problem in the oil and gas industry, and sulfate reducing bacteria (SRB) cause the most aggressive kind of corrosion. A sulfate-reducing enrichment culture was obtained from a natural gas transmission line, and incubated in split chamber-zero resistance ammetry incubations. Here, carbon steel electrodes were placed in a synthetic gas field brine in opposing chambers that were connected with a salt bridge. To mimic the heterogeneous metal coverage of a metal surface that causes MIC, one chamber was experimentally manipulated with the addition of the SRB culture, while the other was uninoculated. Initial measurement of positive current between the electrodes in incubations with an organic electron donor (lactate) indicated a period of priming of the metal surface by planktonic SRB, before the current transitioned to negative, indicating that the cathodic corrosive reaction was occurring on the electrode exposed to SRB activities. This negative current is consistent with hypothesized mechanisms of SRB-induced corrosion and was observed in lactate-free incubations and in uninoculated incubations amended with sulfide. These observations, combined with SRB metabolic patterns and mass loss analyses indicate the dynamic nature of SRB-mediated corrosion and illustrate the utility of real-time monitoring of MIC activities.

Novel flexible hydrogels based on carboxymethyl guar gum and polyacrylic acid for ultra-highly sensitive and reliable strain and pressure sensors

To realize on stable and real-time monitoring of human activities, novel hydrogels using polyacrylic acid (PAA) and carboxymethyl guar gum (CMGG) were fabricated as wearable and flexible strain or pressure sensors in the presence of lignosulfonate (LS) and Al3+. Based on the co-existence of metal coordination bonds, hydrogen bonds and ionic interaction in this system, the obtained hydrogels exhibited desirable mechanical properties with good self-recovery ability. The hydrogels displayed good self-adhesion behavior and an ultra-high tensile sensitivity (gauge factor (GF) = 24.30), therefore, they could precisely detect human joints movements such as elbow, wrist, and finger bending as well as tiny movements and external stimuli such as swallowing, smile, frown, pulse, speaking, writing, and even the falling of different liquid drops. Additionally, the hydrogels showed excellent self-healing ability with the healing efficiency as high as 100 % after 30 h. Most importantly, the healed hydrogel could perform the same sensing performance as before. Based on these distinguished characteristics, this hydrogel represents great potentials in wearable and flexible sensors for long-term and stable health monitoring application.

Biomimetic scale-like polysaccharide-based highly-sensitive piezoresistive sensor with “shell-core” nanostructure

A nanofiber membrane is an ideal carrier for constructing a typical three-dimensional conductive network. Inspired by the biomimetic scale-like nanostructure, polysaccharide-based piezoresistive material with outstanding Joule heating performance, thermal efficiency, and high conductivity is developed, presenting a potential indicator material with the color shifting function for intelligent skin or soft robots in practical applications. The stable core-shell structure due to the in-situ polymerization of polypyrrole (PPy) on the electrospun nanofiber endows the piezoresistive sensor (s-PGG@PPy) with a broad pressure range (0.13–128.46 kPa), high sensitivity (52.42 kPa−1) and fast response time (26 ms). The free motion of π electrons along the nanofibers between carbon atoms perfectly made it an attractive candidate for real-time monitoring of human activities, including bending of fingers, wrist, knee, and facial expression. In addition, designing s-PGG@PPy is to be connected in parallel and composed of an indication function glove, which shows different brightness with finger pressure. Consequently, the reported piezoresistive sensor represents a potential for wearable bioelectronics.

Satellite derived SO2 emissions from the relatively low-intensity, effusive 2021 eruption of Fagradalsfjall, Iceland

In March 2021 an effusive eruption began at the Fagradalsfjall volcanic system in Iceland, ending nearly 800 years of dormancy on the Reykjanes peninsula. The eruption produced lava flows and moderate gas emissions and, although it did not cause significant disruption, highlighted the need for near real-time monitoring of volcanic activity on the peninsula for future eruptions. The activity passed through several phases, each characterised by a different eruption style, providing a rich testbed for monitoring methodologies.We present measurements of the volcanic sulphur dioxide (SO2) emission rate and injection altitude throughout the eruption, generated by combining satellite SO2 imagery from TROPOMI with PlumeTraj, a back-trajectory analysis toolkit. We compare the results with ground-based measurements of the emission rate and plume altitude, finding excellent agreement in the plume altitude. Reasonable agreement was also found between the measured emission rates, with the best match for stronger and more continuous emissions. This demonstrates the ability for PlumeTraj to monitor SO2 emissions from future effusive eruptions, while highlighting the need for care when analysing results from low altitude plumes or during periods of high cloud cover.

Assessing Consciousness through Neurofeedback and Neuromodulation: Possibilities and Challenges.

Neurofeedback is a non-invasive therapeutic approach that has gained traction in recent years, showing promising results for various neurological and psychiatric conditions. It involves real-time monitoring of brain activity, allowing individuals to gain control over their own brainwaves and improve cognitive performance or alleviate symptoms. The use of electroencephalography (EEG), such as brain-computer interface (BCI), transcranial direct current stimulation (tDCS), and transcranial magnetic stimulation (TMS), has been instrumental in developing neurofeedback techniques. However, the application of these tools in patients with disorders of consciousness (DoC) presents unique challenges. In this narrative review, we explore the use of neurofeedback in treating patients with DoC. More specifically, we discuss the advantages and challenges of using tools such as EEG neurofeedback, tDCS, TMS, and BCI for these conditions. Ultimately, we hope to provide the neuroscientific community with a comprehensive overview of neurofeedback and emphasize its potential therapeutic applications in severe cases of impaired consciousness levels.

Recovery of protein synthesis to assay DNA repair activity in transcribed genes in living cells and tissues.

Transcription-coupled nucleotide excision repair (TC-NER) is an important DNA repair mechanism that protects against the negative effects of transcription-blocking DNA lesions. Hereditary TC-NER deficiencies cause pleiotropic and often severe neurodegenerative and progeroid symptoms. While multiple assays have been developed to determine TC-NER activity for clinical and research purposes, monitoring TC-NER is hampered by the low frequency of repair events occurring in transcribed DNA. 'Recovery of RNA Synthesis' is widely used as indirect TC-NER assay based on the notion that lesion-blocked transcription only resumes after successful TC-NER. Here, we show that measuring novel synthesis of a protein after its compound-induced degradation prior to DNA damage induction is an equally effective but more versatile manner to indirectly monitor DNA repair activity in transcribed genes. This 'Recovery of Protein Synthesis' (RPS) assay can be adapted to various degradable proteins and readouts, including imaging and immunoblotting. Moreover, RPS allows real-time monitoring of TC-NER activity in various living cells types and even in differentiated tissues of living organisms. To illustrate its utility, we show that DNA repair in transcribed genes declines in aging muscle tissue of C. elegans. Therefore, the RPS assay constitutes an important novel clinical and research tool to investigate transcription-coupled DNA repair.

Three-Dimensional Printing Enabled Droplet Microfluidic Device for Real-Time Monitoring of Single-Cell Viability and Blebbing Activity.

Droplet-based microfluidics with the characteristics of high throughput, low sample consumption, increasing reaction speed, and homogeneous volume control have been demonstrated as a useful platform for biomedical research and applications. The traditional fabrication methods of droplet microfluidics largely rely on expensive instruments, sophisticated operations, and even the requirement of an ultraclean room. In this manuscript, we present a 3D printing-based droplet microfluidic system with a specifically designed microstructure for droplet generation aimed at developing a more accessible and cost-effective method. The performance of droplet generation and the encapsulation capacity of the setup were examined. The device was further applied to measure the variation in cell viability over time and monitor the cell's blebbing activity to investigate its potential ability and feasibility for single-cell analysis. The result demonstrated that the produced droplets remained stable enough to enable the long-time detection of cell viability. Additionally, cell membrane protrusions featuring the life cycle of bleb initiation, expansion, and retraction can be well-observed. Three-dimensional printing-based droplet microfluidics benefit from the ease of manufacture, which is expected to simplify the fabrication of microfluidics and expand the application of the droplet approach in biomedical fields.