Portable Technology Research Articles

Space exploration as a catalyst for medical innovations.

Aerospace research has a long history of developing technologies with industry-changing applications and recent history is no exception. The expansion of commercial spaceflight and the upcoming exploration-class missions to the Moon and Mars are expected to accelerate this process even more. The resulting portable, wearable, contactless, and regenerable medical technologies are not only the future of healthcare in deep space but also the future of healthcare here on Earth. These multi-dimensional and integrative technologies are non-invasive, easily-deployable, low-footprint devices that have the ability to facilitate rapid detection, diagnosis, monitoring, and treatment of a variety of conditions, and to provide decision-making and performance support. Therefore, they are primed for applications in low-resource and remote environments, facilitating the extension of quality care delivery to all patients in all communities and empowering non-specialists to intervene early and safely in order to optimize patient-centered outcomes. Additionally, these technologies have the potential to advance care delivery in tertiary care centers by improving transitions of care, providing holistic patient data, and supporting clinician wellness and performance. The requirements of space exploration have created a number of paradigm-altering medical technologies that are primed to revitalize and elevate our standard of care here on Earth.

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain.

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

Gaps and future directions in research on health effects of airpollution.

Despite progress in many countries, air pollution, and especially fine particulate matter air pollution (PM2.5) remains a global health threat: over 6 million premature cardiovascular and respiratory deaths/yr. have been attributed to household and outdoor air pollution. In this viewpoint, we identify present gaps in air pollution monitoring andregulation, and how they could be strengthened in future mitigation policies to more optimally reduce health impacts. We conclude that there is a need to move beyond simply regulating PM2.5 particulate matter mass concentrations at central site stations. A greater emphasis is needed on: new portable and affordable technologies to measure personal exposures to particle mass; the consideration of a submicron (PM1) mass air quality standard; and further evaluations of effects by particle composition and source. We emphasize the need to enable further studies on exposure-health relationships in underserved populations that are disproportionately impacted by air pollution, but not sufficiently represented in current studies.

Hip Joint Angles and Moments during Stair Ascent Using Neural Networks and Wearable Sensors.

End-stage hip joint osteoarthritis treatment, known as total hip arthroplasty (THA), improves satisfaction, life quality, and activities of daily living (ADL) function. Postoperatively, evaluating how patients move (i.e., their kinematics/kinetics) during ADL often requires visits to clinics or specialized biomechanics laboratories. Prior work in our lab and others have leveraged wearables and machine learning approaches such as artificial neural networks (ANNs) to quantify hip angles/moments during simple ADL such as walking. Although level-ground ambulation is necessary for patient satisfaction and post-THA function, other tasks such as stair ascent may be more critical for improvement. This study utilized wearable sensors/ANNs to quantify sagittal/frontal plane angles and moments of the hip joint during stair ascent from 17 healthy subjects. Shin/thigh-mounted inertial measurement units and force insole data were inputted to an ANN (2 hidden layers, 10 total nodes). These results were compared to gold-standard optical motion capture and force-measuring insoles. The wearable-ANN approach performed well, achieving rRMSE = 17.7% and R2 = 0.77 (sagittal angle/moment: rRMSE = 17.7 ± 1.2%/14.1 ± 0.80%, R2 = 0.80 ± 0.02/0.77 ± 0.02; frontal angle/moment: rRMSE = 26.4 ± 1.4%/12.7 ± 1.1%, R2 = 0.59 ± 0.02/0.93 ± 0.01). While we only evaluated healthy subjects herein, this approach is simple and human-centered and could provide portable technology for quantifying patient hip biomechanics in future investigations.

GraSSAMS: A new instrument designed for the determination of grain size and shape of sand-gravel-sized sediment

Natural coasts define the interface between land and ocean and constitute a natural barrier to protect humans and infrastructure from waves and storm surges. In the context of global sea level rise and coastal erosion, beaches, especially sand-gravel beaches, can achieve better marine energy reduction at the expense of a smaller spatial buffer zone (i.e., the lateral range of the coastal zone), meaning that nature-based coastal reconstruction and protection are becoming increasingly important. The need for beach replenishment and coastal protection necessitates fast, accurate, portable, and wide-range gravel grain size measurement technology to provide technical support and data for the designing and monitoring of artificial gravel beaches. However, existing grain size analysis methods for gravel-sized sediment are either inefficient (such as sieve analysis) or have a limited range of sizes (such as dynamic image analyzers, up to −3 φ), or have difficulty in eliminating errors caused by gravel overlap (e.g., remote-sensing in situ image analysis). In this study, a Gravel Grain Size and Shape Automatic Measurement System (GraSSAMS) was designed to analyze grain size and shape parameters of gravel-sized sediments. The mean diameters of three types of coins and some Zirconia balls measured using this method were compared with those measured by a vernier caliper. The results show that the GraSSAMS method has good accuracy and yields an acceptable relative error. The grain sizes of 67 field gravel samples were analyzed using both the GraSSAMS method and sieve analysis. The irreducible random error between the two methods is 1.41 φ. In addition, a Camsizer XT and GraSSAMS were used to measure samples with a grain size range of 1∼8 mm (0 φ ∼ -3 φ), respectively. The results of the two methods show good correspondence, with an irreducible random error of 0.31 φ. GraSSAMS was also tested in the field on several gravel beaches. Results revealed that GraSSAMS could complete the surface gravel measurement of a 0.5 m × 0.5 m quadrat within 8 min, and the analysis results avoided the fabric error involved in remote-sensing (photographic) measurement. Based on these various results, we propose that GraSSAMS can be used to analyze the grain size and shape of sand-gravel sediments in the size range of 1∼330 mm (0 φ ∼ -8.37 φ) in a laboratory as well as in the field. Compared with traditional methods, GraSSAM has the advantages of accuracy, high efficiency, and portability and can be used as an alternative for grain size analysis of gravel sediments, with broad application prospects to gravel beaches and fluvial deposits worldwide.

Introducing the New Editorial Team

Introducing the New Editorial Team

Forage calibration transfer from laboratory to portable near infrared spectrometers

Portable near infrared (NIR) spectrometers are now readily available on the market and with their smaller size, weight and cost have provided the opportunity to analyze forages both on farms and directly in the field. As new technologies and new portable NIR instruments become available on the market, calibrations for these instruments become a major constraint due to the costs and time necessary to collect reference data. This study evaluated techniques to transfer calibrations for alfalfa and grass forage samples that were developed for a scanning benchtop monochromator (FOSS 6500, 400–2498 nm, LAB) to a diode array instrument (AuroraNir, 950–1650 nm, DA), a digital light processing instrument (NIR-S-G1, 950–1650 nm, DLP) and a short wavelength instrument (SCiO, 740–1070 nm, SCIO). Alfalfa (N = 612) and grass (N = 516) samples from eight agronomic studies were analyzed by wet chemistry for crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), in-vitro digestibility (IVTD) and NDF digestibility (NDFD) and divided into calibration, test-set, standardization and inoculation/prediction datasets. Different calibration transfer strategies were evaluated: Spectral Bias Correction (SBC), Shenk and Westerhaus algorithm (SW), Piecewise Direct Standardization (PDS), Dynamic Orthogonal Projection (DOP) or creating a new calibration using LAB predictions of the inoculation/prediction dataset as reference values. All computations for trimming, calibration, validation and standardization were developed using R. SBC with inoculation was an effective method to transfer calibrations for DA. Validation errors for DA transferred calibrations were about 15% lower than LAB for alfalfa data but 6% greater for grass data. For SCIO after DOP spectral adjustment, predicting errors were slightly greater than LAB for both data sets, while prediction errors with DLP were two to three times greater than LAB even after inoculation. PDS created spectral artifacts in the spectra of all three portables, which then resulted in large validation errors. Using LAB predictions as reference values was suitable only for DA, while DLP and DA had large prediction errors. This study showed that calibration sharing between a benchtop and portable instruments is challenging, but possible depending on the portable technologies and the transfer method. Spectral bias correction plus inoculation was the best method to transfer multivariate models for the forage components’ prediction from LAB to handhelds, particularly for DA. Application of DOP was beneficial for SCIO to successfully maintain performance of the original calibration, while for DLP the prediction models were not accurate. Additional studies are necessary to verify these transferring techniques can also be applied to fresh forages, allowing an easier and extended implementation of NIR analysis directly in fields.

M-Commerce and its impact on Today's Economy

Mobile commerce, often known as m-commerce, comprises the use of wireless portable devices such as mobile phones and tablets to undertake online commercial transactions such as the purchase and selling of items, banking on the internet, and bill payment. The main difference is that customers do not need a laptop or PC to achieve this. They can make use of portable technologies such as cell phones and tablets. Users can now use online shopping sites and other internet services from anywhere and at any time. For example, when someone purchases any products if they have an Android or iOS app, they are engaging in m-commerce. A mobile device may be used to buy and sell a variety of content assets such as games, programmes, ringtones, subscriptions, and so on. Mobile commerce offers organisations extraordinary market potential, high productivity, as well as elevated profitability due to intrinsic properties such as ubiquity, personalisation, flexibility, and diffusion.

Implementation of Solar-Powered Submersible Pump Technology (PSTSP) to Increase Rainfed Rice Field Production

Waninggap Miraf is one of the villages with its main source of income being rice cultivation. Rainfed rice fields are managed by relying on rainwater stored in reservoirs, requiring Alkon pumps to control and supply water. However, operational costs for irrigating the fields have increased due to using oil-based fuels in the Alkon pumps. The implementation of Portable Solar-Powered Submersible Pump Technology (PSTSP) is expected to solve the challenges farmers face. The method utilized is harnessing solar energy as an alternative to oil-based fuels. The dissemination of this technology aims to optimize operational costs and enhance farmers' knowledge of utilizing renewable energy in agriculture. The implementation of this community-driven project involves the participation of the local community in the process of socialization, planning, design, training, and technology application. Based on trial results, this project has successfully increased farmers' knowledge and reduced operational costs by sustaining for up to 4 hours, supplying approximately 12,000 liters of water per hour.

Penerapan Teknologi Venturi Finebubble Portable Buoy Berbasis Solar Cell dan Internet Of Things Pada Tambak Udang Vaname Karangrejo Banyuwangi

Indonesia is a maritime country that has enormous potential in marine products. One of the marine products which is the highest export commodity is shrimp. Lingkungan Pakem, Karangrejo Village, Banyuwangi Regency is a partner location that is one of the national shrimp producing centers. Partners cultivate vaname shrimp with an intensive system as a producer of oxygen bubbles. The application of an intensive system causes problems, namely the amount of electricity costs and the uneven flow of water flow so that oxygen levels are not optimal. Based on these problems, the application of venturi finebubble portable buoy technology based on solar cells and IoT aims to increase the efficiency of the production of vannamei shrimp produced. The stages of technology application to partners consist of observation, planning, manufacture, assembly, and evaluation. The implementation of this technology can reduce electricity bills from operational costs in one harvest period (2 months) which was initially IDR 3,000,000.00 to IDR 2,000,000.00 and the average mortality rate of shrimp from 3000 individuals is equivalent to IDR 1,100,000.00 to 1560 individuals which is equivalent to IDR 572,000.00. Thus, the savings achieved are 37% or IDR 1,528,000.00 per harvest.

Single Position ECG Detection System Based on Charge Induction

With the growing incidence of cardiovascular disease (CVD) in recent decades, the demand for out-of-hospital real-time ECG monitoring is increasing day by day, which promotes the research and development of portable ECG monitoring equipment. At present, two main categories of ECG monitoring devices are “limb lead ECG recording devices” and “chest lead ECG recording devices”, which both require at least two electrodes. The former needs to complete the detection by means of a two-hand lap joint. This will seriously affect the normal activities of users. The electrodes used by the latter also need to be kept at a certain distance, usually more than 10 cm, to ensure the accuracy of the detection results. Decreasing the electrode spacing of the existing ECG detection equipment or reducing the area required for detection will be more conducive to improving the integration of the out-of-hospital portable ECG technologies. Therefore, a single-position ECG system based on charge induction is proposed to realize ECG detection on the surface of the human body with only one electrode with a diameter of less than 2 cm. Firstly, the ECG waveform detected in a single location is simulated by analyzing the electrophysiological activities of the human heart on the human body surface with COMSOL Multiphysics 5.4 software. Then, the hardware circuit design of the system and the host computer are developed and the test is performed. Finally, experiments for static and dynamic ECG monitoring are carried out and the heart rate correlation coefficients are 0.9698 and 0.9802, respectively, which proves the reliability and data accuracy of the system.

DESIGN AND PROTOTYPE OF AN AUTOMATED POSITIVE SUCTION MECHANICAL VENTILATOR UNDER AN ECONOMIC AND SOCIAL PROJECT ANALYSIS IN LOW-INCOME PATIENTS

The design and prototype of a low-cost portable positive pressure mechanical ventilator for use in cases of mass disasters and resource-limited environments are described. The ventilator provides breaths by compressing a conventional valve bag mask (AMBU) using a pivoting lever, eliminating the need for a human operator for the AMBU. An initial prototype was constructed using acrylic, with measurements of 285 x 350 x 250 mm and a weight of 4.1 kg (9 lb). It is powered by a 12V DC battery-operated electric motor and features an adjustable air volume of up to a maximum of 750 ml. Control is achieved through a human-machine interface using a 16x2 LCD screen displaying RPM and percentage speed data, which are adjusted using an easy-to-use potentiometer. The prototype also includes an overvoltage safety control mode and pilot lights to indicate the equipment's status. Iterations of the device will include a controllable inspiration-to-expiration time ratio, a pressure relief valve, and a battery bank system that allows for 4 hours of autonomy. The prototype manufacturing cost is only $820. Through this ventilator prototype, it is demonstrated that the lever-driven AMBU compression strategy is a viable option to achieve a low-cost, low-consumption portable technology that provides essential ventilator features at a fraction of the cost of existing technology

Biosensors for point-of-care testing and personalized monitoring of gastrointestinal microbiota.

The gastrointestinal (GI) microbiota is essential in maintaining human health. Alteration of the GI microbiota or gut microbiota (GM) from homeostasis (i.e., dysbiosis) is associated with several communicable and non-communicable diseases. Thus, it is crucial to constantly monitor the GM composition and host-microbe interactions in the GI tract since they could provide vital health information and indicate possible predispositions to various diseases. Pathogens in the GI tract must be detected early to prevent dysbiosis and related diseases. Similarly, the consumed beneficial microbial strains (i.e., probiotics) also require real-time monitoring to quantify the actual number of their colony-forming units within the GI tract. Unfortunately, due to the inherent limitations associated with the conventional methods, routine monitoring of one's GM health is not attainable till date. In this context, miniaturized diagnostic devices such as biosensors could provide alternative and rapid detection methods by offering robust, affordable, portable, convenient, and reliable technology. Though biosensors for GM are still at a relatively preliminary stage, they can potentially transform clinical diagnosis in the near future. In this mini-review, we have discussed the significance and recent advancements of biosensors in monitoring GM. Finally, the progresses on future biosensing techniques such as lab-on-chip, smart materials, ingestible capsules, wearable devices, and fusion of machine learning/artificial intelligence (ML/AI) have also been highlighted.

Clinical features and novel technologies for prehospital detection of intracerebral haemorrhage: a scoping review protocol

IntroductionThe detection of intracerebral haemorrhage (ICH) in the prehospital setting without conventional imaging technology might allow early treatment to reduce haematoma expansion and improve patient outcomes. Although ICH and ischaemic...

Performance Assessment of Heartbeat Detection Algorithms on Photoplethysmograph and Functional NearInfrared Spectroscopy Signals

With wearable sensors, the acquisition of physiological signals has become affordable and feasible in everyday life. Specifically, Photoplethysmography (PPG), being a low-cost and highly portable technology, has attracted notable interest for measuring and diagnosing cardiac activity, one of the most important physiological and autonomic indicators. In addition to the technological development, several specific signal-processing algorithms have been designed to enable reliable detection of heartbeats and cope with the lower quality of the signals. In this study, we compare three heartbeat detection algorithms: Derivative-Based Detection (DBD), Recursive Combinatorial Optimization (RCO), and Multi-Scale Peak and Trough Detection (MSPTD). In particular, we considered signals from two datasets, namely, the PPG-DALIA dataset (N = 15) and the FANTASIA dataset (N = 20) which differ in terms of signal characteristics (sampling frequency and length) and type of acquisition devices (wearable and medical-grade). The comparison is performed both in terms of heartbeat detection performance and computational workload required to execute the algorithms. Finally, we explore the applicability of these algorithms on the cardiac component obtained from functional Near InfraRed Spectroscopy signals (fNIRS).The results indicate that, while the MSPTD algorithm achieves a higher F1 score in cases that involve body movements, such as cycling (MSPTD: Mean = 74.7, SD = 14.4; DBD: Mean = 54.4, SD = 21.0; DBD + RCO: Mean = 49.5, SD = 22.9) and walking up and down the stairs (MSPTD: Mean = 62.9, SD = 12.2; DBD: Mean = 50.5, SD = 11.9; DBD + RCO: Mean = 45.0, SD = 14.0), for all other activities the three algorithms perform similarly. In terms of computational complexity, the computation time of the MSPTD algorithm appears to grow exponentially with the signal sampling frequency, thus requiring longer computation times in the case of high-sampling frequency signals, where the usage of the DBD and RCO algorithms might be preferable. All three algorithms appear to be appropriate candidates for exploring the applicability of heartbeat detection on fNIRS data.

Rapid, convenient, and ultrasensitive point-of-care sensing of histamine from fish: A Portable chromatographic platform based on derivatization reaction

Food poisoning caused by histamine ingestion is one of the prevalent allergies associated with fish consumption in the world. Reliable detection of histamine from fish by a portable platform was of urgent importance to food safety. A portable technology for on-site monitoring of histamine in tuna was established through combined azo-derivatized thin-layer chromatography (TLC) with surface-enhanced Raman scattering (SERS) spectroscopy. The real tuna meat sample was directly applied onto the portable sensor for the separation of histamine and azo-derivatizing of histamine was reacted on the TLC plate. The colorless histamine was visualized by azo-derivatization after spraying Pauly reagent onto the diatomite TLC plate. The molecule information and concentration of the histamine was measured and calculated by SERS spectra. Diatomite TLC plate was capable of separating histamine with 1.32 × 10−7 M of Au colloid for the SERS enhancement. Accordingly, the limit of detection of histamine from mixture sample could achieve 2.8 × 10−4 ppm. These results indicated that the portable azo-derivatized TLC-SERS sensor not only visualizes the histamine but also improves the intensity of the Raman spectra. The azo-derivatized TLC-SERS sensor could be applied for rapid, convenient, and ultrasensitive point-of-care sensing of histamine in fish.

Minecraft as a technology of postwar urban ordering: the situated-portable epistemic nexus of urban peacebuilding in Pristina

ABSTRACT In this article, I argue that a ‘situated-portable epistemic nexus’ characterizes postwar urban peacebuilding. The concept captures how knowledge in urban peacebuilding is produced by/productive of discursive and material conditions that are both, and simultaneously, situated in a particular urban environment and transnationally emergent and circulating. I illustrate this argument in an analysis of an urban peacebuilding project in postwar Pristina, Kosovo, that relied on the computer game Minecraft as the main technology. Despite a heterogeneous group of actors involved, and a primacy devoted to local perspectives, the at-once-situated and globally portable discourses, technologies and artefacts of the Pristina project conditioned the production of a relatively narrow urban knowledge and space that formed around a purely visual conception of the urban – overall limiting what the situated urban was and could become.

Characterization of Gaseous and Particulate Phase Polycyclic Aromatic Hydrocarbons Emitted During Preharvest Burning of Sugar Cane in Different Regions of Kwa-Zulu Natal, South Africa.

Biomass burning is a significant anthropogenic source of air pollution, including the preharvest burning of sugar cane. These burn events result in atmospheric emissions, including semivolatile organic compounds, that may have adverse impacts on air quality and human health on a local, regional, and even a global scale. Gaseous and particulate polycyclic aromatic hydrocarbon (PAH) emissions from various sugar cane burn events in the province of Kwa-Zulu Natal in South Africa were simultaneously sampled using a portable denuder sampling technology, consisting of a quartz fiber filter sandwiched between two polydimethylsiloxane multichannel traps. Total gas and particle phase PAH concentrations ranged from 0.05 to 9.85 µg m-3 per individual burn event, and nine PAHs were quantified. Over 85% of all PAHs were found to exist in the gas phase, with smaller two- and three-ring PAHs, primarily naphthalene, 1-methyl naphthalene, and acenaphthylene, being the most dominant and causing the majority of variance between the burn sites. The PAH profiles differed between the different burn events at different sites, emphasizing the significant influence that the crop variety, prevailing weather conditions, and geographical location has on the type and number of pollutants emitted. The potential carcinogenicity of the PAH exposure was estimated based on toxic equivalency factors that showed varying risk potentials per burn event, with the highest value of 5.97 ng m-3 . Environ Toxicol Chem 2023;42:778-792. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Tackling chikungunya and dengue crisis in Paraguay amidst COVID-19: an epidemiological alert - a correspondence.

Tackling chikungunya and dengue crisis in Paraguay amidst COVID-19: an epidemiological alert - a correspondence.

Development of a New Lab-on-Paper Microfluidics Platform Using Bi-Material Cantilever Actuators for ELISA on Paper.

In this paper, we present a novel and cost-effective lab-on-paper microfluidics platform for performing ELISA autonomously, with no user intervention beyond adding the sample. The platform utilizes two Bi-Material Cantilever Valves placed in a specially designed housing. The integration of these valves in a specific channel network forms a complete fluidic logic circuit for performing ELISA on paper. The housing also incorporates an innovative reagent storage and release mechanism that minimizes variability in the volume of reagents released into the reagent pads. The platform design was optimized to minimize variance in the time of fluid wicking from the reagent pad, using a randomized design of experiment. The platform adheres to the World Health Organization's ASSURED principles. The optimized design was used to conduct an ELISA for detecting rabbit immunoglobulin G (IgG) in a buffer, with a limit of detection of 2.27 ng/mL and a limit of quantification of 8.33 ng/mL. This represents a 58% improvement over previous ELISA methods for detecting rabbit IgG in buffer using portable microfluidic technology.