Wireless Tracking Research Articles

Self-powered strain sensing devices with wireless transmission: DIW-printed conductive hydrogel electrodes featuring stretchable and self-healing properties

With rapid advancements in health and human–computer interaction, wearable electronic skins (e-skins) designed for application on the human body provide a platform for real-time detection of physiological signals. Wearable strain sensors, integral functional units within e-skins, can be integrated with Internet of Things (IoT) technology to broaden the applications for human body monitoring. A significant challenge lies in the reliance of most existing wearable strain sensors on rigid external power supplies, limiting their practical flexibility. In this study, we present an innovative strategy to fabricate glutaraldehyde (GA)-poly(vinyl alcohol) (PVA)/cellulose nanocrystals (CNC)/Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) conductive hydrogels through multiple hydrogen bonding systems. Combining the advantageous rheological properties of the precursor solution and the high specific surface area after freeze–thaw cycling, we have created a self-powered sensing system prepared by large-area printing using direct ink writing (DIW) printing. The resulting conductive hydrogel exhibits commendable mechanical properties (411 KPa), impressive stretchability (580 %), and robust self-healing capabilities (>98.3 %). The strain sensor, derived from the conductive hydrogel, demonstrates a gauge factor (GF) of 2.5 within a stretching range of 0–580 %. Additionally, the resultant supercapacitor displays a peak energy density of 0.131 mWh/cm3 at a power density of 3.6 mW/cm3. Benefiting from its elevated strain response and remarkable power density features, this self-powered strain sensing system enables the real-time monitoring of human joint motion. The incorporation of a 5G transmission module enhances its capabilities for remote data monitoring, thereby contributing to the progress of wireless tracking technologies for self-powered electronic skin.

Digitally-defined ultrathin transparent wireless sensor network for room-scale imperceptible ambient intelligence

Wireless and battery-free radio-frequency (RF) sensors can be used to create physical spaces that ambiently sense and respond to human activities. Making such sensors ultra-flexible and transparent is important to preserve the aesthetics of living environments, accommodate daily activities, and functionally integrate with objects. However, existing RF sensors are unable to simultaneously achieve high transparency, flexibility, and the electrical conductivity required for remote room-scale operation. Here, we report 4.5 µm RF tag sensors achieving transparency exceeding 90% that provide capabilities in room-scale ambient wireless sensing. We develop a laser-assisted water-based adhesion-reversion process to digitally realize computer-aided RF design at scale. By individually tagging multiple objects and regions of the human body, we demonstrate multiplexed wireless tracking of human-environment interactions and physiological signals at a range of up to 8 m. These radio-frequency identification sensors open opportunities for non-intrusive wireless sensing of daily living spaces for applications in health monitoring and elderly care.

Statistical evaluation of tongue capability with visual feedback

BackgroundAnalysis of tongue movement would benefit from a reference showcasing healthy tongue capability. We aimed to develop a reference of tongue capability and evaluated the role of visual feedback on the expression of movement.MethodsUsing a wireless tracking intraoral wearable device, we composed probability distributions of the tongue tip as subjects were asked to explore the entire sensing surface area. Half of the 32 subjects received live visual feedback of the location of the center of the tongue tip contact.ResultsWe observed that the visual feedback group was 51.0% more consistent with each other in the position domain, explored 21.5% more sensing surface area, and was 50.7% more uniformly distributed. We found less consistent results when we evaluated velocity and acceleration.ConclusionVisual feedback best established a healthy capability reference which can be used for designing new interfaces, quantifying tongue ability, developing new diagnostic and rehabilitation techniques, and studying underlying mechanisms of tongue motor control.

Printable and flexible integrated sensing systems for wireless healthcare.

The rapid development of wearable sensing devices and artificial intelligence has enabled portable and wireless tracking of human health, fulfilling the promise of digitalized healthcare applications. To achieve versatile design and integration of multi-functional modules including sensors and data transmission units onto various flexible platforms, printable technologies emerged as some of the most promising strategies. This review first introduces the commonly utilized printing technologies, followed by discussion of the printable ink formulations and flexible substrates to ensure reliable device fabrication and system integration. The advances of printable sensors for body status monitoring are then discussed. Moreover, the integration of wireless data transmission via printable approaches is also presented. Finally, the challenges in achieving printable sensing devices and wireless integrated systems with competitive performances are considered, so as to realize their practical applications for personalized healthcare.

Event-Based Wireless Tracking Control for a Wheeled Mobile Robot Against Reactive Jamming Attacks

In this paper, an event-based defense strategy is studied for a wireless remote tracking control system of a wheeled mobile robot suffering from reactive jamming attacks. First, utility functions of both the reactive jammer and control center are established based on the signal to interference plus noise ratio and residual energies. Then, interactions between the reactive jammer and control center are described through a Stackelberg game scheme, for which the existence and uniqueness of the game equilibrium solution are guaranteed. To defend this type of attacks, an event-driven communication scheme is proposed to save transmission energies at the control center. By making full use of the saved energies, a retransmission mechanism is employed to improve the reliability of the communication. Meanwhile, the unavailable data are estimated for both the robot and control center by proposing a model-based estimation method. With the combination of the event-driven communication scheme, the retransmission mechanism and the estimation method, an event-based defense strategy is established. It can be shown that the states of tracking error system under the reactive jamming attacks is guaranteed to be stochastically ultimately bounded (SUB). Finally, the efficiency of the proposed scheme is verified by simulation results.

Multi-engineered Graphene Extended-Gate Field-Effect Transistor for Peroxynitrite Sensing in Alzheimer's Disease.

The expression of β-amyloid peptides (Aβ), a pathological indicator of Alzheimer's disease (AD), was reported to be inapparent in the early stage of AD. While peroxynitrite (ONOO-) is produced excessively and emerges earlier than Aβ plaques in the progression of AD, it is thus significant to sensitively detect ONOO- for early diagnosis of AD and its pathological research. Herein, we unveiled an integrated sensor for monitoring ONOO-, which consisted of a commercially available field-effect transistor (FET) and a high-performance multi-engineered graphene extended-gate (EG) electrode. In the configuration of the presented EG electrode, laser-induced graphene (LIG) intercalated with MnO2 nanoparticles (MnO2/LIG) can improve the electrical properties of LIG and the sensitivity of the sensor, and graphene oxide (GO)-MnO2/Hemin nanozyme with ONOO- isomerase activity can selectively trigger the isomerization of ONOO- to NO3-. With this synergistic effect, our EG-FET sensor can respond to the ONOO- with high sensitivity and selectivity. Moreover, taking advantage of our EG-FET sensor, we modularly assembled a portable sensing platform for wireless tracking ONOO- levels in the brain tissue of AD transgenic mice at earlier stages before massive Aβ plaques appeared, and we systematically explored the complex role of ONOO- in the occurrence and development of AD.

Advancements in Image-Guided Navigation for Surgical Procedures

Surgeons may now conduct complex surgeries with more precision, accuracy, and safety thanks to image-guided navigation. This article analyzes how image-guided navigation devices have changed surgical operations. Surgeons now approach procedures differently thanks to the integration of imaging modalities like Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and ultrasound with surgical navigation systems. Surgeons can confidently navigate complex anatomical features and plan surgical paths using these technologies' real-time, three-dimensional anatomy visualization. Image-guided navigation has advanced with Augmented Reality (AR) and Virtual Reality (VR). Augmented Reality (AR) devices improve spatial awareness and reduce errors by superimposing patient-specific anatomical data onto the surgeon's field of view. VR allows surgeons to perform complex surgeries in a virtual environment, increasing their skills and aiding preoperative planning. Another innovation is machine learning and Artificial Intelligence (AI) algorithms in image-guided navigation systems. These algorithms evaluate massive volumes of patient data, including medical pictures, surgery plans, and results, to help surgeons make predictions and judgments. Data-driven algorithms in AI-driven navigation systems optimize surgical operations, accuracy, and patient outcomes. Miniaturized and wireless tracking systems provide less invasive image-guided navigation. Electromagnetic and optical monitoring devices allow surgeons to track surgical tools inside the patient's body, providing real-time feedback and instruction. Image-guided navigation is being used in laparoscopic, endoscopic, and robotic-assisted surgeries. Image-guided navigation still faces challenges. The incorporation of diverse imaging modalities, system accuracy, and smooth compatibility with surgical instruments are ongoing research and development. To promote widespread adoption of these technologies, cost-effectiveness, training, and regulations must be addressed. Image-guided navigation has improved surgical visualization, navigation, and decision-making. Augmented reality, virtual reality, machine learning, and tiny tracking have improved surgery and patient outcomes. Image-guided navigation could become common surgery with continued study and improvement in this sector.

Indoor tracking for smart hospital by a hybrid visible light positioning system

<p class="Abstract">Modern hospital operations and management, i.e., smart hospitals, require pervasive system-wide wireless communication and positioning capabilities. Unfortunately, this cannot be entirely facilitated by existing radio frequency (RF) wireless technologies due to interference concerns in hospitals. We design and implemented a novel hybrid RF-free wireless tracking system utilizing combined visible light communication (VLC) and positioning (VLP), and powerline communication (PLC) technologies to enable future smart hospital operations. This VLC/VLP/PLC tracking system consists of host optical transceivers embedded in light-emitting diode (LED) bulbs and user-end photodetector (PD) optical tags, as well as backbone powerline interface, to form a ubiquitous wireless tracking and communication network connecting all people and equipment throughout all hospital buildings. The new indoor optical-based tracking system was validated via simulation and experiments. Being embedded into the existing LED lighting infrastructure, this hybrid VLC/VLP/PLC tracking system technology is accurate, ultralow cost and environment friendly. Smart hospitals will lead to efficient and affordable healthcare, a revolutionary solution in the human society.</p>

Miniature magneto-mechanical resonators for wireless tracking and sensing.

Sensor miniaturization enables applications such as minimally invasive medical procedures or patient monitoring by providing process feedback in situ. Ideally, miniature sensors should be wireless, inexpensive, and allow for remote detection over sufficient distance by an affordable detection system. We analyze the signal strength of wireless sensors theoretically and derive a simple design of high-signal resonant magneto-mechanical sensors featuring volumes below 1 cubic millimeter. As examples, we demonstrate real-time tracking of position and attitude of a flying bee, navigation of a biopsy needle, tracking of a free-flowing marker, and sensing of pressure and temperature, all in unshielded environments. The achieved sensor size, measurement accuracy, and workspace of ~25 centimeters show the potential for a low-cost wireless tracking and sensing platform for medical and nonmedical applications.

The watchful eye: investigating tourist perceptions of different wireless tracking technologies at a travel destination

ABSTRACT Wireless tracking technologies is an emerging technology used in tourism destinations to better understand the movement of tourists and to develop more personalized products. However, little is understood of tourists’ perceptions of these wireless tracking technologies. This study investigated the impact inferences of manipulative intent, privacy concerns, perceived personalization, and personal innovativeness on tourists’ attitudes and intentions towards the technology and destinations. A total of 615 questionnaires were collected under three between-subject’s conditions, namely ‘wireless tracking only’, ‘Wi-Fi wireless tracking’, and ‘app-based tracking’. Structural equation modelling revealed that perceived personalization significantly predicted positive attitudes, while inferences of manipulative intent significantly deterred tourists. Theoretically, this study reveals the different ways in which different wireless tracking technologies are perceived and how these perceptions impact on the destination. Further, the results of this study can assist destination marketing organizations and governing bodies to improve their implementation of such technologies at a destination.

Spatiotemporal Modeling of Grip Forces Captures Proficiency in Manual Robot Control.

New technologies for monitoring grip forces during hand and finger movements in non-standard task contexts have provided unprecedented functional insights into somatosensory cognition. Somatosensory cognition is the basis of our ability to manipulate and transform objects of the physical world and to grasp them with the right amount of force. In previous work, the wireless tracking of grip-force signals recorded from biosensors in the palm of the human hand has permitted us to unravel some of the functional synergies that underlie perceptual and motor learning under conditions of non-standard and essentially unreliable sensory input. This paper builds on this previous work and discusses further, functionally motivated, analyses of individual grip-force data in manual robot control. Grip forces were recorded from various loci in the dominant and non-dominant hands of individuals with wearable wireless sensor technology. Statistical analyses bring to the fore skill-specific temporal variations in thousands of grip forces of a complete novice and a highly proficient expert in manual robot control. A brain-inspired neural network model that uses the output metric of a self-organizing pap with unsupervised winner-take-all learning was run on the sensor output from both hands of each user. The neural network metric expresses the difference between an input representation and its model representation at any given moment in time and reliably captures the differences between novice and expert performance in terms of grip-force variability.Functionally motivated spatiotemporal analysis of individual average grip forces, computed for time windows of constant size in the output of a restricted amount of task-relevant sensors in the dominant (preferred) hand, reveal finger-specific synergies reflecting robotic task skill. The analyses lead the way towards grip-force monitoring in real time. This will permit tracking task skill evolution in trainees, or identify individual proficiency levels in human robot-interaction, which represents unprecedented challenges for perceptual and motor adaptation in environmental contexts of high sensory uncertainty. Cross-disciplinary insights from systems neuroscience and cognitive behavioral science, and the predictive modeling of operator skills using parsimonious Artificial Intelligence (AI), will contribute towards improving the outcome of new types of surgery, in particular the single-port approaches such as NOTES (Natural Orifice Transluminal Endoscopic Surgery) and SILS (Single-Incision Laparoscopic Surgery).

Numerical Investigation on ELF Electromagnetic Field Distribution of Pipeline Robot Tracking and Positioning System Using UAV

Pipeline robot, as a new type of equipment for pipeline operations such as pigging and detection, will play an increasingly important role in the operation and maintenance of oil and gas pipeline networks. The tracking and positioning technology during its operation process is one of the essential topics to improve the operating performance of pipeline robots and eliminate potential pipeline accidents. This paper presents the overall design of the wireless tracking and positioning system for pipeline robots based on extremely low frequency (ELF) electromagnetic method using the unmanned aerial vehicle (UAV). Starting from the classical electromagnetic theory, a mathematical model for the distribution of ELF electromagnetic field in buried metal pipeline environment is established. According to the characteristics of ELF electromagnetic wave transceiver and the model based on classical theory, the equivalent magnetic dipole transmission model is deduced. Based on the equivalent model, the attenuation characteristics of the ELF electromagnetic wave in the external space of the pipeline are analyzed by numerical simulation. The influence of the geometrical dimensions, environmental and working parameters, and other factors on the electromagnetic field intensity outside the pipeline is given at the same time. Finally, the distribution of ELF electromagnetic field in pipeline environment is discussed for horizontal-laying pipeline and inclined-laying pipeline, and the tracking method of pipeline robot is proposed on this basis. The proposed scheme is practical and effective, and it is suitable for real-time tracking and positioning of robot working in the pipelines whose slope is no more than 60 degrees with known or unknown distribution.

ASO Visual Abstract: Real-Time Wireless Tumor Tracking in Navigated Liver Resections—an Ex Vivo Feasibility Study

ASO Visual Abstract: Real-Time Wireless Tumor Tracking in Navigated Liver Resections—an Ex Vivo Feasibility Study

Acceptance of RFID Toll Payment Method by Highway Users in Malaysia

Radio frequency identification (RFID) is a wireless tracking technology for data identification, capturing and analysis. It is used in numerous business applications to overcome the drawback of collecting data manually, such as data errors, time delay and high labour cost. RFID was introduced as an alternate toll charge payment method in Malaysia highways in 2018, and the government of Malaysia aims for a full implementation by end 2023. However, up to January 2022, only 10% of highway users switched to RFID. Hence, this study aims to assess highway users’ intention level on using RFID as toll payment mode. Additionally, the study also aims to evaluate the causal relationship between users’ perception on RFID payment mode and users’ intention to use RFID. The study views users’ perception based on modified TAM theory, which consist of perceived ease of use, perceived usefulness, perceived culture’s influence and perceived privacy and security. The study is quantitative based, structured questionnaire adopted from prior studies was distributed to the targeted population, which is class 1 highway users, and 176 responded. Data collected is normally distributed and statistically reliable. Hence, data was processed further with descriptive analysis and Pearson correlation test to address the research objectives. Finding from the research reveals that users’ intention to migrate to RFID payment mode is low, which suggested additional effort is required for the full implementation of RFID by end 2023. Additionally. Result of correlation test discloses that users’ perception on the ease of use and the usefulness are significantly associated with the intention to use RFID. However, the correlation of perceived culture’s influence, privacy and security with intention is weak and insignificant. The finding implies that highway operator should focus on addressing users’ anxieties and hesitation of using RFID in order to encourage more users to migrate to RFID. Additionally, the study also contributes to the domain new technology acceptance by the introduction of users’ acceptance model for RFID based on modified TAM theory.

A PERUSAL STUDY OF METHODS FOR ENERGY EFFICIENT MULTI OBJECT TRACKING IN WIRELESS SENSOR NETWORKS

Wireless sensor networks (WSNs) has various applications in different areas such as object detection and target tracking, industrial process monitoring, environmental monitoring, wildlife monitoring, Robot control and security applications for buildings. In WSNs, Energy efficiency is one of the important research issues, as it determines the lifetime of the sensor network deployed for the specific applications. Object tracking is one of the dominant applications of wireless sensor networks and many energy-efficient multi object tracking algorithms are used for precise or exact object tracking. The main focus this paper is the perusal study of all different energy-efficient object tracking methods and algorithms for Wireless Sensor Network.

Intelligent Ureteral Stent for Early Detection of Hydronephrosis

AbstractMillions of people around the world currently suffer from kidney stone diseases. While ureteral stenting is an unmistakably effective treatment of these patients, their long‐term adverse effects can result in the build‐up of crystals around the stent. This, in turn, can lead to new ureter blockages that can dangerously increase kidney pressure, a condition known as hydronephrosis, which, if severe and prolonged, can cause irreversible kidney damage. Toward enabling early detection of hydronephrosis, this paper investigates the first intelligent ureteral stent with an integrated radiofrequency antenna and micro pressure sensor for resonance‐based wireless tracking of kidney pressure. Prototyping is conducted using a commercial ureteral stent as the substrate for microfabrication of the device. The packaged device is experimentally assessed for electrical characterizations and wireless pressure sensing using an in vitro test model. Preliminary telemetry testing demonstrates the fundamental ability of the device with its approximately linear responses of up to 1.7 kHz mmHg−1 over a pressure range of up to 120 mmHg in air, water, and artificial urine. These findings verify the efficacy of the device design and the approach to kidney pressure monitoring through indwelling stents, paving the way for the transfer of this technology to today's ureteral stent products.

Validation of a novel handheld 3D ultrasound system for imaging scoliosis - phantom study.

Use of 3D ultrasound (US) scanners to detect and monitor scoliosis have been validated. The Cobb angle, axial vertebral rotation, spinal flexibility, curvatures in the sagittal profile and the Cobb angle on the plane of maximum curvature (PMC) can be measured from coronal, transverse and sagittal planes of ultrasound images. However, traditional 3D ultrasound scanners are relatively bulky and expensive. 2D US handheld and low-cost scanners are widely available. To adapt the 2D scanners for scoliosis applications, a position and orientation system is integrated with the scanner. The objective of this study was to validate a newly developed 3D handheld US system to image the spine. The wireless handheld US scanner (C3-HD, Clarius, Canada) was selected because of its high resolution and availability of raw data. A wireless tracking system based on electromagnetic (G4 system, Polhemus, USA) was integrated with the Clarius ultrasound. During scanning, the ultrasound information was synchronized with the scanner's position and orientation by using custom developed software. Both information were streamed wirelessly to a laptop. Custom software reconstructed and displayed the 3D spinal image in real-time. A single 3D printed vertebra, two full plastic spine phantoms from T1-T12 vertebrae and a non-scoliotic volunteer were scanned. The 3D reconstruction process of a spine image was less than 3 seconds. The dimensional and the angle errors were 1 mm and 3°, respectively. This study demonstrated that a low-cost ($11,000 USD) handheld 3D ultrasound system was developed and validated. Clinical trials on subjects attending will be the next step.

Intensive longitudinal characterization of multidimensional biobehavioral dynamics in laboratory rats.

Rats have been used as animal models for human diseases for more than a century, yet a systematic understanding of basal biobehavioral phenotypes of laboratory rats is still missing. In this study, we utilize wireless tracking technology and videography, collect and analyze more than 130 billion data points to fill this gap, and characterize the evolution of behavior and physiology of group-housed male and female rats (n= 114) of the most commonly used strains (Lister Hooded, Long-Evans, Sprague-Dawley, and Wistar) throughout their development. The resulting intensive longitudinal data suggest the existence of strain and sex differences and bi-stable developmental states. Under standard laboratory 12-h light/12-h dark conditions, our study found the presence of multiple oscillations such as circatidal-like rhythms in locomotor activity. The overall findings further suggest that frequent movement along cage walls or thigmotaxic activity may be a physical feature of motion in constrained spaces, critically affecting the interpretation of basal behavior of rats in cages.

Performance Analysis of Wireless Location and Velocity Tracking of Digital Broadcast Signals Based on Extended Kalman Filter Algorithm

In order to improve the accuracy and reliability of wireless location in NLOS environment, a wireless location algorithm based on artificial neural network (ANN) is proposed for NLOS positioning error caused by non-line-of-sight (NLOS) propagation, such as occlusion and signal reflection. The mapping relationship between TOA and TDOA measurement data and coordinates is established. The connection weights of neural network are estimated as the state variables of nonlinear dynamic system. The multilayer perceptron network is trained by the real-time neural network training algorithm based on extended Kalman (EKF). Combined with the statistical characteristics of NLOS error, the state component NLOS bias estimation is modified to realize TDOA data reconstruction. Simulation and experimental data analysis show that the algorithm can effectively weaken the influence of NLOS error. The localization method does not depend on the specific NLOS error distribution, nor does it need LOS and NLOS recognition. It can significantly improve the mobile positioning accuracy.

Virtual Reality Interactive Method and Device Based on Wireless Communication Tracking

Virtual reality is a computer system that creates a virtual world and then experiences through multiple senses. It is generated by a computer and stimulated by perception systems such as hearing, vision, touch, taste, and smell, providing users with a personal experience. Human‐computer interaction is one of the core technologies of virtual reality. Wireless communication is the transmission of communications over long distances between multiple nodes without propagation through conductors or cables and can be carried out using radios, radios, etc. Wireless communication includes a variety of fixed, mobile, and portable applications such as two‐way radios, mobile phones, personal digital assistants, and wireless networks. Other examples of radio wireless communication are GPS, garage door remotes, wireless mice, etc. Most wireless communication technologies use radio, including Wi‐Fi with distances of just a few meters, but also deep space networks that communicate with Voyager 1 and distances of over millions of kilometers. With the continuous development of sensors and other supporting hardware facilities, the current development of human‐computer interaction in virtual reality has made rapid progress. In the research to be conducted in this article, the virtual reality system used in this article cleverly integrates the three characteristics of immersion, interactivity, and conception, so that the experimenter can obtain more realistic data in comparison. To this end, this article first gives a general introduction to virtual reality technology and wireless communication tracking technology and then explains how to use wireless communication tracking technology to make the virtual reality interactive system smoother and smoother, as well as the introduction of its devices. This article explores and analyzes the possible or existing problems of wireless communication tracking technology in virtual reality interaction, hoping to contribute to the wider application of wireless communication tracking technology in virtual reality interaction. The positioning experiment on the wireless mobile signal identification points can be obtained. Among the 40 sensor nodes that are randomly deployed, when the interval of adjusting the mobile signal identification point to broadcast the current position information is 5 s, the average positioning error of the node is about 1.5 m; when the interval is 3 s, the average positioning error of the node is about 1.76 m. It can be seen that the positioning error of the node increases as the interval between the mobile signal identification points increases, which is consistent with the simulation detection result. When the node position of the target signal identification point is chosen to calculate does not just stay on the node communication circle, it introduces a certain localization distance difference, and the further the target signal identification point is from the position of the signal circle, the greater the error. Irregularity of RSS due to environmental changes analyzes the maximum error and provides the factors influencing the error and analyzing the maximum error and provide the factors that influence it.