Non-contact Device Research Articles

Intelligent rehabilitation platform in intensive care unit

As the development of rehabilitation medicine and critical care medicine, intensive care rehabilitation has become the focus of attention. With the development of artificial intelligence, wearable devices and non-contact multimodal behavior perception devices can collect and transmit patients' vital signs continuously, and establish large databases and formulate rehabilitation strategies intelligently. Wearable devices, exoskeleton robots, position management beds, rehabilitation robots, virtual reality can be used in the implementation of rehabilitation in ICU. The whole process rehabilitation mode which combined intelligent rehabilitation with sequential remote home management might be a new work mode of intensive care rehabilitation in the future.

Indoor Human Action Recognition Based on Dual Kinect V2 and Improved Ensemble Learning Method.

Indoor human action recognition, essential across various applications, faces significant challenges such as orientation constraints and identification limitations, particularly in systems reliant on non-contact devices. Self-occlusions and non-line of sight (NLOS) situations are important representatives among them. To address these challenges, this paper presents a novel system utilizing dual Kinect V2, enhanced by an advanced Transmission Control Protocol (TCP) and sophisticated ensemble learning techniques, tailor-made to handle self-occlusions and NLOS situations. Our main works are as follows: (1) a data-adaptive adjustment mechanism, anchored on localization outcomes, to mitigate self-occlusion in dynamic orientations; (2) the adoption of sophisticated ensemble learning techniques, including a Chirp acoustic signal identification method, based on an optimized fuzzy c-means-AdaBoost algorithm, for improving positioning accuracy in NLOS contexts; and (3) an amalgamation of the Random Forest model and bat algorithm, providing innovative action identification strategies for intricate scenarios. We conduct extensive experiments, and our results show that the proposed system augments human action recognition precision by a substantial 30.25%, surpassing the benchmarks set by current state-of-the-art works.

A Noncontact Feed Microwave Metal Devices Deformation and Stress Sensor Based on Metamaterial

In this paper, a non-contact feed microwave metal deformation and stress sensor based on microwave harvesting metamaterial (MHMA) is proposed. It integrates HMA array, feed network and complementary cross finger split-ring resonator detector (CFSRRD). The sensor can be applied in the detection system composed of waveguide antenna (WA at 10GHz) and vector network analyzer (VNA). In processing of monitoring, the signal emitted by WA will be captured by MHMA array and output to CFSRRD through feed network. Then the response signal of CFSRRD will be returned to WA and analyzed by VNA. From analysis results, the deformation information of metal device will be obtained. Combined with the initial conditions of metal devices, the stress mutation information can be further obtained. Simulation and measurement results show that the designed sensor can detect the metal pipeline deformation caused by external force, pressure or high temperature with the reliable accuracy level of 500 μm (Submillimeter Level), and the minimum detectable radius of pipe is 30mm. It has the advantage of simple structure, strong adaptability and overcomes the shortcoming that traditional detection methods are difficult to detect the operating state of metal devices in complex environment.

A Flexible Tough Hydrovoltaic Coating for Wearable Sensing Electronics.

The lack of a strong binding mechanism between nanomaterials severely restricts the advantages of the evaporation-driven hydrovoltaic effect in wearable sensing electronics. It is a challenging task to observably improve the mechanical toughness and flexibility of hydrovoltaic devices to match the wearable demand without abandoning the nanostructures and surface function. Here, a flexible tough polyacrylonitrile/alumina (PAN/Al2 O3 ) hydrovoltaic coating with both good electricity generation (open-circuit voltage, Voc ≈3.18V) and sensitive ion sensing (2285VM-1 for NaCl solutions in 10-4 to 10-3 m) capabilities is developed. The porous nanostructure composed of Al2 O3 nanoparticles is firmly locked by the strong binding effect of PAN, giving a critical binding force 4 times that of Al2 O3 film to easily deal with 9.92ms-1 strong water-flow impact. Finally, skin-tight and non-contact device structures are proposed to achieve wearable multifunctional self-powered sensing directly using sweat. The flexible tough PAN/Al2 O3 hydrovoltaic coating breaks through the mechanical brittleness limitation and broadens the applications of the evaporation-induced hydrovoltaic effect in self-powered wearable sensing electronics.

Non-contact model test and numerical simulation of plastic zone in sandy soil foundation

Reasonable determination of the ultimate bearing capacity of the foundation is of great significance in engineering applications. Based on the self-developed non-contact testing device for the plastic zone of shallow foundation, this paper carries out model test research on the plastic zone of sandy soil shallow foundation and analyzes the development law of plastic zone under the action of foundation load. The main advantages and functional characteristics of the foundation plastic zone test system are that it can realize the non-contact test of displacement deformation of soil, the dynamic development process of shear deformation, and the plastic zone of model foundation can be obtained intuitively. The development process, morphological boundary characteristics, and foundation failure mode of the plastic zone of the sand foundation are obtained. The plastic zone of the foundation starts from the edges of both sides of the bearing plate; with the increase of the load, the plastic zone gradually develops downward and approaches to the center line, and finally crosses through at the bottom until the local shear failure of the foundation occurs. The measured plastic zone is a symmetrical spindle shape with thin ends and a bulge in the middle; the sand on both sides of the bearing plate partially bulges, forming a “V” shaped shear failure zone, and the bottom of bearing plate forms a triangular compression zone, the foundation failure mode of sandy soil represents a typical punching shear failure mode. In order to study the distribution characteristics of the plastic zone range of foundation under different foundation loads and foundation widths, the Universal Distinct Element Code (UDEC) based on the discrete element method is used for numerical simulation research. By conducting parameterized numerical simulation test for the plastic zone of foundation and analyzing the results, with the changes in the foundation load and the foundation width, the variation law of (1) the depth of the plastic zone on the foundation bottom, (2) the width of the plastic zone on both sides of the foundation, (3) the ratio for the depth of plastic zone to the width of foundation, (4) the ratio for the width of plastic zone to the width of foundation and (5) the ratio for the width of plastic zone to the depth of plastic zone is obtained. The research has significant guiding significance for the study of the development law of plastic zone and foundation design.

Development of an IoT Embedded Wearable Device with Non-Contact Temperature Detector for Early Detection of Fever

One of the most common and early symptoms of any viral infections is fever which is the reaction to a disease-specific stimulus causing the increase of human body temperature. The current common method of monitoring the human body temperature uses the application of non-contact infrared thermometer (NCIT) and is only limited for stationary conditions within short distances and mostly suitable for indoor premises. The available technology to detect human body temperature for longer distances uses the thermal camera which is costly and large. Thus, it is challenging to detect anyone with high body temperature innon-stationary conditions, at longer distances, especially outdoor. The paper proposes an innovation to the current practice, for a wearable non-contact temperature detector device which is portable. The wearable non-contact temperature detector embeds a thermal sensor and a microcontroller to a normal hat. It is able to detect objects with higher temperature (37.5 C)within 1 meter radius of 60° angle viewin stationary and non-stationary conditions. The wearable device communicates via Bluetooth to a mobile device to display the detected temperature and notifies the user via alert message and alarm for high temperature detection. Display of the object’s thermal image is also available with a resolution of 8 8 pixel. The wearable non-contact temperature detector is able to achieve 99% accuracy of temperature measurement for detection distance of up to 70 cm for indoor and within 20 cm for outdoor when tested with normal temperature subject and high temperature objectsand compared with the actual temperature detected via a commercial NCIT device.

Study on the Measurement Technique and Judgment Procedure of Ultrasonic Corona Imaging Equipment

Corona discharge is a phenomenon wherein gas on the surface of electrical equipment is ionised. Severe ionisation can lead to insulation breakdown and cause equipment damage. Consequently, non-contact portable devices are employed to detect corona discharge in real time while the electrical equipment is pressurised. Recently, several devices capable of visualising corona discharge phenomena occurring in the ultrasonic region have been developed. However, these devices are primarily used for scanning purposes to verify the occurrence of partial discharge, as detailed guidelines for operating the equipment in real-world field conditions are yet to be established. Therefore, this study proposes a measurement technique for utilising ultrasonic corona imaging diagnostic equipment in the field. This technique involves the use of corona discharge electrodes and aged epoxy insulator samples. First, the performance of the ultrasonic corona imaging diagnostic equipment based on environmental conditions was evaluated by varying the distance, frequency, temperature, and humidity using the corona discharge electrodes. Then, parallel measurements were conducted with a high-frequency current transformer sensor on epoxy insulator samples subjected to simple ageing, cracking, and partial surface damage, and the results were analysed. Finally, an efficient measurement technique, including equipment operation procedures, was proposed by integrating the measurement results.

Incubator-based active noise control device: comparison to ear covers and noise reduction zone quantification

BackgroundNoise exposure in the neonatal intensive care unit (NICU) is consistently higher than current recommendations. This may adversely affect neonatal sleep, weight gain, and overall health. We sought to evaluate the effect of a novel active noise control (ANC) system.MethodsAn ANC device’s noise reduction performance was compared to that of adhesively affixed foam ear covers in response to alarm and voice sounds in a simulated NICU environment. The zone of noise reduction of the ANC device was quantified with the same set of alarm and voice sounds.ResultsThe ANC device provided greater noise reduction than the ear covers in seven of the eight sound sequences tested in which a noise reduction greater than the just noticeable difference was achieved. For noise in the 500 Hz octave band, the ANC device exhibited consistent noise reduction throughout expected patient positions. It provided better performance for noise below 1000 Hz than above 1000 Hz.ConclusionsThe ANC device provided generally superior noise reduction to the ear covers and provided a zone of noise reduction throughout the range where an infant would be placed within an incubator. Implications for patient sleep and weight gain are discussed.ImpactActive noise control device can effectively reduce noise inside an infant incubator due to bedside device alarms.This is the first analysis of an incubator-based active noise control device and comparison to adhesively affixed silicone ear covers.A non-contact noise reduction device may be an appropriate means of reducing noise exposure of the hospitalized preterm infant.

Dry Ice Blasting Method as a Descaling

The scale removing process with acid, generally called as the pickling process, is accepted by the steel producers satisfactorily. However, most of the producers tend to develop scale removing process without acid due to the environmental regulations. In the related literature, some methods were studied for finding eco-friendly solutions. Although these studies seem to be promising, pickling process is still dominant as a descaling process before cold rolling applications. In this study, efficient surface cleaning method which is called as dry ice blasting method was used under different parameters on the carbon steel surface as it might be used instead of pickling process. Results of the experiments were studied by observing cross-sectional micro structure of samples. In addition, before destroying samples for hot mounting application, the surface topographies were measured by non-contact device. Finally, surface roughness values of the samples were showed on figures.

Improvement of the measuring ultrasonic electromagnetic-acoustic transducer

Based on the analysis of previously published research and studies, it has been established that despite their significant advantages over traditional “contact” sensors in measurements, testing and diagnostics of thin dielectric coated (via paint, plastic, etc.) metal products, the available electromagnetic-acoustic transducers provide insufficient sensitivity and significant uncontrolled (“dead”) zone. This situation complicates testing of thin sheets, pipes, shells, tanks etc., and sometimes makes it impossible to measure the remaining thickness of the metal.
 The analysis of available research has shown that the possibility of transducers sensitivity increases via traditional increase in the magnetic induction value, and the high-frequency current value is practically exhausted. At the same time, the prospects for improving the design of electromagnetic-acoustic transducers were determined. The problems of traditional transducers were solved through development of a new electronic control circuit. For this, the control unit was designed to be distributed between ultrasonic shear pulse excitation devices, and as a result, for the device of ultrasonic signals reflected from the metalwork reception, the device sensitivity was increased. In addition, to provide the possibility to test and measure thin metal product thickness, the electronic circuit was supplemented with means of interference suppression after the powerful supply of the high-frequency current of the converter, which allowed significantly reducing the “dead” zone.
 A special stand was constructed to experimentally test the capabilities of the transducer developed, including a powerful high-frequency current pulse generator, an amplifier of received ultrasonic pulses and a digital oscilloscope. It has been experimentally demonstrated that the new electronic circuit of the non-contact sensor allows it to be qualitatively matched with the probing pulse generator and the amplifier of the received ultrasonic packet signals. As a result, the sensitivity of the transducer was increased by 2.5...3 times in relation to the amplitudes of bottom pulses and interference. At the same time, the diagnostics of metal products with thickness 30...50% less than the traditional sensitivity threshold of non-contact device is ensured.

FedRadar: Federated Multi-Task Transfer Learning for Radar-Based Internet of Medical Things

Owing to increasing connected medical devices and rapid development of deep learning technologies, the Internet of Medical Things (IoMT) has attracted great attention for healthcare monitoring with intelligent sensors. Radar serves as a non-contact healthcare device, continuously measuring human’s vital signs and behavior to provide daily and comprehensive long-term record on health status. However, radar sensor data collected from various users and families usually involve sensitive personal information, while traditional deep learning technologies using IoMT radar data may present high privacy leakage risks. This paper proposes FedRadar, a novel federated multi-task transfer learning framework for radar-based heartbeat rate and activity monitoring in IoMT to solve these challenges. It deals with the decentralized structure, training personalized multi-task models collaboratively, combining the shared relevance knowledge of human’s physiological information while keeping personal radar data locally for privacy protection. First, the multi-task neural network is built on the spatial-temporal radar data to capture the potential relationship and shared representations between human’s vital sign and activity. Furthermore, the federated learning with knowledge transfer scheme is designed to achieve personalized local models by transferring coarse relevant features and keeping fine-grained individual information. Extensive experiments demonstrate the effectiveness and robustness of FedRadar with 2.8% and 2.5% superior than local training model respectively on the accuracy of heartbeat rate estimation and activity classification in realistic constructed radar datasets. In addition, FedRadar is extensible and suitable to continuously monitor multiple health indicators with privacy protection in IoMT. The FedRadar codes and constructed radar datasets are available on https://github.com/bupt-uwb/FedRadar.

Research on simulation and detection of space electric field distribution of deteriorated insulators in three-phase over-head transmission lines

Operation accidents caused by deteriorated insulators occur from time to time, which poses a direct threat to the safe and stable operation of transmission lines. Much research has been done at home and abroad on the degradation mechanism of deteriorated insulators, the electric field distribution characteristics of insulator strings and the influence of deteriorated insulators on the space electric field, but there is little research on the influence of three-phase electrification on the space electric field of insulator strings. Therefore, this paper studies the simulation and detection of electric field distribution of deteriorated insulators in three-phase transmission lines. First, the difference between three-phase electrification and single-phase electrification on the space electric field of insulator strings is simulated and analyzed, and the influence of deteriorated insulators on the space electric field distribution of insulator strings under three-phase electrification is studied. Second, based on simulation results, a detection method for deteriorated insulators in three-phase overhead trans-mission lines is proposed, and a non-contact space electric field measurement device based on Unmanned Aerial Vehicle (UAV) is developed. Finally, a Unmanned Aerial Vehicle inspection system is used to test the transmission lines in combination with an electric power department, and the simulation results and the effectiveness of the proposed detection method are verified. Results show the electric field distribution of insulator strings is obviously different between three-phase electrification and single-phase electrification, and when the detection distance is 300 mm, the proposed detection method and device can effectively identify deteriorated insulators in three-phase transmission lines.

Research on RBF neural network adaptive control of three-point contactless measuring device for CNC roller grinder

Abstract In order to improve the CNC roll grinder production efficiency, a novel three-point non-contact measurement device is proposed. An adaptive back-stepping control system that combines with a radial basis function neural network (RBFNN) was designed to control the measurement device working position and also to track the periodic reference movement trajectory. In the proposed control system, the RBFNN approximation and tracking ability are used to identify the unknown measuring device dynamic information. Then, the Lyapunov stability theorem is used to derive the adaptive online learning algorithm. All control algorithms are placed in the control chip based on the TMS320F28335 archive. The simulation results show that the proposed control system has a good control effect when applied to the three-point non-contact measuring device in CNC roll grinders.

Design of a Noncontact Torsion Testing Device Using Magnetic Levitation Mechanism

To facilitate torsion testing in special environments, a noncontact torsion testing device, where a noncontact torque can be transmitted to a specimen, was developed using magnetic levitation technology. A permanent magnetic gear is used to produce noncontact torque. In addition, four electromagnets and four attractive-type permanent magnetic bearings were employed to realize levitation; in more detail, the four electromagnets actively stabilized two levitation degrees of freedom (DoFs), while the four attractive-type permanent magnetic bearings passively stabilized four DoFs. Furthermore, a plant model considering the effect caused by the four attractive-type permanent magnetic bearings was built for the two levitation DoFs requiring active control. Based on the plant model, two PD-controllers were designed. Moreover, a control simulation was conducted to obtain appropriate PD-gains. Finally, experiments further validated the feasibility of the whole scheme, and it was proven that the device can apply a 0.126 N·m torque to the specimen while maintaining levitation.

Geriatric Care Management System Powered by the IoT and Computer Vision Techniques.

The digitalisation of geriatric care refers to the use of emerging technologies to manage and provide person-centered care to the elderly by collecting patients' data electronically and using them to streamline the care process, which improves the overall quality, accuracy, and efficiency of healthcare. In many countries, healthcare providers still rely on the manual measurement of bioparameters, inconsistent monitoring, and paper-based care plans to manage and deliver care to elderly patients. This can lead to a number of problems, including incomplete and inaccurate record-keeping, errors, and delays in identifying and resolving health problems. The purpose of this study is to develop a geriatric care management system that combines signals from various wearable sensors, noncontact measurement devices, and image recognition techniques to monitor and detect changes in the health status of a person. The system relies on deep learning algorithms and the Internet of Things (IoT) to identify the patient and their six most pertinent poses. In addition, the algorithm has been developed to monitor changes in the patient's position over a longer period of time, which could be important for detecting health problems in a timely manner and taking appropriate measures. Finally, based on expert knowledge and a priori rules integrated in a decision tree-based model, the automated final decision on the status of nursing care plan is generated to support nursing staff.

Application of intraoperative infrared thermography in bypass surgery for adult moyamoya syndrome: A preliminary study.

Cerebral revascularization surgery is the mainstay of treatment for moyamoya syndrome (MMS) today, and intraoperative determination of the patency of the revascularized vessel is a critical factor in the success of the procedure. Currently, major imaging modalities include intraoperative indocyanine green (ICG) videoangiography (ICG-VA), digital subtraction angiography (DSA), and vascular ultrasound Doppler. Infrared thermography is a modern imaging modality with non-contact devices for the acquisition and analysis of thermal data. We aimed to investigate the feasibility and advantages of infrared thermography in determining anastomotic patency during MMS surgery. Indocyanine green videoangiography and infrared thermography were performed simultaneously in 21 patients with MMS who underwent bypass surgery. The detection result of vessel patency was compared, and the feasibility and advantages of infrared thermography were assessed. The patency of the anastomosis was accurately determined in 21 patients using either ICG angiography or infrared thermography. In 20 patients, the results of infrared thermography showed that the vascular anastomosis was unobstructed, and there was an agreement with the subsequent results of ICG-VA. In one patient, we suspected inadequate patency after testing the anastomosis with infrared thermography, and the results of ICG-VA evaluation of the anastomosis confirmed that there was indeed an anastomotic obstruction. Compared with ICG-VA, infrared thermography might offer an alternative non-invasive, contrast-free option in assessing anastomosis patency compared with ICG-VA, and it is likely to become more widely used in the clinic in the near future.

Non-Contact and Non-Intrusive Add-on IoT Device for Wireless Remote Elevator Control

This work proposes an Internet-of-Things (IoT) device for remote elevator control. The new contribution of this proposal to the state-of-the-art is that it can convert a manually operated elevator into a remote controlled elevator without requiring any intrusive manipulation or wiring connection in the elevator. This IoT device has been designed as an add-on non-contact tool which is placed over the original elevator button panel, using servomotors to press the original buttons. This design allows its fast deployment as a remote control tool that increases elevator accessibility through the use of messages, a webpage or a QR code. Some application examples of this proposal are non-contact use of elevators in pandemic conditions, and the unsupervised use of elevators by autonomous cleaning or delivery mobile robots. The experimental evaluation of the IoT device in real operational conditions has validated its non-contact control features.

Recent Progress in Long-Term Sleep Monitoring Technology.

Sleep is an essential physiological activity, accounting for about one-third of our lives, which significantly impacts our memory, mood, health, and children's growth. Especially after the COVID-19 epidemic, sleep health issues have attracted more attention. In recent years, with the development of wearable electronic devices, there have been more and more studies, products, or solutions related to sleep monitoring. Many mature technologies, such as polysomnography, have been applied to clinical practice. However, it is urgent to develop wearable or non-contacting electronic devices suitable for household continuous sleep monitoring. This paper first introduces the basic knowledge of sleep and the significance of sleep monitoring. Then, according to the types of physiological signals monitored, this paper describes the research progress of bioelectrical signals, biomechanical signals, and biochemical signals used for sleep monitoring. However, it is not ideal to monitor the sleep quality for the whole night based on only one signal. Therefore, this paper reviews the research on multi-signal monitoring and introduces systematic sleep monitoring schemes. Finally, a conclusion and discussion of sleep monitoring are presented to propose potential future directions and prospects for sleep monitoring.

Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study.

Dry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartphone app, namely, the DEA01, has been developed as a noninvasive, noncontact, and remote screening device, in the context of an ongoing paradigm shift in the health care system, to facilitate a diagnosis of DED. This study aimed to evaluate the capabilities of the DEA01 smartphone app to facilitate a DED diagnosis. In this multicenter, open-label, prospective, and cross-sectional study, the test method will involve using the DEA01 smartphone app to collect and evaluate DED symptoms, based on the Japanese version of the Ocular Surface Disease Index (J-OSDI), and to measure the maximum blink interval (MBI). The standard method will then involve a paper-based J-OSDI evaluation of subjective symptoms of DED and tear film breakup time (TFBUT) measurement in an in-person encounter. We will allocate 220 patients to DED and non-DED groups, based on the standard method. The primary outcome will be the sensitivity and specificity of the DED diagnosis according to the test method. Secondary outcomes will be the validity and reliability of the test method. The concordance rate, positive and negative predictive values, and the likelihood ratio between the test and standard methods will be assessed. The area under the curve of the test method will be evaluated using a receiver operating characteristic curve. The internal consistency of the app-based J-OSDI and the correlation between the app-based J-OSDI and paper-based J-OSDI will be assessed. A DED diagnosis cutoff value for the app-based MBI will be determined using a receiver operating characteristic curve. The app-based MBI will be assessed to determine a correlation between a slit lamp-based MBI and TFBUT. Adverse events and DEA01 failure data will be collected. Operability and usability will be assessed using a 5-point Likert scale questionnaire. Patient enrollment will start in February 2023 and end in July 2023. The findings will be analyzed in August 2023, and the results will be reported from March 2024 onward. This study may have implications in identifying a noninvasive, noncontact route to facilitate a diagnosis of DED. The DEA01 may enable a comprehensive diagnostic evaluation within a telemedicine setting and facilitate early intervention for undiagnosed patients with DED confronting health care access barriers. Japan Registry of Clinical Trials jRCTs032220524; https://jrct.niph.go.jp/latest-detail/jRCTs032220524. PRR1-10.2196/45218.

Non-invasive estimation of hemoglobin, bilirubin and oxygen saturation of neonates simultaneously using whole optical spectrum analysis at point of care

The study was aimed to evaluate the performance of a newly developed spectroscopy-based non-invasive and noncontact device (SAMIRA) for the simultaneous measurement of hemoglobin, bilirubin and oxygen saturation as an alternative to the invasive biochemical method of blood sampling. The accuracy of the device was assessed in 4318 neonates having incidences of either anemia, jaundice, or hypoxia. Transcutaneous bilirubin, hemoglobin and blood saturation values were obtained by the newly developed instrument which was corroborated with the biochemical blood tests by expert clinicians. The instrument is trained using Artificial Neural Network Analysis to increase the acceptability of the data. The artificial intelligence incorporated within the instrument determines the disease condition of the neonate. The Pearson’s correlation coefficient, r was found to be 0.987 for hemoglobin estimation and 0.988 for bilirubin and blood gas saturation respectively. The bias and the limits of agreement for the measurement of all the three parameters were within the clinically acceptance limit.