External Sensors Research Articles

MHealth in sub-Saharan Africa and Europe: A systematic review comparing the use and availability of mHealth approaches in sub-Saharan Africa and Europe.

mHealth can help with healthcare service delivery for various health issues, but there's a significant gap in the availability and use of mHealth systems between sub-Saharan Africa and Europe, despite the ongoing digitalization of the global healthcare system. This work aims to compare and investigate the use and availability of mHealth systems in sub-Saharan Africa and Europe, and identify gaps in current mHealth development and implementation in both regions. The study adhered to the PRISMA 2020 guidelines for article search and selection to ensure an unbiased comparison between sub-Saharan Africa and Europe. Four databases (Scopus, Web of Science, IEEE Xplore, and PubMed) were used, and articles were evaluated based on predetermined criteria. Details on the mHealth system type, goal, patient type, health concern, and development stage were collected and recorded in a Microsoft Excel worksheet. The search query produced 1020 articles for sub-Saharan Africa and 2477 articles for Europe. After screening for eligibility, 86 articles for sub-Saharan Africa and 297 articles for Europe were included. To minimize bias, two reviewers conducted the article screening and data retrieval. Sub-Saharan Africa used SMS and call-based mHealth methods for consultation and diagnosis, mainly for young patients such as children and mothers, and for issues such as HIV, pregnancy, childbirth, and child care. Europe relied more on apps, sensors, and wearables for monitoring, with the elderly as the most common patient group, and the most common health issues being cardiovascular disease and heart failure. Wearable technology and external sensors are heavily used in Europe, whereas they are seldom used in sub-Saharan Africa. More efforts should be made to use the mHealth system to improve health outcomes in both regions, incorporating more cutting-edge technologies like wearables internal and external sensors. Undertaking context-based studies, identifying determinants of mHealth systems use, and considering these determinants during mHealth system design could enhance mHealth availability and utilization.

Investigation of the genetic algorithm in the correction scheme of inertial navigation systems in the conditions of the disappearance of signals from external sensors

A scheme for correcting inertial navigation systems in the output signal at the signals disappearance from external sensors of navigation information is considered. The correction is carried out by using predictive error models of the inertial navigation system built by using a genetic algorithm. Measurement accesses of genetic algorithms used for short-term, medium-term and long-term error prediction of inertial navigation systems are studied. Factors that influence the accuracy of predictive models are identified. Recommendations for the practical use of genetic algorithms in the correction scheme of inertial navigation systems are formulated. Keywords inertial navigation system, absence of external signals, correction, genetic algorithm, measuring access, short-term forecast, long-term forecast, recommendations

Event-Triggered Pose Synchronization in SE(3) for Cooperating Multi-Robot Teams

Consensus and synchronization are fundamental concepts for the coordination of cooperating multi-robot teams. Applications like cooperative manipulation may require not only synchronization of the position, but also of the orientation of the individual agents. The pose of the agent can be described within the special Euclidean group and common results for coordination have to be adapted. We propose a control framework for full-pose synchronization in SE(3) for a team of Euler-Lagrange agents, relying only on relative information in the absence of a global coordinate frame. The framework consists of an inner loop for feedback linearization and an outer loop for pose synchronization. The measurements are taken by external sensors and communicated to the respective agents via a common communication network. To deal with limited communication bandwidth, we propose an event-triggered update strategy for the relative measurements. Finally, the efficacy of the proposed control and triggering law is illustrated in simulations.

Interim results of the H2020 3beLiEVe project: battery material selection, cell prototyping, battery module and pack design and manufacturing process modelling for Generation 3b LNMO cells

This paper presents selected interim results of the H2020 project 3beLiEVe, which aims to deliver next-generation Lithium-Nickel-Manganese-Oxide (Generation 3b) battery cells for automotive applications, encompassing research activities across three pillars: (i) Selection and optimisation of the cathode (LNMO) and anode (Si/C) materials, as well as the high-voltage electrolyte, (ii) development and integration of cell-internal and external sensors, and demonstration at cell, module and pack level, (iii) demonstration of large-scale manufacturing capability and compatibility with a circular economy. This article shows selected results of the project achieved so far in these three pillars, aiming to inform the scientific community about some of the latest achievements of European research on Generation 3b Li-ion batteries.

Linear Parameter Varying Controller Design For Satellite Attitude Control*

This paper presents a systematic linear parameter varying (LPV) control approach for the 3-axis attitude control of an Earth-observation satellite in a sun-synchronous orbit. The dynamics of the satellite depend on the orientation of the solar array which completes a full rotation every orbit, thus it is used as a scheduling parameter in the design. The satellite has two additional flexible appendages; these are 2 scatterometers. The control objective is to precisely track a given reference attitude using reaction wheels, while rejecting external torque disturbances and sensor noise. The design follows a mixed-sensitivity approach, applying a recently introduced weighting scheme. It allows traceable and effective controller tuning by using a low number of physically interpretable weights. The controller is synthesised by solving the induced L2-norm of the closed-loop interconnection of the controller and weighted plant. Scheduling with the solar array orientation leads to an LPV notching behaviour in the controller that effectively mitigates the effects of the array's most prominent flexible modes. This behaviour enables increased performance, when compared to a linear time invariant controller, while maintaining robustness. The pointing performance of the synthesised controller over the complete satellite lifecycle is verified using the European Space Agency's standards for spacecraft attitude control.

Curving Motion Control of a Traction Rail Mover Using a Dual BLAC Motor Drive

This article presents an improved position control method of an overhang-type rail system considering a curved path. The designed system is driven by two BLAC (brushless ac) motors, and the moving position is controlled based on the signal from a simple Hall position sensor mounted on the motor without any absolute position sensors. The rail is composed of both linear and curved paths. For the linear rail, the two motors are controlled to rotate in the same speed. However, in a curved path, the two motors must have different moving distance according to the curvature. Generally, in order to determine the proper motion commands for both traction motors, the actual curvature state and position have to be detected by a potentiometer or an encoder equipped with linear position sensor, but this method significantly increases complexity and cost of the system. This article aims to solve this problem by using a low-cost semiconductor IMU (inertia measurement unit) to estimate the actual rail condition. The IMU will then estimate the heading angle variation to compensate the motion commands for the two BLAC motors without any additional external absolute sensors. As a result, a balanced and improved motion can be achieved for an arbitrary rail path. Practical experiments using an overhang-type rail traction system were performed to verify the effectiveness of the proposed control scheme. The results show the advanced control performance in both linear and curved path, and also a smooth transition between them both.

RISE: an open-source architecture for interdisciplinary and reproducible human-robot interaction research.

In this article, we present RISE-a Robotics Integration and Scenario-Management Extensible-Architecture-for designing human-robot dialogs and conducting Human-Robot Interaction (HRI) studies. In current HRI research, interdisciplinarity in the creation and implementation of interaction studies is becoming increasingly important. In addition, there is a lack of reproducibility of the research results. With the presented open-source architecture, we aim to address these two topics. Therefore, we discuss the advantages and disadvantages of various existing tools from different sub-fields within robotics. Requirements for an architecture can be derived from this overview of the literature, which 1) supports interdisciplinary research, 2) allows reproducibility of the research, and 3) is accessible to other researchers in the field of HRI. With our architecture, we tackle these requirements by providing a Graphical User Interface which explains the robot behavior and allows introspection into the current state of the dialog. Additionally, it offers controlling possibilities to easily conduct Wizard of Oz studies. To achieve transparency, the dialog is modeled explicitly, and the robot behavior can be configured. Furthermore, the modular architecture offers an interface for external features and sensors and is expandable to new robots and modalities.

АВТОМАТИЗИРОВАННАЯ СИСТЕМА СТАРТА ЗАБЕГОВ И КОНТРОЛЯ ЛЕГКОАТЛЕТОВ НА ТРЕНИРОВКАХ И СОРЕВНОВАНИЯХ

This paper is about developing a time event system at competitions with the athletes and the start-finish identification. To implement the system, widely used integrated systems-on-achip or modules are used, which are a microcontroller with a digital transceiver, accelerometers, gyroscopes and other integrated or external microdevices and sensors, for example, an oximeter, breath sensor, galvanic skin response and others, which are connected to analog -digital converter of the controller or digital port.

Automatic control system for automatic maintenance of microclimate in vegetable storages

The paper presents an automatic control system for automatic maintenance of the desired microclimate in the storage, controlled by a computer. The state of the microclimate in the vegetable store is monitored with the product and channel temperature sensors and internal and external humidity sensors. This system will automatically control the ventilation parameters at different times of the year, and regulate humidity conditions.

External UHF Sensor for GIS PD Insulation Defect from Resin Hole

In view of the effective perception demand of PD (Partial Discharge) insulation defect of in-service GIS (Gas Insulated Switchgear), the external UHF (Ultra High Frequency, 0.3−3 GHz) sensing technology for GIS PD insulation defect from resin hole is studied in this paper. Firstly, rectangular waveguide theory is used to analyze the electromagnetic wave propagation characteristics from rectangular resin hole in GIS disc insulator. It is found that the energy of leaked electromagnetic wave mainly concentrates in the frequency band above 1 GHz. Then based on this frequency band characteristics, a cavity-backed bowtie sensor for GIS PD external detection is designed optimized by HFSS finite element software, in band of 1–3 GHz, its maximum VSWR is 7, the minimum is 1.1, the average is 2.9, and in band of 0.3–1 GHz, the maximum and minimum VSWR is 42.8 and 7, the average is 20.6. Finally, a sensor prototype is made, its sensitivity experiment is carried out on 220 kV GIS, experimental results show that the designed sensor can stably detect the PD electromagnetic wave signal leaked from the resin hole, and the signal energy in frequency band range is consistent with the theoretical analysis results.

Robust Attitude Estimation Using Magnetic and Inertial Sensors

Lightweight and low-cost magnetic and inertial sensors are commonly used for attitude estimation in a wide range of applications, from motion tracking to autonomous navigation. However, the inherent and external sensor errors and the accelerations due to the actual motion of the platform highly affect the estimation accuracy. This study proposes a robust attitude estimation algorithm that compensates the sensor errors and the external accelerations at the algorithm level. The attitude estimation filter, which is structured as a Multiplicative Extended Kalman Filter (MEKF), is modified to compensate for both the long-term and short-term measurement uncertainties. Modification is applied mainly by estimating and compensating the bias and external accelerations for long-term uncertainties and tuning the measurement noise covariance matrix for short-term uncertainties. Simulations test the proposed algorithm, and the results are compared with benchmark algorithms.

외부 시스템을 이용한 Monocular camera-3D LiDAR 융합 시스템의 Non-overlapping 외부 교정 방법에 대한 연구

This study presents a novel framework for the extrinsic calibration of monocular camera and LiDAR with a non-overlapping field of view. The conventional non-overlapping extrinsic calibration utilizes a motion-based calibration method. However, motion-based calibration has a disadvantage in that the vehicle must be moving. In order to solve extrinsic calibration problems under such constraint configurations, the proposed solution uses external sensors that are located away from vehicle. First, the external camera and vehicle camera utilize an aruco marker. Second, the external LiDAR and vehicle LiDAR utilize a scan matching method. In this study, a Gazebo simulator was utilized to show the accuracy of the proposed method. The external LiDAR used Velodyne HDL 64ch, the vehicle LiDAR used Puck 16ch, and the camera used the Blackfly color sensor from FLIR.

Spiral Spring-Supported Force Plate with an External Eddy Current Displacement Sensor

This study proposes a force plate with a planar spring and an eddy current displacement sensor to measure the ground reaction force (GRF) of a small insect and reveal its motion characteristics. The proposed force plate comprises a circular aluminum plate, four aluminum springs symmetrically connected to the plate, and an eddy current displacement sensor under the plate. The diameter and thickness of the fabricated plate were 8 and 0.1 mm, respectively. The spring width was 0.4 mm. When a force is applied to the plate, the plate moves vertically downward. Then, an eddy current displacement sensor detects the plate displacement without contact. The applied force can be measured using Hooke’s law. The proposed force plate has the advantages of ease of fabrication and cost-effectiveness. The central displacement variation and resonant frequency of the designed springs were evaluated by simulation. Then, we calibrated the fabricated force plate to obtain the sensitivity variation and resonant frequency. The experimental results suggest that the proposed force plate can effectively measure the GRF of a small insect.

A Training Smartphone Application for the Simulation of Outdoor Blind Pedestrian Navigation: Usability, UX Evaluation, Sentiment Analysis.

Training blind and visually impaired individuals is an important but often neglected aspect of Assistive Technology solutions (ATs) that can benefit from systems utilizing multiple sensors and hardware devices. Training serves a dual purpose as it not only enables the target group to effectively utilize the ATs but, also, helps in improving their low acceptance rate. In this paper, we present the design, implementation, and validation of a smartphone-based training application. It is a form of immersive system that enables users to learn the features of an outdoor blind pedestrian navigation application and, simultaneously, to help them develop long-term Orientation and Mobility (O&M) skills. The system consists of an Android application leveraging, as data sources, an external high-accuracy GPS sensor for real-time pedestrian mobility tracking, a second custom-made device attached to traffic lights for identifying their status, and an ultra-sonic sensor for detecting near-field obstacles on the navigation path of the users. The training version running as an Android application employs route simulation with audio and haptic feedback, is functionally equivalent to the main application, and was used in the context of specially designed user-centered training sessions. A Usability and User Experience (UX) evaluation revealed the positive attitude of the users towards the training version as well as their satisfaction with the skills acquired during their training sessions (SUS = 69.1, UEQ+ = 1.53). Further confirming the positive attitude was the conduct of a Recursive Neural Network (RNN)-based sentiment analysis on user responses with a score of 3 on a scale from 0 to 4. Finally, we conclude with the lessons learned and the proposal of general design guidelines concerning the observed lack of accessibility and non-universal interfaces.

Acquisition of Field Data through Mobile-based Apps Dedicated to Soil Health Protection

Mobile applications dedicated to soil resource protection are increasingly common among users worldwide. What makes them popular among them is the possibility they offer in the acquisition, respectively saving and storing data from the field. Regarding the possibility of acquiring soil resource data, we propose to make an analysis, to emphasize the malleable nature of specific mobile applications with what software development platforms allow; for the present paper, we examined an application created through the MIT App Inventor® platform. As a result of the research, three ways of data acquisition were determined - through the interface, internal sensors, and external sensors. The obtained results showed that the acquisition of soil-related data depends to a large extent on the specifics of mobile devices (especially the presence and access of sensors), but also on the implemented functionalities that the user wants to have access to at that time. Consequently, any application created through platforms such as MIT App Inventor® can and must have at least one of the data acquisition methods presented in the paper; the dynamics and specificity of the application must agree with the user requirements and the requirements imposed by the research context.

ThumbAir

Typing while wearing a standalone Head Mounted Display (HMD)---systems without external input devices or sensors to support text entry---is hard. To address this issue, prior work has used external trackers to monitor finger movements to support in-air typing on virtual keyboards. While performance has been promising, current systems are practically infeasible: finger movements may be visually occluded from inside-out HMD based tracking systems or, otherwise, awkward and uncomfortable to perform. To address these issues, this paper explores an alternative approach. Taking inspiration from the prevalence of thumb-typing on mobile phones, we describe four studies exploring, defining and validating the performance of ThumbAir, an in-air thumb-typing system implemented on a commercial HMD. The first study explores viable target locations, ultimately recommending eight targets sites. The second study collects performance data for taps on pairs of these targets to both inform the design of a target selection procedure and also support a computational design process to select a keyboard layout. The final two studies validate the selected keyboard layout in word repetition and phrase entry tasks, ultimately achieving final WPMs of 27.1 and 13.73. Qualitative data captured in the final study indicate that the discreet movements required to operate ThumbAir, in comparison to the larger scale finger and hand motions used in a baseline design from prior work, lead to reduced levels of perceived exertion and physical demand and are rated as acceptable for use in a wider range of social situations.

In-Cabin MIMO Radar System for Human Dysfunctional Breathing Detection

The integration of wireless sensors into the automotive industry is making vehicles increasingly safe and autonomous. At present, vehicles are equipped with external sensors that facilitate maneuverability and braking and internal sensors that detect presence, seat belt state, and occupant vital signs. Early detection of dysfunctional breathing patterns can reduce the risk of accidents caused by drowsiness or fatigue. In this regard, this work presents an MIMO FMCW Radar System able to distinguish dysfunctional breathing patterns from human torso motion. The torso has been divided into six regions, and the amplitude of the elongation and the frequency of motion of each region have been measured during breathing. An elongation map is then constructed in order to graphically show the dysfunctional breathing patterns. The signal processing includes a peak search algorithm to detect elongation amplitude and a bandpass frequency filter to minimize dc components, random driver motion, and vehicle vibration. A torso elongation emulator phantom has been assembled with materials of skin-like relative permittivity and dc motors for calibration and validation of basic breathing patterns. Finally, the signal of the system is compared with that of a commercial respiration belt, and then the system is tested by performing measurements on people. The MIMO radar system is able to measure, differentiate, and classify patterns associated with dysfunctional breathing such as hyperventilation syndrome and thoracic dominant breathing.

LED Screen-Based Intelligent Hand Gesture Recognition System

Common human–computer interaction (HCI) modes rely on various sensors or cameras for operation. This study proposes a gesture recognition method and device based on light sensing characteristics, which removes the need for external sensors with only light-emitting diode (LED) screens. The key technique is that the photoelectric sensing ability of LED is applied to detect the information change of light without interference to the display function, thus indicating the variation of gestures. This system is integrated by using six LED screen modules with the field-programmable gate array (FPGA) to control display and collect data for deep-learning analysis. Depending on both time- and frequency-domain characteristics of gestures, the recognition algorithm is implemented based on static bidirectional long short-term memory (S-Bi-LSTM). As revealed by the experiments conducted on hand gestures of different people and under the context of complex background illumination, the accuracy of gesture recognition reaches as high as 93.60%. As for dynamic gesture actions, an optimized dynamic bidirectional long short-term memory (D-Bi-LSTM) algorithm is also proposed with the method of frame segmentation. This method divides dynamic gestures into three parts to feed different classifiers, so as to enhance the accuracy of dynamic gestures recognition up to 91.67%. The device possesses all the structures of a large LED screen, which verifies the feasibility of pattern recognition for large LED screens from an experimental perspective. Without any need for traditional sensors, it is contactless, secure, and easy to promote.

Disturbance-Observer-Based Dual-Position Feedback Controller for Precision Control of an Industrial Robot Arm

Recently, the fourth industrial revolution has accelerated the application of multiple degrees-of-freedom (DOF) robot arms in various applications. However, it is difficult to utilize robot arms for precision motion control because of their low stiffness. External loads applied to robot arms induce deflections in the joints and links, which deteriorates the positioning accuracy. To solve this problem, control methods using a disturbance observer (DOB) with an external sensory system have been developed. However, external sensors are expensive and have low reliability because of noise and reliance on the surrounding environment. A disturbance-observer-based dual-position feedback (DOB-DPF) controller is proposed herein to improve the positioning accuracy by compensating for the deflections in real time using only an internal sensor. The DOB was designed to derive the unpredictable disturbance torque applied to each joint using the command voltage generated by the position controller. The angular deflection of each joint was calculated based on the disturbance torque and joint stiffness, which were identified experimentally. The DPF controller was designed to control the joint motor while simultaneously compensating for angular deflection. A five-DOF robot arm testbed with a position controller was constructed to verify the proposed controller. The contouring performance of the DOB-DPF controller was compared with that of a conventional position controller with an external load applied to the end effector. The increases in the root mean square values of the contour errors were 1.71 and 0.12 mm with a conventional position controller and the proposed DOB-DPF controller, respectively, after a 2.2 kg weight was applied to the end effector. The results show that the contour error caused by the external load is effectively compensated for by the DOB-DPF controller without an external sensor.

Saliency-Based Rotor Spatial Position Displacement Self-Sensing for Self-Bearing Machines.

Self-bearing machines do not contain physical bearings but magnetic bearings. Both rotor rotary and spatial positions displacement are required in these types of machines to control the rotor position while it is levitating. Self-bearing machines often use external sensors for x (horizontal) and y (vertical) spatial position measurement, which will result in additional cost, volume, complexity, and number of parts susceptible to failure. To overcome these issues, this paper proposes a xy-position estimation self-sensing technique based on both main- and cross-inductance variation. The proposed method estimates x and y position based on inductive saliency between two sets of three-phase coils. The proposed idea is applied on a combined winding self-bearing machine which does not require additional suspension force winding. No additional search coil placement for xy-position estimation is required. Therefore, the proposed algorithm can result in a compact size self-bearing machine that does not require external sensors for xy-position measurement and suspension force winding.