2D Quantitative Imaging of Magnetic Nanoparticles by an AC Biosusceptometry Based Scanning Approach and Inverse Problem

The use of magnetic nanoparticles (MNPs) in biomedical applications requires the quantitative knowledge of their quantitative distribution within the body. AC Biosusceptometry (ACB) is a biomagnetic technique recently employed to detect MNPs in vivo by measuring the MNPs response when exposed to an alternate magnetic field. The ACB technique presents some interesting characteristics: non-invasiveness, low operational cost, high portability, and no need for magnetic shielding. ACB conventional methods until now provided only qualitative information about the MNPs’ mapping in small animals. We present a theoretical model and experimentally demonstrate the feasibility of ACB reconstructing 2D quantitative images of MNPs’ distributions. We employed an ACB single-channel scanning approach, measuring at 361 sensor positions, to reconstruct MNPs’ spatial distributions. For this, we established a discrete forward problem and solved the ACB system’s inverse problem. Thus, we were able to determine the positions and quantities of MNPs in a field of view of 5×5×1 cm3 with good precision and accuracy. The results show the ACB system’s capabilities to reconstruct the quantitative spatial distribution of MNPs with a spatial resolution better than 1 cm, and a sensitivity of 1.17 mg of MNPs fixed in gypsum. These results show the system’s potential for biomedical application of MNPs in several studies, for example, electrochemical-functionalized MNPs for cancer cell targeting, quantitative sensing, and possibly in vivo imaging.

Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices

The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO2, humidity, and illuminance. The results show that the positions of PIR and CO2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.

WR-Hand

This paper presents WR-Hand, a wearable-based system tracking 3D hand pose of 14 hand skeleton points over time using Electromyography (EMG) and gyroscope sensor data from commercial armband. This system provides a significant leap in wearable sensing and enables new application potentials in medical care, human-computer interaction, etc. A challenge is the armband EMG sensors inevitably collect mixed EMG signals from multiple forearm muscles because of the fixed sensor positions on the device, while prior bio-medical models for hand pose tracking are built on isolated EMG signal inputs from isolated forearm spots for different muscles. In this paper, we leverage the recent success of neural networks to enhance the existing bio-medical model using the armband's EMG data and visualize our design to understand why our solution is effective. Moreover, we propose solutions to place the constructed hand pose reliably in a global coordinate system, and address two practical issues by providing a general plug-and-play version for new users without training and compensating for the position difference in how users wear their armbands. We implement a prototype using different commercial armbands, which is lightweight to execute on user's phone in real-time. Extensive evaluation shows the efficacy of the WR-Hand design.

Maximum Correntropy Criterion for Robust TOA-Based Localization in NLOS Environments

We investigate the problem of time-of-arrival (TOA)-based localization under possible non-line-of-sight (NLOS) propagation conditions. To robustify the squared-range-based location estimator, we follow the maximum correntropy criterion, essentially the Welsch M-estimator with a redescending influence function which behaves like $$\ell _0$$ ℓ 0 -minimization toward the grossly biased measurements, to derive the formulation. The half-quadratic technique is then applied to settle the resulting optimization problem in an alternating maximization (AM) manner. By construction, the major computational challenge at each AM iteration boils down to handling an easily solvable generalized trust region subproblem. It is worth noting that the implementation of our localization method requires nothing but merely the TOA-based range measurements and sensor positions as prior information. Simulation and experimental results demonstrate the competence of the presented scheme in outperforming several state-of-the-art approaches in terms of positioning accuracy, especially in scenarios, where the percentage of NLOS paths is not large enough.

Mathematical Considerations for Unmanned Aerial Vehicle Navigation in the Magnetic Field of Two Parallel Transmission Lines

This publication deals with the navigation of unmanned aerial vehicles (UAVs) moving in the magnetic field of two long, straight, parallel conductors, which is of high interest for several new technical applications. How the position and orientation of the UAV can be calculated using a minimal number of only three three-axis magnetometers are discussed. It is shown that the angles can be determined without the knowledge of the conductor currents and the magnetic field equations, but only by combining the sensor measurements with the rotation matrix and exploiting a characteristic property of the magnetic field. Furthermore, different strategies were investigated to determine the respective sensor positions. An analytical solution was derived from the nonlinear magnetic field equations, which promises a low computational time. It is shown that for a given sensor, several solutions exist, from which the correct one has to be selected. Therefore, a specific detection method is introduced. Once the solution is known, the UAV location can be determined. Finally, the overall algorithm was tested by simulations far from and near the conductors with superimposed typical magnetic noise.

Measurement of Physical Activity by Shoe-Based Accelerometers—Calibration and Free-Living Validation

There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, validate the performance in a workplace setting and compare it to the most commonly used accelerometer positions. Models for EE estimation were calibrated in a laboratory setting for the shoe, hip, thigh and wrist worn accelerometers. These models were validated in a free-living workplace setting. Furthermore, additional models were developed from free-living data. All sensor positions performed well in the laboratory setting. When the calibration models derived from laboratory data were validated in free living, the shoe, hip and thigh sensors displayed higher correlation, but lower agreement, with measured EE compared to the wrist sensor. Using free-living data for calibration improved the agreement of the shoe, hip and thigh sensors. This study suggests that the performance of a shoe-based accelerometer is similar to the most commonly used sensor positions with regard to PA measurement. Furthermore, it highlights limitations in using the relationship between accelerometer output and EE from a laboratory setting to estimate EE in a free-living setting.

UAV-based aeromagnetic gradient measurements and inversion

<p>Rotary wing UAV’s are used in aeromagnetic measurements for UXO detection. That way, contaminated areas can be mapped fast and with high resolution. Until today, only the total magnetic intensity (TMI) is evaluated, even when a three axis fluxgate magnetometer is flown. In this project, we use two three component fluxgate sensors, an inertial measurement unit (IMU) and a GPS antenna. The IMU allows for a projection of the magnetic data into the geographic coordinate system as well as the calculation of the sensor positions relative to the GPS antenna. With this system, it is possible for the first time to evaluate the component gradients between the magnetometers.</p><p>The sensors are attached to the UAV via a versatile, T-shaped boom hanging below the UAV with the sensors positioned in a horizontal distance of 50 cm. The total mass of the flight system is about 5 kg with an air time of 15 minutes.</p><p>For the inversion, we use a dipole model which calculates the magnetic data for all sensor positions. Because the sources of the magnetic anomalies are unknown as a general rule, there is no distinction between induced and remanent magnetisation. Instead, the three components of the magnetic moment are fitted alongside the positions of the anomaly sources. The number of dipoles to be fitted and their initial parameters are arbitrary. For the inversion, the TMI and component gradients between the sensors are considered.</p><p>In order to analyse the accuracy of the complete system, we conducted surveys over a test field of 100 x 20 m, separated into four sections with varying anomaly configurations. As anomaly sources, we used neodymium magnets which we characterised in laboratory measurements. For optimal coverage and to compare flight directions, the test field was surveyed both lengthways and crossways with a sensor height of 1.5 m above ground. Inversion results show that when component gradients are used, overlapping anomalies can be separated and parameterised. The mean errors of the derived anomaly positions are 5 cm, the total magnetic moment can be determined with an accuracy of 0.35 Am<sup>2</sup>, whereby the errors in direction (declination and inclination) are 4 ° and 2 °, respectively.</p>