63 research outputs found

    Lattice dynamics effects on the magnetocrystalline anisotropy energy: application to MnBi

    Full text link
    Using a first-principles fully relativistic scheme based on ultrasoft pseudopotentials and density functional perturbation theory, we study the magnetocrystalline anisotropy free energy of the ferromagnetic binary compound MnBi. We find that differences in the phonon dispersions due to the different orientations of the magnetization (in-plane and perpendicular to the plane) give a difference between the vibrational free energies of the high-temperature and low-temperature phases. This vibrational contribution to the magnetocrystalline anisotropy energy (MAE) constant, KuK_u, is non-negligible. When the energy contribution to the MAE is calculated by the PBEsol exchange and correlation functional, the addition of the phonon contribution allows to get a T=0T = 0 K KuK_u and a spin-reorientation transition temperature in reasonable agreement with experiments.Comment: 6 pages, 4 figures, 2 table

    Spectral and time-frequency domains features for quantitative lower-limb rehabilitation monitoring via wearable inertial sensors

    Get PDF
    Inertial data represent a rich source of clinically relevant information which can provide details on motor assessment in subjects involved in a rehabilitation process. Thus, a number of metrics in the spectral and time-frequency domain has been considered to be reliable for measuring and quantifying patient progress and has been applied on the 3D accelerometer and angular rate signals collected on one impaired subject with knee injury through a wearable wireless inertial sensing system developed at the Tyndall National Institute. The subject has performed different activities evaluated across several sessions over time. Data show that most of the studied features can provide a quantitative analysis of the improvement of the subject along rehabilitation, and differentiate between impaired and unimpaired limb motor performance. The work proves that the studied features can be taken into account by clinicians and sport scientists to study the overall patients' condition and provide accurate clinical feedback as to their rehabilitative progress. The work is ongoing and additional clinical trials are currently being planned with an enhanced number of injured subjects to provide a more robust statistical analysis of the data in the study

    Inertial sensors-based lower-limb rehabilitation assessment: A comprehensive evaluation of gait, kinematic and statistical metrics

    Get PDF
    Analysis of biomechanics is frequently used in both clinical and sporting practice in order to assess human motion and their performance of defined tasks. Whilst camera-based motion capture systems have long been regarded as the ‘Gold-standard’ for quantitative movement-based analysis, their application is not without limitations as regards potential sources of variability in measurements, high cost, and practicality of use for larger patient/subject groups. Another more practical approach, which presents itself as a viable solution to biomechanical motion capture and monitoring in sporting and patient groups, is through the use of small-size low-cost wearable Micro-ElectroMechanical Systems (MEMs)-based inertial sensors. The clinical aim of the present work is to evaluate rehabilitation progress following knee injuries, identifying a number of metrics measured via a wireless inertial sensing system. Several metrics in the time-domain have been considered to be reliable for measuring and quantifying patient progress across multiple exercises in different activities. This system was developed at the Tyndall National Institute and is able to provide a complete and accurate biomechanics assessment without the constraints of a motion capture laboratory. The results show that inertial sensors can be used for a quantitative assessment of knee joint mobility, providing valuable information to clinical experts as regards the trend of patient progress over the course of rehabilitation

    Wearable inertial sensors as a tool for quantitative assessment of progress during rehabilitation

    Get PDF
    Biomechanics analysis is frequently used in both clinical and sporting practice in order to assess human motion and performance of defined tasks. Whilst camera-based motion systems have long been regarded as the ‘Goldstandard’ for quantitative movement-based analysis, their application is not without limitations as regards potential sources of variability in measurements, high costs, and practicality of use for larger patient/subject groups. Another more practical approach, which presents itself as a viable solution to biomechanical motion capture and monitoring in sporting and patient groups, is through the use of small-size low-cost wearable Micro-ElectroMechanical Systems (MEMs)- based inertial sensors. The clinical aim of the present work is to evaluate gait during rehabilitation following knee injuries and to identify gait abnormalities through a wireless inertial sensing system. This system was developed at the Tyndall National Institute to meet clinician-defined needs, and is able to provide a complete biomechanics assessment without the constraints of a motion capture laboratory. The derived motion parameter outcomes can be analyzed by clinicians and sport scientists to study the overall patients’ condition and provide accurate medical feedback as to their rehabilitative progress. Detection of atypical movement characteristics is possible by comparing the performance and variability in motion characteristics in the patient’s affected and unaffected lower-limbs. The work is ongoing, and to date the system has been tested on only one impaired subject, additional clinical trials are currently being planned with an enhanced number of injured subjects. This will provide a more robust statistical analysis of the data in the study. The present feasibility study proved that inertial sensors can be used for a quantitative assessment of knee joint mobility, and gait mechanics during the rehabilitation program of injured subjects and can provide valuable information to clinical experts as regards patient rehabilitation

    Hidden orders and (anti-)Magnetoelectric Effects in Cr2_2O3_3 and α\alpha-Fe2_2O3_3

    Full text link
    We present ab initio calculations of hidden magnetoelectric multipolar order in Cr2_2O3_3 and its iron-based analogue, α\alpha-Fe2_2O3_3. First, we discuss the connection between the order of such hidden multipoles and the linear magnetoelectric effect. Next, we show the presence of hidden antiferroically-ordered magnetoelectric multipoles in both the prototypical magnetoelectric material Cr2_2O3_3, and centrosymmetric α\alpha-Fe2_2O3_3, which has the same crystal structure as Cr2_2O3_3, but a different magnetic dipolar ordering. In turn, we predict anti-magnetoelectric effects, in which local magnetic dipole moments are induced in opposite directions under the application of an external electric field, to create an additional antiferromagnetic ordering. We confirm the predicted induced moments using first-principles calculations. Our results demonstrate the existence of hidden magnetoelectric multipoles leading to local linear magnetoelectric responses even in centrosymmetric materials, where a net bulk linear magnetoelectric effect is forbidden by symmetry

    Sub-pixel point detection algorithm for point tracking with low-power wearable camera systems: a simplified linear interpolation

    Get PDF
    With the continuous developments in vision sensor technology, highly miniaturized low-power and wearable vision sensing is becoming a reality. Several wearable vision applications exist which involve point tracking. The ability to efficiently detect points at a sub-pixel level can be beneficial, as the accuracy of point detection is no longer limited to the resolution of the vision sensor. In this work, we propose a novel Simplified Linear Interpolation (SLI) algorithm that achieves high computational efficiency, which outperforms existing algorithms in terms of the accuracy under certain conditions. We present the principles underlying our algorithm and evaluate it in a series of test scenarios. Its performance is finally compared to similar algorithms currently available in the literature

    3D ranging and tracking using lensless smart sensors

    Get PDF
    Target tracking has a wide range of applications in Internet of Things (IoT), such as smart city sensors, indoor tracking, and gesture recognition. Several studies have been conducted in this area. Most of the published works either use vision sensors or inertial sensors for motion analysis and gesture recognition [1, 2]. Recent works use a combination of depth sensors and inertial sensors for 3D ranging and tracking [3, 4]. This often requires complex hardware and the use of complex embedded algorithms. Stereo cameras or Kinect depth sensors used for high precision ranging are instead expensive and not easy to use. The aim of this work is to track in 3D a hand fitted with a series of precisely positioned IR LEDs using a novel Lensless Smart Sensor (LSS) developed by Rambus, Inc. [5, 6]. In the adopted device, the lens used in conventional cameras is replaced by low-cost ultra-miniaturized diffraction optics attached directly to the image sensor array. The unique diffraction pattern enables more precise position tracking than possible with a lens by capturing more information about the scene
    • …
    corecore