Low-energy ion outflows from the ionosphere during a major polar cap expansion — evidence for equatorward motion of inverted-V structures

Data from the Dynamics Explorer 1 satellite and the EISCAT and Sondrestrom incoherent scatter radars, have allowed a study of low-energy ion outflows from the ionosphere into the magnetosphere during a rapid expansion of the polar cap. From the combined radar data, a 200kV increase in cross-cap potential is estimated. The upflowing ions show “X” signatures in the pitch angle-time spectrograms in the expanding midnight sector of the auroral oval. These signatures reveal low-energy (below about 60eV), light-ion beams sandwiched between two regions of ion conics and are associated with inverted-V electron precipitation. The lack of mass dispersion of the poleward edge of the event, despite great differences in the times of flight, reflects the equatorward expansion of the acceleration regions at velocities similar to those of the antisunward convection. In addition, a transient burst of upflow of 0+ is observed within the cap, possibly due to enhanced Joule heating during the event.

Low-cost HMD and EEG: using visual stimulation by the Oculus Rift® to detect stronger ERDs induced by motion imagery

Virtual Reality (VR) can provide visual stimuli for EEG studies that can be altered in real time and can produce effects that are difficult or impossible to reproduce in a non-virtual experimental platform. As part of this experiment the Oculus Rift, a commercial-grade, low-cost, Head Mounted Display (HMD) was assessed as a visual stimuli platform for experiments recording EEG. Following, the device was used to investigate the effect of congruent visual stimuli on Event Related Desynchronisation (ERD) due to motion imagery.

Local energy and pre-envelope

We observe that the local energy is the pre-envelope for analytic function. The maxima and phase of this function can be used to compute and classify visual features such as motion and stereo disparity, texture, etc. We examine the construction of new filters for computing Local Energy, and compare these filters with the Gabor filters and the three-point-filter of Venkatesh and Owens.

Odometria visual baseada em técnicas de structure from motion

Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

Step Counting and Energy Expenditure Estimation in Patients With Chronic Obstructive Pulmonary Disease and Healthy Elderly: Accuracy of 2 Motion Sensors

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Energy expenditure during daily activities as measured by two motion sensors in patients with COPD

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of visual information on optimal obstacle crossing

Human motion seems to be guided by some optimal principles. In general, it is assumed that human walking is generated with minimal energy consumption. However, in the presence of disturbances during gait, there is a trade-off between stability (avoiding a fall) and energy-consumption. This work analyses the obstacle-crossing with the leading foot. It was hypothesized that energy-saving mechanisms during obstacle-crossing are modulated by the requirement to avoid a fall using the available sensory information, particularly, by vision. A total of fourteen subjects, seven with no visual impairment and seven blind, walked along a 5 meter flat pathway with an obstacle of 0.26 m height located at 3 m from the starting point. The seven subjects with normal vision crossed the obstacle successfully 30 times in two conditions: blindfolded and with normal vision. The seven blind subjects did the same 30 times. The motion of the leading limb was recorded by video at 60 Hz. There were markers placed on the subject's hip, knee, ankle, rear foot, and forefoot. The motion data were filtered with a fourth order Butterworth filter with a cut-off frequency of 4 Hz. The following variables were calculated: horizontal distance between the leading foot and the obstacle at toe-off prior to (DHPO) and after (DHOP) crossing, minimal vertical height from the foot to the obstacle (DVPO), average step velocity (VELOm). The segmental energies were also calculated and the work consumed by the leading limb during the crossing obstacle was computed for each trial. A statistical analysis repeated-measures ANOVA was conducted on these dependent variables revealing significant differences between the vision and non-vision conditions in healthy subjects. In addition, there were no significant differences between the blind and people with vision blindfolded. These results indicate that vision is crucial to determine the optimal trade-off between energy consumption and avoiding a trip during obstacle crossing.

Consistency of superspace low energy equations of motion of 4D Type II superstring with Type II sigma model at tree-level

We derive the torsion constraints and show the consistency of equations of motion of four-dimensional Type II supergravity in superspace. with Type II sigma model. This is achieved by coupling the four-dimensional compactified Type II Berkovits' superstring to an N = 2 curved background and requiring that the sigma-model has superconformal invariance at tree-level. We compute this in a manifestly 4D N = 2 supersymmetric way. The constraints break the target conformal and SU(2) invariances and the dilaton will be a conformal, SU(2) x U(1) compensator. For Type II superstring in four dimensions, worldsheet supersymmetry requires two different compensators. One type is described by chiral and anti-chiral superfields. This compensator can be identified with a vector multiplet. The other Type II compensator is described by twist-chiral and twist-anti-chiral superfields and can be identified with a tensor hypermultiplet. Also, the superconformal invariance at tree-level selects a particular gauge, where the matter is fixed, but not the compensators. After imposing the reality conditions, we show that the Type II sigma model at tree-level is consistent with the equations of motion for Type II supergravity in the string gauge. (C) 2003 Elsevier B.V All rights reserved.

Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

Energy harvesting from body motion using rotational micro-generation

Autonomous system applications are typically limited by the power supply operational lifetime when battery replacement is difficult or costly. A trade-off between battery size and battery life is usually calculated to determine the device capability and lifespan. As a result, energy harvesting research has gained importance as society searches for alternative energy sources for power generation. For instance, energy harvesting has been a proven alternative for powering solar-based calculators and self-winding wristwatches. Thus, the use of energy harvesting technology can make it possible to assist or replace batteries for portable, wearable, or surgically-implantable autonomous systems. Applications such as cardiac pacemakers or electrical stimulation applications can benefit from this approach since the number of surgeries for battery replacement can be reduced or eliminated. Research on energy scavenging from body motion has been investigated to evaluate the feasibility of powering wearable or implantable systems. Energy from walking has been previously extracted using generators placed on shoes, backpacks, and knee braces while producing power levels ranging from milliwatts to watts. The research presented in this paper examines the available power from walking and running at several body locations. The ankle, knee, hip, chest, wrist, elbow, upper arm, side of the head, and back of the head were the chosen target localizations. Joints were preferred since they experience the most drastic acceleration changes. For this, a motor-driven treadmill test was performed on 11 healthy individuals at several walking (1-4 mph) and running (2-5 mph) speeds. The treadmill test provided the acceleration magnitudes from the listed body locations. Power can be estimated from the treadmill evaluation since it is proportional to the acceleration and frequency of occurrence. Available power output from walking was determined to be greater than 1mW/cm³ for most body locations while being over 10mW/cm³ at the foot and ankle locations. Available power from running was found to be almost 10 times higher than that from walking. Most energy harvester topologies use linear generator approaches that are well suited to fixed-frequency vibrations with sub-millimeter amplitude oscillations. In contrast, body motion is characterized with a wide frequency spectrum and larger amplitudes. A generator prototype based on self-winding wristwatches is deemed to be appropriate for harvesting body motion since it is not limited to operate at fixed-frequencies or restricted displacements. Electromagnetic generation is typically favored because of its slightly higher power output per unit volume. Then, a nonharmonic oscillating rotational energy scavenger prototype is proposed to harness body motion. The electromagnetic generator follows the approach from small wind turbine designs that overcome the lack of a gearbox by using a larger number of coil and magnets arrangements. The device presented here is composed of a rotor with multiple-pole permanent magnets having an eccentric weight and a stator composed of stacked planar coils. The rotor oscillations induce a voltage on the planar coil due to the eccentric mass unbalance produced by body motion. A meso-scale prototype device was then built and evaluated for energy generation. The meso-scale casing and rotor were constructed on PMMA with the help of a CNC mill machine. Commercially available discrete magnets were encased in a 25mm rotor. Commercial copper-coated polyimide film was employed to manufacture the planar coils using MEMS fabrication processes. Jewel bearings were used to finalize the arrangement. The prototypes were also tested at the listed body locations. A meso-scale generator with a 2-layer coil was capable to extract up to 234 µW of power at the ankle while walking at 3mph with a 2cm³ prototype for a power density of 117 µW/cm³. This dissertation presents the analysis of available power from walking and running at different speeds and the development of an unobtrusive miniature energy harvesting generator for body motion. Power generation indicates the possibility of powering devices by extracting energy from body motion.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

The influence of naturalistic, directionally non-specific motion on the spatial deployment of visual attention in right-hemispheric stroke

An impairment of the spatial deployment of visual attention during exploration of static (i.e., motionless) stimuli is a common finding after an acute, right-hemispheric stroke. However, less is known about how these deficits: a) are modulated through naturalistic motion (i.e., without directional, specific spatial features); and, b) evolve in the subacute/chronic post-stroke phase. In the present study, we investigated free visual exploration in three patient groups with subacute/chronic right-hemispheric stroke and in healthy subjects. The first group included patients with left visual neglect and a left visual field defect (VFD), the second patients with a left VFD but no neglect, and the third patients without neglect or VFD. Eye movements were measured in all participants while they freely explored a traffic scene without (static condition) and with (dynamic condition) naturalistic motion, i.e., cars moving from the right or left. In the static condition, all patient groups showed similar deployment of visual exploration (i.e., as measured by the cumulative fixation duration) as compared to healthy subjects, suggesting that recovery processes took place, with normal spatial allocation of attention. However, the more demanding dynamic condition with moving cars elicited different re-distribution patterns of visual attention, quite similar to those typically observed in acute stroke. Neglect patients with VFD showed a significant decrease of visual exploration in the contralesional space, whereas patients with VFD but no neglect showed a significant increase of visual exploration in the contralesional space. No differences, as compared to healthy subjects, were found in patients without neglect or VFD. These results suggest that naturalistic motion, without directional, specific spatial features, may critically influence the spatial distribution of visual attention in subacute/chronic stroke patients.

Control motion approach of a lower limb orthosis to reduce energy consumption

By analysing the dynamic principles of the human gait, an economic gait‐control analysis is performed, and passive elements are included to increase the energy efficiency in the motion control of active orthoses. Traditional orthoses use position patterns from the clinical gait analyses (CGAs) of healthy people, which are then de‐normalized and adjusted to each user. These orthoses maintain a very rigid gait, and their energy cosT is very high, reducing the autonomy of the user. First, to take advantage of the inherent dynamics of the legs, a state machine pattern with different gains in eachstate is applied to reduce the actuator energy consumption. Next, different passive elements, such as springs and brakes in the joints, are analysed to further reduce energy consumption. After an off‐line parameter optimization and a heuristic improvement with genetic algorithms, a reduction in energy consumption of 16.8% is obtained by applying a state machine control pattern, and a reduction of 18.9% is obtained by using passive elements. Finally, by combining both strategies, a more natural gait is obtained, and energy consumption is reduced by 24.6%compared with a pure CGA pattern.

Study and analysis of the Leap Motion sensor and the Software Development Kit (SDK) for the implementation of visual Human Computer Interfaces

En este proyecto, se presenta un informe técnico sobre la cámara Leap Motion y el Software Development Kit correspondiente, el cual es un dispositivo con una cámara de profundidad orientada a interfaces hombre-máquina. Esto es realizado con el propósito de desarrollar una interfaz hombre-máquina basada en un sistema de reconocimiento de gestos de manos. Después de un exhaustivo estudio de la cámara Leap Motion, se han realizado diversos programas de ejemplo con la intención de verificar las capacidades descritas en el informe técnico, poniendo a prueba la Application Programming Interface y evaluando la precisión de las diferentes medidas obtenidas sobre los datos de la cámara. Finalmente, se desarrolla un prototipo de un sistema de reconocimiento de gestos. Los datos sobre la posición y orientación de la punta de los dedos obtenidos de la Leap Motion son usados para describir un gesto mediante un vector descriptor, el cual es enviado a una Máquina Vectores Soporte, utilizada como clasificador multi-clase.