Absolute Orientation Research Articles

Wearable technology mediated biofeedback to modulate spine motor control: a scoping review

BackgroundLower back pain (LBP) is a disability that affects a large proportion of the population and treatment for this condition has been shifting towards a more individualized, patient-centered approach. There has been a recent uptake in the utilization and implementation of wearable sensors that can administer biofeedback in various industrial, clinical, and performance-based settings. Despite this, there is a strong need to investigate how wearable sensors can be used in a sensorimotor (re)training approach, including how sensory biofeedback from wearable sensors can be used to improve measures of spinal motor control and proprioception.Research questionThe purpose of this scoping review was to examine the wide range of wearable sensor-mediated biofeedback frameworks currently being utilized to enhance spine posture and motor function.MethodsA comprehensive scoping review was conducted in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines extension for Scoping Reviews (PRISMA-ScR) across the following databases: Embase, PubMed, Scopus, Cochrane, and IEEEXplore. Articles related to wearable biofeedback and spine movement were reviewed dated from 1980 - 2020. Extracted data was collected as per a predetermined checklist including the type, timing, trigger, location, and magnitude of sensory feedback being applied to the body.ResultsA total of 23 articles were reviewed and analysed. The most used wearable sensor to inform biofeedback were inertial measurement units (IMUs). Haptic (vibrotactile) feedback was the most common sensory stimulus. Most studies used an instantaneous online trigger to initiate sensory feedback derived from information pertaining to gross lumbar angles or the absolute orientations of the thorax or pelvis.ConclusionsThis is the first study to review wearable sensor-derived sensory biofeedback to modulate spine motor control. Although the type of wearable sensor and feedback were common, this study highlights the lack of consensus regarding the timing and structure of sensory feedback, suggesting the need to optimize any sensory feedback to a specific use case. The findings from this study help to improve the understanding surrounding the ecological utility of wearable sensor-mediated biofeedback in industrial, clinical, and performance settings to enhance the sensorimotor control of the lumbar spine.

The Hera Radio Science Experiment at Didymos

Hera represents the European Space Agency's inaugural planetary defense space mission and plays a pivotal role in the Asteroid Impact and Deflection Assessment international collaboration with NASA DART mission that performed the first asteroid deflection experiment using the kinetic impactor techniques. With the primary objective of conducting a detailed post-impact survey of the Didymos binary asteroid following the DART impact on its small moon called Dimorphos, Hera aims to comprehensively assess and characterize the feasibility of the kinetic impactor technique in asteroid deflection while conducting an in-depth investigation of the asteroid binary, including its physical and compositional properties as well as the effect of the impact on the surface and shape of Dimorphos. In this work, we describe the Hera radio science experiment, which will allow us to precisely estimate critical parameters, including the mass, which is required to determine the momentum enhancement resulting from the DART impact, mass distribution, rotational states, relative orbits, and dynamics of the asteroids Didymos and Dimorphos. Through a multi-arc covariance analysis, we present the achievable accuracy for these parameters, which consider the full expected asteroid phase and are based on ground radiometric, Hera optical images, and Hera to CubeSats InterSatellite Link radiometric measurements. The expected formal uncertainties for Didymos and Dimorphos GM are better than 0.01% and 0.1%, respectively, while their J2 formal uncertainties are better than 0.1% and 10%, respectively. Regarding their rotational state, the absolute spin pole orientations of the bodies can be recovered to better than 1°, and Dimorphos' spin rate to better than 10−3%. Dimorphos reconstructed relative orbit can be estimated at the sub-m level. Preliminary results, using a higher-fidelity dynamical model of the coupled motion between rotational and orbital dynamics, show uncertainties in the main parameters of interest that are comparable to those in standard radio science models. A first-order estimate of the expected uncertainty in the momentum transfer efficiency from DART's impact, obtainable with Hera, yields a value of about 0.25. This represents a significant improvement compared to current estimates. Overall, the retrieved values meet the Hera radio science requirements and goals, and remain valid under the condition that the system is determined to be in an excited but non-chaotic (or tumbling) state. The Hera radio science experiment will play an integral role in the exploration of the Didymos binary asteroid system and will provide unique scientific measurements, which, when combined with other observables such as optical images, altimetry measurements, and satellite-to-satellite tracking of the CubeSats, will support the mission's overarching goals in planetary defense and the deep understanding of binary asteroids.

Fingerprints of Chalcogen Bonding Revealed Through 77Se-NMR.

77Se-NMR is used to characterise several chalcogen bonded complexes of derivatives of the organoselenium drug ebselen, exploring a range of electron demand. NMR titration experiments support the intuitive understanding that chalcogen bond donors bearing more electron withdrawing substituents give rise stronger chalcogen bonds. The chemical shift of the selenium nucleus is also shown to move upfield as it participates in a chalcogen bond. Solid-state NMR is used to explore chalcogen bonding in co-crystals. Due to the lack of molecular reorientation on the NMR timescale in the solid state, the shape of the chemical shift tensor can be determined using this technique. A range of co-crystals are shown to have extremely large chemical shift anisotropy, which suggests a strongly anisotropic electron density distribution around the selenium atom. A single crystal NMR experiment was conducted using one of the co-crystals, affording the absolute orientation of the chemical shift tensor within the crystal. This showed that the selenium nucleus is strongly shielded in the direction of the chalcogen bond (due to the approach of the lone pair of the Lewis base), and strongly deshielded in the perpendicular direction. The orientation of the deshielded axis is consistent with the presence of a second σ-hole which is not participating in a chalcogen bond, showing the profound effect of electron density anisotropy on the chemical shift.

3D reconstruction of spherical images based on incremental structure from motion

ABSTRACT 3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to the frequent tracking failures of camera frames and high data collection costs. Recently, spherical images have been extensively exploited due to the capability of recording surrounding environments using one camera exposure. Classical 3D reconstruction pipelines, however, cannot be used for spherical images. Besides, there exist few software packages for the 3D reconstruction of spherical images. Based on the imaging geometry of spherical cameras, this study investigates the algorithms for relative orientation using spherical correspondences, absolute orientation using 3D correspondences between the scene and spherical points, as well as cost functions for BA (bundle adjustment) optimization. Besides, an incremental SfM (Structure from Motion) workflow has been proposed for spherical images by using the above-mentioned algorithms. The proposed solution is finally verified by using three spherical datasets captured by both consumer-grade and professional spherical cameras. The results demonstrate that the proposed SfM workflow can achieve the successful 3D reconstruction of complex scenes and provide useful clues for the implementation in open-source software packages. The source code would be publicly available.

User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning.

In this paper, the issue of detecting a user's position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for the binary classification of user orientation, neural networks achieved accuracy that was more than 9% higher than that for the well-known threshold method. In addition, the classification of user position angles relative to the reference node was analyzed. It was proven that, using the proposed deep learning approach and the channel impulse response, it was possible to estimate the angle of the user's position in relation to the antenna geometry. Absolute user orientation angle errors of about 4-7° for convolutional neural networks and of about 14-15° for multilayer perceptrons were achieved in approximately 85% of the cases in both tested scenarios.

The effects of field strength on stimulated echo and motion-compensated spin-echo diffusion tensor cardiovascular magnetic resonance sequences

BackgroundIn-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) is an emerging technique for microstructural tissue characterization in the myocardium. Most studies are performed at 3T, where higher signal-to-noise ratio (SNR) should benefit this signal-starved method. However, a few studies have suggested that DT-CMR is possible at 1.5T, where echo planar imaging artifacts may be less severe and 1.5T hardware is more widely available. MethodsWe recruited 20 healthy volunteers and performed mid-ventricular short-axis DT-CMR at 1.5T and 3T. Acquisitions were performed at peak systole and end-diastole using both stimulated echo acquisition mode (STEAM) and motion-compensated spin-echo (MCSE) sequences at matched spatial resolutions. DT-CMR parameters were averaged over the left ventricle and compared between 1.5T and 3T sequences using both datasets with and without the blow reference data included. ResultsEleven (1.5T) and 12 (3T) diastolic MCSE acquisitions were rejected as the helix angle (HA) demonstrated <50% normal appearance circumferentially or the acquisition was abandoned due to poor image quality; a maximum of one acquisition was rejected for other datasets. Subjective HA map quality was significantly better at 3T than 1.5T for STEAM (p < 0.05), but not for MCSE and other DT-CMR quality measures were consistent with improvements in STEAM at 3T over 1.5T. When blow data were excluded, no significant differences in mean diffusivity were observed between field strengths, but fractional anisotropy was significantly higher at 1.5T than 3T for STEAM systole (p < 0.05). Absolute second eigenvector orientation (E2A, sheetlet angle) was significantly higher at 1.5T than 3T for MCSE systole and STEAM diastole, but significantly lower for STEAM systole (all p < 0.05). Transmural HA distribution was less steep at 1.5T than 3T for STEAM diastole data (p < 0.05). SNR was higher at 3T than 1.5T for all acquisitions (p < 0.05). ConclusionWhile 3T provides benefits in terms of SNR, both STEAM and MCSE can be performed at 1.5T. However, MCSE is unreliable in diastole at both field strengths and STEAM benefits from the improved SNR at 3T over 1.5T. Future clinical research studies may be able to leverage the wider availability of 1.5T CMR hardware where MCSE acquisitions are desirable.

Absolute local conformation of poly(methyl methacrylate) chains adsorbed on a quartz surface.

Polymer chains at a buried interface with an inorganic solid play a critical role in the performance of polymer nanocomposites and adhesives. Sum frequency generation (SFG) vibrational spectroscopy with a sub-nanometer depth resolution provides valuable information regarding the orientation angle of functional groups at interfaces. However, in the case of conventional SFG, since the signal intensity is proportional to the square of the second-order nonlinear optical susceptibility and thereby loses phase information, it cannot be unambiguously determined whether the functional groups face upward or downward. This problem can be solved by phase-sensitive SFG (ps-SFG). We here applied ps-SFG to poly(methyl methacrylate) (PMMA) chains in direct contact with a quartz surface, shedding light on the local conformation of chains adsorbed onto the solid surface. The measurements made it possible to determine the absolute orientation of the ester methyl groups of PMMA, which were oriented toward the quartz interface. Combining ps-SFG with all-atomistic molecular dynamics simulation, the distribution of the local conformation and the driving force are also discussed.

On the anisotropic distribution of clusters in the local Universe

ABSTRACT In his 2021 lecture to the Canadian Association of Physicists Congress, P.J.E. Peebles pointed out that the brightest extragalactic radio sources tend to be aligned with the plane of the de Vaucouleur Local Supercluster up to redshifts of z = 0.02 ($d_{\rm MW}\approx 85~\rm {Mpc}$). He then asked whether such an alignment of clusters is anomalous in the standard Lambda cold dark matter (ΛCDM) framework. In this letter, we employ an alternative, absolute orientation agnostic, measure of the anisotropy based on the inertia tensor axial ratio of these brightest sources and use a large cosmological simulation from the flamingo suite to measure how common such an alignment of structures is. We find that only 3.5 per cent of randomly selected regions display an anisotropy of their clusters more extreme than the one found in the local Universe’s radio data. This sets the region around the Milky Way as a 1.85σ outlier. Varying the selection parameters of the objects in the catalogue, we find that the clusters in the local Universe are never more than 2σ away from the simulations’ prediction for the same selection. We thus conclude that the reported anisotropy, whilst noteworthy, is not in tension with the ΛCDM paradigm.

Automated analysis of animal behavior and its relation to key aspects of the environment reveals new cognitive specializations of neurons

A thorough analysis of animal behavior is essential for examining the relationship between specific neuron activations with the elements of the external environment, behavior, or internal state. Machine learning techniques have made some advancements in automatic segmentation of animal behavior based on data concerning the location of animal body parts [1–3]. At present, these methods cannot achieve the level of segmentation accuracy desired or make correlations between an animal’s behavioral acts and key environmental factors. To address this issue, the authors have created a software package that can extract a variety of behavioral variables from video recordings of animals in experimental settings, enabling mathematical analysis of a behavioral act continuum. The identification of specific aspects of an animal’s anatomy is crucial for extracting a vast array of behavioral variables. In order to accomplish this task, our team employed DeepLabCut, an accessible toolkit for tracking experimental animal behavior that operates on the principle of transfer learning through deep neural networks. We have devised a technique to ascertain the positions of animal body parts in diverse behavioral situations, resulting in a body parts collection meeting two criteria: offering superior responsiveness to small motor movements of the animal and delivering a high percentage of correct body part locations. In scenarios employing camera shooting from above, such a collection encompasses the nose, ears, tail base, body center, forelimbs, hind limbs, and both flanks of the animal’s body. Next, we created software tools to extract and annotate behavioral variables from data on animal kinematics in various cognitive tasks. Our automated system comprises two main scripting modules: CreatePreset and BehaviorAnalyzer. The CreatePreset module interacts with users to select the type of arena geometry, object location, and necessary temporal and spatial parameters for analysis. The script’s result saves as a mat-file for analyzing the behavior of all experiment videos, assuming a constant relative position of the arena and the video camera alongside the experiment’s design. The BehaviorAnalyzer module conducts initial processing on time series data consisting of coordinates of an animal’s body parts. This results in the formation of a kinematogram, which details the kinematics of the body parts. The module then isolates individual behavioral acts of the animal and annotates its behavior based on motivational and environmental factors. Using mutual information-based methods, we analyzed the specialization of hippocampal CA1 neurons in animals as they explored arenas with varying degrees of novelty. Through the analysis, we have identified neurons that exhibit selectivity in relation to specific continuous kinematic parameters governing the posture and trajectory of the animal. These parameters include the animal’s location in the arena space (X and Y coordinates), as well as the speed and angle of rotation of the animal’s head (i.e. absolute orientation in the arena). Neurons specialized in discrete acts of behavior were identified, including rests, locomotions, freezing, rears, and acts of interaction with objects. Furthermore, a selective activation of neurons was found with regard to an additional set of distinct parameters, which combine the animal’s location in the arena and its speed.

3D Finger Rotation Estimation from Fingerprint Images

Various touch-based interaction techniques have been developed to make interactions on mobile devices more effective, efficient, and intuitive. Finger orientation, especially, has attracted a lot of attentions since it intuitively brings three additional degrees of freedom (DOF) compared with two-dimensional (2D) touching points. The mapping of finger orientation can be classified as being either absolute or relative, suitable for different interaction applications. However, only absolute orientation has been explored in prior works. The relative angles can be calculated based on two estimated absolute orientations, although, a higher accuracy is expected by predicting relative rotation from input images directly. Consequently, in this paper, we propose to estimate complete 3D relative finger angles based on two fingerprint images, which incorporate more information with a higher image resolution than capacitive images. For algorithm training and evaluation, we constructed a dataset consisting of fingerprint images and their corresponding ground truth 3D relative finger rotation angles. Experimental results on this dataset revealed that our method outperforms previous approaches with absolute finger angle models. Further, extensive experiments were conducted to explore the impact of image resolutions, finger types, and rotation ranges on performance. A user study was also conducted to examine the efficiency and precision using 3D relative finger orientation in 3D object rotation task.

Quantitative analysis of the morphing wing mechanism of raptors: IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy. Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Ontological models of the development of urban areas from the stand-point of applied cultural studies

The object of research is the universal processes of space development in urban planning. An ontological model of space development is proposed, applicable to the zoning of megacities and public spaces, allowing its sectoral and zigzag representation. Territorial planning is defined as the formalization of the genesis and self-organization processes. The formalization includes eight stages of the self-organization process, absolute and relative spatial interpretation of each stage, and a set of urban planning functions for each stage. This approach can be used to examine the zoning of public spaces both as part of the designed public space and in the surrounding buildings. In the sectoral ontological model, the development of space is presented as a process of genesis, directed from the general to the particular and having an absolute or relative orientation to the cardinal points. In the zigzag ontological model, a relative spatial orientation is established between adjacent objects. The novelty of the study lies in the establishment of common principles for structuring space for megacities and their public spaces.

Estimation of Spatio-Temporal Parameters of Gait and Posture of Visually Impaired People Using Wearable Sensors

In rehabilitating orientation and mobility (O&amp;M) for visually impaired people (VIP), the measurement of spatio-temporal gait and postural parameters is of specific interest for rehabilitators to assess performance and improvements in independent mobility. In the current practice of rehabilitation worldwide, this assessment is carried out in people with estimates made visually. The objective of this research was to propose a simple architecture based on the use of wearable inertial sensors for quantitative estimation of distance traveled, step detection, gait velocity, step length and postural stability. These parameters were calculated using absolute orientation angles. Two different sensing architectures were tested for gait according to a selected biomechanical model. The validation tests included five different walking tasks. There were nine visually impaired volunteers in real-time acquisitions, where the volunteers walked indoor and outdoor distances at different gait velocities in their residences. The ground truth gait characteristics of the volunteers in five walking tasks and an assessment of the natural posture during the walking tasks are also presented in this article. One of the proposed methods was selected for presenting the lowest absolute error of the calculated parameters in all of the traveling experimentations: 45 walking tasks between 7 and 45 m representing a total of 1039 m walked and 2068 steps; the step length measurement was 4.6 ± 6.7 cm with a mean of 56 cm (11.59 Std) and 1.5 ± 1.6 relative error in step count, which compromised the distance traveled and gait velocity measurements, presenting an absolute error of 1.78 ± 1.80 m and 7.1 ± 7.2 cm/s, respectively. The results suggest that the proposed method and its architecture could be used as a tool for assistive technology designed for O&amp;M training to assess gait parameters and/or navigation, and that a sensor placed in the dorsal area is sufficient to detect noticeable postural changes that compromise heading, inclinations and balancing in walking tasks.

A large depth-of-field virtual measurement network for non-cooperative 6DOF pose estimation in occlusion scenes

Six degrees of freedom (6DOF) measurement capable of determining the rigid transformation is a vital task in aerospace exploration and autonomous navigation. In this paper, a large depth-of-field virtual measurement network is proposed based on a moving rotating-prism-embedded camera to achieve 6DOF pose estimation for non-cooperative partially occluded targets. It includes stereo recovery using dense beam localization and accurate absolute orientation based on dual quaternions and adaptive scale factors. The former allows the three-dimensional (3D) extraction by multiview large-parallax imaging, while the latter enables the decoupling of translation and orientation without initial value estimation to avoid error accumulation. Compared to the mainstream methods, our method provides high-quality pose metrology, especially for depth extraction. The experiments show that the architecture allows the 3D reconstruction and non-cooperative 6DOF estimation with a large depth of field and object occlusion, solving the problem of difficult compromise between long-baseline imaging and compact configuration.

Robust registration of aerial and close‐range photogrammetric point clouds using visual context features and scale consistency

AbstractPoint cloud registration is of great significance to the reconstruction of high‐precision 3D city models. There are some challenges when aligning aerial and close‐range photogrammetric point clouds, such as huge view differences caused by the different sights of the sensors, massive noisy points due to the error in dense matching, and scale uncertainty since there are no control points for absolute orientation. To achieve complementary advantages of aerial and close‐range point clouds, in this paper, a robust cross‐source point clouds registration method is proposed using image visual context features and scale consistency. First, a cross‐view image matching method based on image visual context features is proposed to obtain corresponding points. Second, to overcome the challenges of noisy points and scale differences, an outlier filtering method is designed based on scale consistency. Finally, the dual quaternions model considering the scale factor is introduced to solve the spatial transformation model. To analyze the feasibility of this method qualitatively and quantitatively, experiments are conducted using the public scene dataset of Dortmund, Germany, and the scene dataset of Zhengzhou City, China. Three kinds of cross‐source point clouds registration experiments are conducted in this paper, including aerial and close‐range point clouds registration in Dortmund, and aerial and ground point clouds registrations in both Dortmund and Zhengzhou. The chamfer distances of the three sets of experiments are 4.48 m, 5.97 m and 4.78 m, respectively. The ablation study shows that the outlier filtering method and the dual quaternions model improve the accuracy by at least 14% and 25%, respectively. The experiments demonstrate that the method accomplishes the cross‐source point clouds registration in large‐scale scenes accurately and efficiently, providing a solid foundation for subsequent fine 3D reconstruction.

Stability Analysis of Nonlinear Rotating Systems Using Lyapunov Characteristic Exponents Estimated From Multibody Dynamics

Abstract The use of Lyapunov characteristic exponents to assess the stability of nonlinear, time-dependent mechanical systems is discussed. Specific attention is dedicated to methods capable of estimating the largest exponent without requiring the Jacobian matrix of the problem, which can be applied to time histories resulting from simulations performed with existing multibody solvers. Helicopter ground resonance is analyzed as the reference application. Improvements over the available literature are: the problem is formulated in physical coordinates, without eliminating periodicity through multiblade coordinates; the rotation of the blades is not linearized; the problem is modeled considering absolute positions and orientations of parts. The dynamic instability that arises at some angular velocities when the isotropy of the rotor is broken (e.g., caused by the failure of one lead-lag damper, a design test condition) is observed to evolve into a large amplitude limit cycle, where the usual Floquet–Lyapunov analysis of the linearized time-periodic simply predicts instability.

Iteratively weighted least squares solution for universal 3D similarity transformation

The 3D similarity coordinate transformation is widely used to estimate the transformation parameters for measurement datum transformation. Accurate and reliable transformation parameters are crucial for accurate and reliable data integration. However, the accuracy of the transformation parameters can be significantly affected or even severely distorted when the observed coordinates are contaminated by gross errors. To address this problem, an advanced iteratively weighted least squares solution based on the weighted least squares is proposed. This solution utilizes the singular value decomposition method to obtain the rotation matrix and introduces a novel weight estimation approach based on Gaussian function. This approach enables the weight to be normalized and optimized iteratively. To verify the accuracy and reliability of the proposed algorithm, the root mean square errors from both true and pseudo-observed values are analyzed by simulation experiments. Furthermore, the results of simulated and empirical experiments show that the proposed algorithm can effectively reduce the influence of gross errors to obtain reliable measurement datum transformation parameters. It should be noted that the new algorithm can easily be extended to the 2D/3D affine and rigid transformation cases, such as image matching, point cloud registration, and absolute orientation of photogrammetry.

A convenient approach for knee kinematics assessment using wearable inertial sensors during home-based rehabilitation: Validation with an optoelectronic system

Rehabilitation services are among the most severely impacted by the COVID-19 pandemic. This has increased the number of people not receiving the needed rehabilitation care. Home-based rehabilitation becomes alternative support to face this greater need. However, monitoring kinematics parameters during rehabilitation exercises is critical for an effective recovery. This work proposes a detailed framework to estimate knee kinematics using a wearable Magnetic and Inertial Measurement Unit (MIMU). That allows at-home monitoring for knee rehabilitation progress. Two MIMU sensors were attached to the shank and thigh segments respectively. First, the absolute orientation of each sensor was estimated using a sensor fusion algorithm. Second, these sensor orientations were transformed to segments orientations using a functional sensor-to-segment (STS) alignment. Third, the relative orientation between segments, i.e., knee joint angle, was computed and the relevant kinematics parameters were extracted. Then, the validity of our approach was evaluated with a gold-standard optoelectronic system. Seven participants completed three to five Timed-Up-and-Go (TUG) tests. The estimated knee angle was compared to the reference angle. Root-mean-square error (RMSE), correlation coefficient, and Bland-Altman analysis were considered as evaluation metrics. Our results showed reasonable accuracy (RMSE < 8°), strong to very-strong correlation (correlation coefficient > 0.86), a mean difference within 1.1°, and agreement limits from -16° to 14°. In addition, no significant difference was found (p-value > 0.05) in extracted kinematics parameters between both systems. The proposed approach might represent a suitable alternative for the assessment of knee rehabilitation progress in a home context.

Miniscope-LFOV: A large-field-of-view, single-cell-resolution, miniature microscope for wired and wire-free imaging of neural dynamics in freely behaving animals

Imaging large-population, single-cell fluorescent dynamics in freely behaving animals larger than mice remains a key endeavor of neuroscience. We present a large-field-of-view open-source miniature microscope (MiniLFOV) designed for large-scale (3.6 mm×2.7 mm), cellular resolution neural imaging in freely behaving rats. It has an electrically adjustable working distance of up to 3.5 mm±100 μm, incorporates an absolute head orientation sensor, and weighs only 13.9 g.The MiniLFOV is capable of both deep brain and cortical imaging and has been validated in freely behaving rats by simultaneously imaging >1000 GCaMP7s-expressing neurons in the hippocampal CA1 layer and in head-fixed mice by simultaneously imaging ~2000 neurons in the dorsal cortex through a cranial window. The MiniLFOV also supports optional wire-free operation using a novel, wire-free data acquisition expansion board. We expect that this new open-source implementation of the UCLA Miniscope platform will enable researchers to address novel hypotheses concerning brain function in freely behaving animals.

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke. The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires. Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported. Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.