Analytical modelling of the transport in analog filamentary conductive-metal-oxide/HfOx ReRAM devices

The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog filamentary conductive-metal-oxide (CMO)/HfOx redox-based resistive switching memory (ReRAM) represents a key technology. Despite device performance enhancements reported in literature, the underlying mechanism behind resistive switching is not fully understood. This work presents the first physics-based analytical model of the current transport and of the resistive switching in these devices. As a case study, analog TaOx/HfOx ReRAM devices are considered. The current transport is explained by a trap-to-trap tunneling process, and the resistive switching by a modulation of the defect density within the sub-band of the TaOx that behaves as electric field and temperature confinement layer. The local temperature and electric field distributions are derived from the solution of the electric and heat transport equations in a 3D finite element ReRAM model. The intermediate resistive states are described as a gradual modulation of the TaOx defect density, which results in a variation of its electrical conductivity. The drift-dynamics of ions during the resistive switching is analytically described, allowing the estimation of defect migration energies in the TaOx layer. Moreover, the role of the electro-thermal properties of the CMO layer is unveiled. The proposed analytical model accurately describes the experimental switching characteristic of analog TaOx/HfOx ReRAM devices, increasing the physical understanding and providing the equations necessary for circuit simulations incorporating this technology.

Predictors of controlled attenuation parameter in metabolic dysfunction

BACKGROUND & AIMS

Hepatic fat content can be non-invasively estimated by controlled attenuation parameter (CAP) during transient elastography. The aim of this study was to examine the determinants and predictors of CAP values in individuals with metabolic dysfunction.

METHODS

We enrolled 1230 consecutive apparently healthy individuals (Liver-Bible-2022 cohort) with ≥3 metabolic dysfunction features. CAP was measured by Fibroscan. CAP determinants and predictors were identified using backward stepwise analysis and introduced in generalized linear models.

RESULTS

Participants were predominantly males (82.9%), mean age was 53.8 ± 6.4 years, 600 (48.8%) had steatosis (CAP ≥ 275 dB/m), and 27 had liver stiffness measurement (LSM) ≥ 8 kPa. CAP values correlated with LSM (p < 10-22). In multivariable analysis, fasting insulin and abdominal circumference (AC) were the main determinants of CAP (p < 10-6), together with body mass index (BMI; p < 10-4), age, diabetes, triglycerides, ferritin, and lower HDL and thyroid stimulating hormone (TSH; p < 0.05 for all). In a subset of 592 participants with thyroid hormone measurement, we found an association between higher free triiodothyronine levels, correlating with lower TSH, and CAP values, independent of TSH and of levothyroxine treatment (p = 0.0025). A clinical CAP score based on age, BMI, AC, HbA1c, ALT, and HDL predicted CAP ≥ 275 dB/m with moderate accuracy (AUROC = 0.73), which was better than that of the Fatty Liver Index and of ALT (AUROC = 0.70/0.61, respectively) and validated it in multiple cohorts.

CONCLUSION

Abdominal adiposity and insulin resistance severity were the main determinants of CAP in individuals with metabolic dysfunction and may improve steatotic liver disease risk stratification. CAP values were modulated by the hypophysis-thyroid axis.

Quantification of indocyanine green near-infrared fluorescence bowel perfusion assessment in colorectal surgery

BACKGROUND

Indocyanine green near-infrared fluorescence bowel perfusion assessment has shown its potential benefit in preventing anastomotic leakage. However, the surgeon's subjective visual interpretation of the fluorescence signal limits the validity and reproducibility of the technique. Therefore, this study aimed to identify objective quantified bowel perfusion patterns in patients undergoing colorectal surgery using a standardized imaging protocol.

METHOD

A standardized fluorescence video was recorded. Postoperatively, the fluorescence videos were quantified by drawing contiguous region of interests (ROIs) on the bowel. For each ROI, a time-intensity curve was plotted from which perfusion parameters (n = 10) were derived and analyzed. Furthermore, the inter-observer agreement of the surgeon's subjective interpretation of the fluorescence signal was assessed.

RESULTS

Twenty patients who underwent colorectal surgery were included in the study. Based on the quantified time-intensity curves, three different perfusion patterns were identified. Similar for both the ileum and colon, perfusion pattern 1 had a steep inflow that reached its peak fluorescence intensity rapidly, followed by a steep outflow. Perfusion pattern 2 had a relatively flat outflow slope immediately followed by its plateau phase. Perfusion pattern 3 only reached its peak fluorescence intensity after 3 min with a slow inflow gradient preceding it. The inter-observer agreement was poor-moderate (Intraclass Correlation Coefficient (ICC): 0.378, 95% CI 0.210-0.579).

CONCLUSION

This study showed that quantification of bowel perfusion is a feasible method to differentiate between different perfusion patterns. In addition, the poor-moderate inter-observer agreement of the subjective interpretation of the fluorescence signal between surgeons emphasizes the need for objective quantification.

Outdoor mm-wave 5G/6G transmission with adaptive analog beamforming and IFoF fronthaul

Adaptive analog beamforming is a key technology to enable spatial control of millimeter-wave wireless signals radiated from phased array antennas (PAAs) which is essential to maximize the capacity of future mobile networks and to ensure efficient usage of scarce spectrum. Intermediate frequency-over-fiber (IFoF), on the other hand, is a promising technology for the millimeter-wave (mm-wave) mobile fronthaul due to its low complexity, high optical spectral efficiency, and low latency. The combination of IFoF and PAA is key to implement mm-wave mobile communications in a scalable, centralized, efficient, and reliable manner. This work presents, for the first time to the best of the authors' knowledge, an extensive outdoor measurement campaign where an experimental IFoF mm-wave wireless setup is evaluated by using PAAs with adaptive beamforming on the transmitter and receiver sides. The configuration of the experimental setup is according to 5G standards, transmitting signals wirelessly at 27 GHz central frequency in the n258 band. The employed PAAs are composed of 8-by-8 patch antenna arrays, allowing beam steering in the azimuth and elevation angles. Furthermore, different end-user locations, antenna configurations, and wireless scenarios are tested in the outdoor experiment, showing excellent EVM performance and achieving 64-QAM transmission over up to 165.5 m at up to 1.88 Gbit/s. The experimental results enable optimization of the experimental setup for different scenarios and prove the system's reliability in different wireless conditions. In addition, the results of this work prove the viability and potential of IFoF combined with PAA to be part of the future 5G/6G structure.

Healable Ionoelastomer Designed from Polymeric Ionic Liquid and Vitrimer Chemistry

The growing demand for all-solid flexible, stretchable, and wearable devices has boosted the need for liquid-free and stretchable ionoelastomers. These ionic conducting materials are subjected to repeated deformations during functioning, making them susceptible to damage. Thus, imparting cross-linked materials with healing ability seems particularly promising to improve their durability. Here, a polymeric ionic liquid (PIL) bearing allyl functional groups was synthesized based on the quaternization of N-allylimidazole with a copolymer rubber of poly(epichlorohydrin) and poly(ethylene oxide) (PEO). The resulting PIL was then cross-linked with dynamic boronic ester cross-linkers 2,2'-(1,4-Phenylene)-bis[4-mercaptan-1,3,2-dioxaborolane] (BDB) through thiol-ene "click" photoaddition. PEO dangling chains were additionally introduced for acting as free volume enhancers. The properties of the resulting all-solid PIL networks were investigated by tuning dynamic cross-linkers and dangling chain contents. Adjusting the cross-linker and dangling chain quantities yielded soft (0.2 MPa), stretchable (300%), and highly conducting ionoelastomers (1.6 × 10^-5 S·cm^-1 at 30 °C). The associative exchange reaction between BDB endowed these materials with vitrimer properties such as healing and recyclability. The recycled materials were able to retain their original mechanical properties and ionic conductivity. These healable PIL networks display a great potential for applications requiring solid electrolytes with high ionic conductivity, healing ability, and reprocessability.

Multifunctional Core@Satellite Magnetic Particles for Magnetoresistive Biosensors

Magnetoresistive (MR) biosensors combine distinctive features such as small size, low cost, good sensitivity, and propensity to be arrayed to perform multiplexed analysis. Magnetic nanoparticles (MNPs) are the ideal target for this platform, especially if modified not only to overcome their intrinsic tendency to aggregate and lack of stability but also to realize an interacting surface suitable for biofunctionalization without strongly losing their magnetic response. Here, we describe an MR biosensor in which commercial MNP clusters were coated with gold nanoparticles (AuNPs) and used to detect human IgG in water using an MR biochip that comprises six sensing regions, each one containing five U-shaped spin valve sensors. The isolated AuNPs (satellites) were stuck onto an aggregate of individual iron oxide crystals (core) so that the resulting core@satellite magnetic particles (CSMPs) could be functionalized by the photochemical immobilization technique-an easy procedure that leads to oriented antibodies immobilized upright onto gold. The morphological, optical, hydrodynamic, magnetic, and surface charge properties of CSMPs were compared with those exhibited by the commercial MNP clusters showing that the proposed coating procedure endows the MNP clusters with stability and ductility without being detrimental to magnetic properties. Eventually, the high-performance MR biosensor allowed us to detect human IgG in water with a detection limit of 13 pM (2 ng mL^-1). Given its portability, the biosensor described in this paper lends itself to a point-of-care device; moreover, the features of the MR biochip also make it suitable for multiplexed analysis.

Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry

Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic thyroid segmentation based on a deep neural network regarding inter- and intraobserver variability, time, and accuracy. Volume reference was MRI. 28 healthy volunteers (24—50 a) were scanned with 2D and 3D ultrasound (and by MRI) by three physicians (MD 1, 2, 3) with different experience levels (6, 4, and 1 a). In the 2D scans, the thyroid lobe volumes were calculated with the ellipsoid formula. A convolutional deep neural network (CNN) automatically segmented the 3D thyroid lobes. 26, 6, and 6 random lobe scans were used for training, validation, and testing, respectively. On MRI (T1 VIBE sequence) the thyroid was manually segmented by an experienced MD. MRI thyroid volumes ranged from 2.8 to 16.7ml (mean 7.4, SD 3.05). The CNN was trained to obtain an average Dice score of 0.94. The interobserver variability comparing two MDs showed mean differences for 2D and 3D respectively of 0.58 to 0.52ml (MD1 vs. 2), −1.33 to −0.17ml (MD1 vs. 3) and −1.89 to −0.70ml (MD2 vs. 3). Paired samples t-tests showed significant differences for 2D (p = .140, p = .002 and p = .002) and none for 3D (p = .176, p = .722 and p = .057). Intraobsever variability was similar for 2D and 3D ultrasound. Comparison of ultrasound volumes and MRI volumes showed a significant difference for the 2D volumetry of all MDs (p = .002, p = .009, p <.001), and no significant difference for 3D ultrasound (p = .292, p = .686, p = 0.091). Acquisition time was significantly shorter for 3D ultrasound. Tracked 3D ultrasound combined with a CNN segmentation significantly reduces interobserver variability in thyroid volumetry and increases the accuracy of the measurements with shorter acquisition times.

Graphene BioFET sensors for SARS-CoV-2 detection: a multiscale simulation approach

Biological Field-Effect Transistors (BioFETs) have already demonstrated enormous potential for detecting minute amounts of ions and molecules. The use of two-dimensional (2D) materials has been shown to boost their performance and to enable the design of new applications. This combination deserves special interest in the current pandemic caused by the SARS-CoV-2 virus which demands fast, reliable and cheap detection methods. However, in spite of the experimental advances, there is a lack of a comprehensive and in-depth computational approach to capture the mechanisms underlying the sensor behaviour. Here, we present a multiscale platform that combines detailed atomic models of the molecules with mesoscopic device-level simulations. The fine-level description exploited in this approach accounts for the charge distribution of the receptor, its reconfiguration when the target binds to it, and the consequences in terms of sensitivity on the transduction mechanism. The results encourage the further exploration of improved sensor designs and 2D materials combined with diverse receptors selected to achieve the desired specificity.

Fast Photoswitchable Molecular Prosthetics Control Neuronal Activity in the Cochlea

Artificial control of neuronal activity enables the study of neural circuits and restoration of neural functions. Direct, rapid, and sustained photocontrol of intact neurons could overcome the limitations of established electrical stimulation such as poor selectivity. We have developed fast photoswitchable ligands of glutamate receptors (GluRs) to enable neuronal control in the auditory system. The new photoswitchable ligands induced photocurrents in untransfected neurons upon covalently tethering to endogenous GluRs and activating them reversibly with visible light pulses of a few milliseconds. As a proof of concept of these molecular prostheses, we applied them to the ultrafast synapses of auditory neurons of the cochlea that encode sound and provide auditory input to the brain. This drug-based method afforded the optical stimulation of auditory neurons of adult gerbils at hundreds of hertz without genetic manipulation that would be required for their optogenetic control. This indicates that the new photoswitchable ligands are also applicable to the spatiotemporal control of fast spiking interneurons in the brain.

Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th Video Browser Showdown

The Video Browser Showdown addresses difficult video search challenges through an annual interactive evaluation campaign attracting research teams focusing on interactive video retrieval. The campaign aims to provide insights into the performance of participating interactive video retrieval systems, tested by selected search tasks on large video collections. For the first time in its ten year history, the Video Browser Showdown 2021 was organized in a fully remote setting and hosted a record number of sixteen scoring systems. In this paper, we describe the competition setting, tasks and results and give an overview of state-of-the-art methods used by the competing systems. By looking at query result logs provided by ten systems, we analyze differences in retrieval model performances and browsing times before a correct submission. Through advances in data gathering methodology and tools, we provide a comprehensive analysis of ad-hoc video search tasks, discuss results, task design and methodological challenges. We highlight that almost all top performing systems utilize some sort of joint embedding for text-image retrieval and enable specification of temporal context in queries for known-item search. Whereas a combination of these techniques drive the currently top performing systems, we identify several future challenges for interactive video search engines and the Video Browser Showdown competition itself.

Vibrational Damping Reveals Vibronic Coupling in Thermally Activated Delayed Fluorescence Materials

We investigate a series of D-A molecules consisting of spiro[acridan-9,9'-fluorene] as the donor and 2-phenylenepyrimidine as the acceptor. In two of the materials, a spiro center effectively electronically isolates the D unit from (consequently) optically innocent yet structurally influential adamantyl side groups. In a third material, adamantyl groups attached directly to the acceptor strongly influence the electronic properties. Steady-state and time-resolved photophysical studies in solution, Zeonex polymer matrix, and neat films reveal that the substituents impact the efficiency of vibronic coupling between singlet and triplet states relevant to reverse intersystem crossing (rISC) and thermally activated delayed fluorescence (TADF), without significantly changing the singlet-triplet gap in the materials. The adamantyl groups serve to raise the segmental mass and inertia, thereby damping intramolecular motions (both vibrational and rotational). This substitution pattern reveals the role of large-amplitude (primarily D-A dihedral angle rocking) motions on reverse intersystem crossing (rISC), as well as smaller contributions from low-amplitude or dampened vibrations in solid state. We demonstrate that rISC still occurs when the high-amplitude motions are suppressed in Zeonex and discuss various vibronic coupling scenarios that point to an underappreciated role of intersegmental motions that persist in rigid solids. Our results underline the complexity of vibronic couplings in the mediation of rISC and provide a synthetic tool to enable future investigations of vibronic coupling through selective mechanical dampening with no impact on electronic systems.

Amorphous Framework in Electrodeposited CuBiTe Thermoelectric Thin Films with High Room-Temperature Performance

Bismuth telluride-based alloys are the most efficient thermoelectric materials near room temperature and widely used in commercial thermoelectric devices. Nevertheless, their thermoelectric performance needs to be improved further for wide-scale implementation either as a thermoelectric generator or cooler. Here, we propose a simultaneous codeposition of CuBiTe thin films and their phase transition strategy via the traditional electrodeposition process. With just 13 atom % Cu doping, crystalline-to-amorphous phase transformation resulted for the electroplated CuBiTe alloy. A close look at the alloy composition revealed spike-shaped nanocrystalline Bi₂Te₃ embedded in the CuBiTe amorphous matrix. Our result shows an exceptionally high power factor (3.02 mW m^-1 K^-2), which comes from the enhanced Seebeck coefficient (-275 μV K^-1) and high electrical conductivity (3.99 × 10⁴ S m^-1) of CuBiTe films. Therefore, it can be suggested that the adopted strategy to form a unique nanocrystallite-embedded amorphous framework provides a platform to develop next-generation high-performance thermoelectric materials with an extraordinary power factor.

5G connected and automated driving: use cases, technologies and trials in cross-border environments

Cooperative, connected and automated mobility (CCAM) across Europe requires harmonized solutions to support cross-border seamless operation. The possibility of providing CCAM services across European countries has an enormous innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of real-time services pose technical challenges which 5G technologies aim to solve. The situation is particularly challenging given the multi-country, multi-operator, multi-telco-vendor, multi-car-manufacturer and cross-network-generation scenario of any cross-border scenario. Motivated by this, the 5GCroCo project, with a total budget of 17 million Euro and partially funded by the European Commission, aims at validating 5G technologies in the Metz-Merzig-Luxembourg cross-border 5G corridor considering the borders between France, Germany and Luxembourg. The activities of 5GCroCo are organized around three use cases: (1) Tele-operated Driving, (2) high-definition map generation and distribution for automated vehicles and (3) Anticipated Cooperative Collision Avoidance (ACCA). The results of the project help contribute to a true European transnational CCAM. This paper describes the overall objectives of the project, motivated by the discussed challenges of cross-border operation, the use cases along with their requirements, the technical 5G features that will be validated and provides a description of the planned trials within 5GCroCo together with some initial results.

Design and Characterization of Microscale Auxetic and Anisotropic Structures Fabricated by Multiphoton Lithography

The need for control of the elastic properties of architected materials has been accentuated due to the advances in modelling and characterization. Among the plethora of unconventional mechanical responses, controlled anisotropy and auxeticity have been promulgated as a new avenue in bioengineering applications. This paper aims to delineate the mechanical performance of characteristic auxetic and anisotropic designs fabricated by multiphoton lithography. Through finite element analysis the distinct responses of representative topologies are conveyed. In addition, nanoindentation experiments observed in-situ through scanning electron microscopy enable the validation of the modeling and the observation of the anisotropic or auxetic phenomena. Our results herald how these categories of architected materials can be investigated at the microscale.

Signalling boosts the evolution of cooperation in repeated group interactions

Many biological and social systems show significant levels of collective action. Several cooperation mechanisms have been proposed, yet they have been mostly studied independently. Among these, direct reciprocity supports cooperation on the basis of repeated interactions among individuals. Signals and quorum dynamics may also drive cooperation. Here, we resort to an evolutionary game-theoretical model to jointly analyse these two mechanisms and study the conditions in which evolution selects for direct reciprocity, signalling, or their combination. We show that signalling alone leads to higher levels of cooperation than when combined with reciprocity, while offering additional robustness against errors. Specifically, successful strategies in the realm of direct reciprocity are often not selected in the presence of signalling, and memory of past interactions is only exploited opportunistically in the case of earlier coordination failure. Differently, signalling always evolves, even when costly. In the light of these results, it may be easier to understand why direct reciprocity has been observed only in a limited number of cases among non-humans, whereas signalling is widespread at all levels of complexity.

Robotic-Assisted Colonoscopy Platform with a Magnetically-Actuated Soft-Tethered Capsule

Background and Aims: Colorectal cancer (CRC) is a major cause of morbidity and mortality worldwide. Despite offering a prime paradigm for screening, CRC screening is often hampered by invasiveness. Endoo is a potentially painless colonoscopy method with an active locomotion tethered capsule offering diagnostic and therapeutic capabilities. Materials and Methods: The Endoo system comprises a soft-tethered capsule, which embeds a permanent magnet controlled by an external robot equipped with a second permanent magnet. Capsule navigation is achieved via closed-loop interaction between the two magnets. Ex-vivo tests were conducted by endoscopy experts and trainees to evaluate the basic key features, usability, and compliance in comparison with conventional colonoscopy (CC) in feasibility and pilot studies. Results: Endoo showed a 100% success rate in operating channel and target approach tests. Progression of the capsule was feasible and repeatable. The magnetic link was lost an average of 1.28 times per complete procedure but was restored in 100% of cases. The peak value of interaction forces was higher in the CC group than the Endoo group (4.12N vs. 1.17N). The cumulative interaction forces over time were higher in the CC group than the Endoo group between the splenic flexure and mid-transverse colon (16.53Ns vs. 1.67Ns, p < 0.001), as well as between the hepatic flexure and cecum (28.77Ns vs. 2.47Ns, p = 0.005). The polyp detection rates were comparable between groups (9.1 ± 0.9% vs. 8.7 ± 0.9%, CC and Endoo respectively, per procedure). Robotic colonoscopies were completed in 67% of the procedures performed with Endoo (53% experts and 100% trainees). Conclusions: Endoo allows smoother navigation than CC and possesses comparable features. Although further research is needed, magnetic capsule colonoscopy demonstrated promising results compared to CC.

Wearable Augmented Reality Platform for Aiding Complex 3D Trajectory Tracing

Augmented reality (AR) Head-Mounted Displays (HMDs) are emerging as the most efficient output medium to support manual tasks performed under direct vision. Despite that, technological and human-factor limitations still hinder their routine use for aiding high-precision manual tasks in the peripersonal space. To overcome such limitations, in this work, we show the results of a user study aimed to validate qualitatively and quantitatively a recently developed AR platform specifically conceived for guiding complex 3D trajectory tracing tasks. The AR platform comprises a new-concept AR video see-through (VST) HMD and a dedicated software framework for the effective deployment of the AR application. In the experiments, the subjects were asked to perform 3D trajectory tracing tasks on 3D-printed replica of planar structures or more elaborated bony anatomies. The accuracy of the trajectories traced by the subjects was evaluated by using templates designed ad hoc to match the surface of the phantoms. The quantitative results suggest that the AR platform could be used to guide high-precision tasks: on average more than 94% of the traced trajectories stayed within an error margin lower than 1 mm. The results confirm that the proposed AR platform will boost the profitable adoption of AR HMDs to guide high precision manual tasks in the peripersonal space.

Nanostructured Organic/Hybrid Materials and Components in Miniaturized Optical and Chemical Sensors

In the last decade, biochemical sensors have brought a disruptive breakthrough in analytical chemistry and microbiology due the advent of technologically advanced systems conceived to respond to specific applications. From the design of a multitude of different detection modalities, several classes of sensor have been developed over the years. However, to date they have been hardly used in point-of-care or in-field applications, where cost and portability are of primary concern. In the present review we report on the use of nanostructured organic and hybrid compounds in optoelectronic, electrochemical and plasmonic components as constituting elements of miniaturized and easy-to-integrate biochemical sensors. We show how the targeted design, synthesis and nanostructuring of organic and hybrid materials have enabled enormous progress not only in terms of modulation and optimization of the sensor capabilities and performance when used as active materials, but also in the architecture of the detection schemes when used as structural/packing components. With a particular focus on optoelectronic, chemical and plasmonic components for sensing, we highlight that the new concept of having highly-integrated architectures through a system-engineering approach may enable the full expression of the potential of the sensing systems in real-setting applications in terms of fast-response, high sensitivity and multiplexity at low-cost and ease of portability.

Cortical encoding of melodic expectations in human temporal cortex

Humans engagement in music rests on underlying elements such as the listeners' cultural background and interest in music. These factors modulate how listeners anticipate musical events, a process inducing instantaneous neural responses as the music confronts these expectations. Measuring such neural correlates would represent a direct window into high-level brain processing. Here we recorded cortical signals as participants listened to Bach melodies. We assessed the relative contributions of acoustic versus melodic components of the music to the neural signal. Melodic features included information on pitch progressions and their tempo, which were extracted from a predictive model of musical structure based on Markov chains. We related the music to brain activity with temporal response functions demonstrating, for the first time, distinct cortical encoding of pitch and note-onset expectations during naturalistic music listening. This encoding was most pronounced at response latencies up to 350 ms, and in both planum temporale and Heschl's gyrus.

Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks

BACKGROUND

To assist people with disabilities, exoskeletons must be provided with human-robot interfaces and smart algorithms capable to identify the user's movement intentions. Surface electromyographic (sEMG) signals could be suitable for this purpose, but their applicability in shared control schemes for real-time operation of assistive devices in daily-life activities is limited due to high inter-subject variability, which requires custom calibrations and training. Here, we developed a machine-learning-based algorithm for detecting the user's motion intention based on electromyographic signals, and discussed its applicability for controlling an upper-limb exoskeleton for people with severe arm disabilities.

METHODS

Ten healthy participants, sitting in front of a screen while wearing the exoskeleton, were asked to perform several reaching movements toward three LEDs, presented in a random order. EMG signals from seven upper-limb muscles were recorded. Data were analyzed offline and used to develop an algorithm that identifies the onset of the movement across two different events: moving from a resting position toward the LED (Go-forward), and going back to resting position (Go-backward). A set of subject-independent time-domain EMG features was selected according to information theory and their probability distributions corresponding to rest and movement phases were modeled by means of a two-component Gaussian Mixture Model (GMM). The detection of movement onset by two types of detectors was tested: the first type based on features extracted from single muscles, whereas the second from multiple muscles. Their performances in terms of sensitivity, specificity and latency were assessed for the two events with a leave one-subject out test method.

RESULTS

The onset of movement was detected with a maximum sensitivity of 89.3% for Go-forward and 60.9% for Go-backward events. Best performances in terms of specificity were 96.2 and 94.3% respectively. For both events the algorithm was able to detect the onset before the actual movement, while computational load was compatible with real-time applications.

CONCLUSIONS

The detection performances and the low computational load make the proposed algorithm promising for the control of upper-limb exoskeletons in real-time applications. Fast initial calibration makes it also suitable for helping people with severe arm disabilities in performing assisted functional tasks.

Energy efficient partition allocation in mixed-criticality systems

This paper addresses the problem of energy management of mixed criticality applications in a multi-core partitioned architecture. Instead of focusing on new scheduling algorithms to adjust frequency in order to save energy, we propose a partition to CPU allocation that takes into account not only the different frequencies at which the CPU can operate but the level of criticality of the partitions. The goal is to provide a set of pre-calculated allocations, called profiles, so at run time the system can switch to different modes depending on the battery level. These profiles achieve different levels of energy saving and performance applying different strategies. We also present a comparison in terms of energy saving of the most used bin-packing algorithms for partition allocation. As this is an heuristic, it is not possible to ensure that our results involve the minimum energy consumption. For this reason, we also provide a comparison with a exact method, such as constraint programming.

User activity recognition system to improve the performance of environmental control interfaces: a pilot study with patients

BACKGROUND

Assistive technologies aim to increase quality of life, reduce dependence on care giver and on the long term care system. Several studies have demonstrated the effectiveness in the use of assistive technology for environment control and communication systems. The progress of brain-computer interfaces (BCI) research together with exoskeleton enable a person with motor impairment to interact with new elements in the environment. This paper aims to evaluate the environment control interface (ECI) developed under the AIDE project conditions, a multimodal interface able to analyze and extract relevant information from the environments as well as from the identification of residual abilities, behaviors, and intentions of the user.

METHODS

This study evaluated the ECI in a simulated scenario using a two screen layout: one with the ECI and the other with a simulated home environment, developed for this purpose. The sensorimotor rhythms and the horizontal oculoversion, acquired through BCI2000, a multipurpose standard BCI platform, were used to online control the ECI after the user training and system calibration. Eight subjects with different neurological diseases and spinal cord injury participated in this study. The subjects performed simulated activities of daily living (ADLs), i.e. actions in the simulated environment as drink, switch on a lamp or raise the bed head, during ten minutes in two different modes, AIDE mode, using a prediction model, to recognize the user intention facilitating the scan, and Manual mode, without a prediction model.

RESULTS

The results show that the mean task time spent in the AIDE mode was less than in the Manual, i.e the users were able to perform more tasks in the AIDE mode during the same time. The results showed a statistically significant differences with p<0.001. Regarding the steps, i.e the number of abstraction levels crossed in the ECI to perform an ADL, the users performed one step in the 90% of the tasks using the AIDE mode and three steps, at least, were necessary in the Manual mode. The user's intention prediction was performed through conditional random fields (CRF), with a global accuracy about 87%.

CONCLUSIONS

The environment analysis and the identification of the user's behaviors can be used to predict the user intention opening a new paradigm in the design of the ECIs. Although the developed ECI was tested only in a simulated home environment, it can be easily adapted to a real environment increasing the user independence at home.

Lost in Datafication? - A Typology of (Emotion) Data Contextualization

This article elaborates on the meaning of "context" for data created in interdisciplinary research on emotions. Particularly with regard to the potential reuse of scientific data, the elicitation of contexts can contribute to a better assessment of emotion data. Beyond a discussion of social scientific conceptualizations of "context" focusing on the situational and cultural contexts and their respective interrelations, this article presents the findings of an empirical study on datafication processes in interdisciplinary emotion research. Based on 123 survey responses and 15 in-depth interviews, a multitude of contextual dimensions will be reviewed. The typology of contexts, ranging from method-specific aspects and researchers' subjectivities to the contextual embeddedness of the research objects, provides a schema suitable for various epistemological approaches. The proposed typology can serve as a framework for emotion researchers to reflect on their research practice and interactions with research participants. The empirical findings also show the limitations of contextualization pertaining to tacit knowledge, implicit knowledge, embodied emotions and ethical considerations. The article concludes with suggestions for further research, pointing to intercultural settings, the integration of contexts and particular scenarios for data reuse.