Real-time hand tracking for rehabilitation and character animation

Hand and finger tracking has a major importance in healthcare, for rehabilitation of hand function required due to a neurological disorder, and in virtual environment applications, like characters animation for on-line games or movies. Current solutions consist mostly of motion tracking gloves with embedded resistive bend sensors that most often suffer from signal drift, sensor saturation, sensor displacement and complex calibration procedures. More advanced solutions provide better tracking stability, but at the expense of a higher cost. The proposed solution aims to provide the required precision, stability and feasibility through the combination of eleven inertial measurements units (IMUs). Each unit captures the spatial orientation of the attached body. To fully capture the hand movement, each finger encompasses two units (at the proximal and distal phalanges), plus one unit at the back of the hand. The proposed glove was validated in two distinct steps: a) evaluation of the sensors’ accuracy and stability over time; b) evaluation of the bending trajectories during usual finger flexion tasks based on the intra-class correlation coefficient (ICC). Results revealed that the glove was sensitive mainly to magnetic field distortions and sensors tuning. The inclusion of a hard and soft iron correction algorithm and accelerometer and gyro drift and temperature compensation methods provided increased stability and precision. Finger trajectories evaluation yielded high ICC values with an overall reliability within application’s satisfying limits. The developed low cost system provides a straightforward calibration and usability, qualifying the device for hand and finger tracking in healthcare and animation industries.

Measuring end-to-end delay in real-time auralisation systems

One of the major challenges in the development of an immersive system is handling the delay between the tracking of the user’s head position and the updated projection of a 3D image or auralised sound, also called end-to-end delay. Excessive end-to-end delay can result in the general decrement of the “feeling of presence”, the occurrence of motion sickness and poor performance in perception-action tasks. These latencies must be known in order to provide insights on the technological (hardware/software optimization) or psychophysical (recalibration sessions) strategies to deal with them. Our goal was to develop a new measurement method of end-to-end delay that is both precise and easily replicated. We used a Head and Torso simulator (HATS) as an auditory signal sensor, a fast response photo-sensor to detect a visual stimulus response from a Motion Capture System, and a voltage input trigger as real-time event. The HATS was mounted in a turntable which allowed us to precisely change the 3D sound relative to the head position. When the virtual sound source was at 90º azimuth, the correspondent HRTF would set all the intensity values to zero, at the same time a trigger would register the real-time event of turning the HATS 90º azimuth. Furthermore, with the HATS turned 90º to the left, the motion capture marker visualization would fell exactly in the photo-sensor receptor. This method allowed us to precisely measure the delay from tracking to displaying. Moreover, our results show that the method of tracking, its tracking frequency, and the rendering of the sound reflections are the main predictors of end-to-end delay.

Detection of live and antibiotic-killed bacteria by quantitative real-time PCR of specific fragments of ribosomal RNA

RÉSUMÉ Le but d'un traitement antimicrobien est d'éradiquer une infection bactérienne. Cependant, il est souvent difficile d'en évaluer rapidement l'efficacité en utilisant les techniques standard. L'estimation de la viabilité bactérienne par marqueurs moléculaires permettrait d'accélérer le processus. Ce travail étudie donc la possibilité d'utiliser le RNA ribosomal (rRNA) à cet effet. Des cultures de Streptococcus gordonii sensibles (parent Wt) et tolérants (mutant Tol 1) à l'action bactéricide de la pénicilline ont été exposées à différents antibiotiques. La survie bactérienne au cours du temps a été déterminée en comparant deux méthodes. La méthode de référence par compte viable a été comparée à une méthode moléculaire consistant à amplifier par PCR quantitative en temps réel une partie du génome bactérien. La cible choisie devait refléter la viabilité cellulaire et par conséquent être synthétisée de manière constitutive lors de la vie de la bactérie et être détruite rapidement lors de la mort cellulaire. Le choix s'est porté sur un fragment du gène 16S-rRNA. Ce travail a permis de valider ce choix en corrélant ce marqueur moléculaire à la viabilité bactérienne au cours d'un traitement antibiotique bactéricide. De manière attendue, les S. gordonii sensibles à la pénicilline ont perdu ≥ 4 log10 CFU/ml après 48 heures de traitement par pénicilline alors que le mutant tolérant Tol1 en a perdu ≥ 1 log10 CFU/ml. De manière intéressant, la quantité de marqueur a augmenté proportionnellement au compte viable durant la phase de croissance bactérienne. Après administration du traitement antibiotique, l'évolution du marqueur dépendait de la capacité de la bactérie à survivre à l'action de l'antibiotique. Stable lors du traitement des souches tolérantes, la quantité de marqueur détectée diminuait de manière proportionnelle au compte viable lors du traitement des souches sensibles. Cette corrélation s'est confirmée lors de l'utilisation d'autres antibiotiques bactéricides. En conclusion, l'amplification par PCR du RNA ribosomal 16S permet d'évaluer rapidement la viabilité bactérienne au cours d'un traitement antibiotique en évitant le recours à la mise en culture dont les résultats ne sont obtenus qu'après plus de 24 heures. Cette méthode offre donc au clinicien une évaluation rapide de l'efficacité du traitement, particulièrement dans les situations, comme le choc septique, où l'initiation sans délai d'un traitement efficace est une des conditions essentielles du succès thérapeutique. ABSTRACT Assessing bacterial viability by molecular markers might help accelerate the measurement of antibiotic-induced killing. This study investigated whether ribosomal RNA (rRNA) could be suitable for this purpose. Cultures of penicillin-susceptible and penicillin-tolerant (Tol1 mutant) Streptococcus gordonii were exposed to mechanistically different penicillin and levofloxacin. Bacterial survival was assessed by viable counts, and compared to quantitative real-time PCR amplification of either the 16S-rRNA genes (rDNA) or the 16S rRNA, following reverse transcription. Penicillin-susceptible S. gordonii lost ≥ 4 log10 CFU/ml of viability over 48 h of penicillin treatment. In comparison, the Toll mutant lost ≤ 1 log10 CFU/ml. Amplification of a 427-base fragment of 16S rDNA yielded amplicons that increased proportionally to viable counts during bacterial growth, but did not decrease during drug-induced killing. In contrast, the same 427-base fragment amplified from 16S rDNA paralleled both bacterial growth and drug-induced killing. It also differentiated between penicillin-induced killing of the parent and the Toll mutant (≥4 log10 CFU/ml and ≤1 lo10 CFU/ml, respectively), and detected killing by mechanistically unrelated levofloxacin. Since large fragments of polynucleotides might be degraded faster than smaller fragments the experiments were repeated by amplifying a 119-base region internal to the origina1 427-base fragment. The amount of 119-base amplicons increased proportionally to viability during growth, but remained stable during drug treatment. Thus, 16S rRNA was a marker of antibiotic-induced killing, but the size of the amplified fragment was critical to differentiate between live and dead bacteria.

Analog circuit for real-time computation of respiratory mechanical impedance in sleep studies

The aim of this work was to develop a low-cost circuit for real-time analog computation of the respiratory mechanical impedance in sleep studies. The practical performance of the circuit was tested in six patients with obstructive sleep apnea. The impedance signal provided by the analog circuit was compared with the impedance calculated simultaneously with a conventional computerized system. We concluded that the low-cost analog circuit developed could be a useful tool for facilitating the real-time assessment of airway obstruction in routine sleep studies.

Detection of live and antibiotic-killed bacteria by quantitative real-time PCR of specific fragments of rRNA.

Assessing bacterial viability by molecular markers might help accelerate the measurement of antibiotic-induced killing. This study investigated whether rRNA could be suitable for this purpose. Cultures of penicillin-susceptible and penicillin-tolerant (Tol1 mutant) Streptococcus gordonii were exposed to mechanistically different penicillin and levofloxacin. Bacterial survival was assessed by viable counts and compared to quantitative real-time PCR amplification of either the 16S rRNA genes or the 16S rRNA, following reverse transcription. Penicillin-susceptible S. gordonii lost > or =4 log(10) CFU/ml of viability over 48 h of penicillin treatment. In comparison, the Tol1 mutant lost < or =1 log(10) CFU/ml. Amplification of a 427-bp fragment of 16S rRNA genes yielded amplicons that increased proportionally to viable counts during bacterial growth but did not decrease during drug-induced killing. In contrast, the same 427-bp fragment amplified from 16S rRNA paralleled both bacterial growth and drug-induced killing. It also differentiated between penicillin-induced killing of the parent and the Tol1 mutant (> or =4 log(10) CFU/ml and < or =1 log(10) CFU/ml, respectively) and detected killing by mechanistically unrelated levofloxacin. Since large fragments of polynucleotides might be degraded faster than smaller fragments, the experiments were repeated by amplifying a 119-bp region internal to the original 427-bp fragment. The amount of 119-bp amplicons increased proportionally to viability during growth but remained stable during drug treatment. Thus, 16S rRNA was a marker of antibiotic-induced killing, but the size of the amplified fragment was critical for differentiation between live and dead bacteria.

Analog circuit for real-time computation of respiratory mechanical impedance in sleep studies

The aim of this work was to develop a low-cost circuit for real-time analog computation of the respiratory mechanical impedance in sleep studies. The practical performance of the circuit was tested in six patients with obstructive sleep apnea. The impedance signal provided by the analog circuit was compared with the impedance calculated simultaneously with a conventional computerized system. We concluded that the low-cost analog circuit developed could be a useful tool for facilitating the real-time assessment of airway obstruction in routine sleep studies.

Real-time tree-foliage surface estimation using a ground laser scanner

The optimization of most pesticide and fertilizer applications is based on overall grove conditions. In this work we measurements. Recently, Wei [9, 10] used a terrestrial propose a measurement system based on a ground laser scanner to LIDAR to measure tree height, width and volume developing estimate the volume of the trees and then extrapolate their foliage a set of experiments to evaluate the repeatability and surface in real-time. Tests with pear trees demonstrated that the accuracy of the measurements, obtaining a coefficient of relation between the volume and the foliage can be interpreted as variation of 5.4% and a relative error of 4.4% in the linear with a coefficient of correlation (R) of 0.81 and the foliar estimation of the volume but without real-time capabilities. surface can be estimated with an average error less than 5 %.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

Oxytocin increases eye contact during a real-time, naturalistic social interaction in males with and without autism

Autism spectrum conditions (autism) affect ~1% of the population and are characterized by deficits in social communication. Oxytocin has been widely reported to affect social-communicative function and its neural underpinnings. Here we report the first evidence that intranasal oxytocin administration improves a core problem that individuals with autism have in using eye contact appropriately in real-world social settings. A randomized double-blind, placebo-controlled, within-subjects design is used to examine how intranasal administration of 24 IU of oxytocin affects gaze behavior for 32 adult males with autism and 34 controls in a real-time interaction with a researcher. This interactive paradigm bypasses many of the limitations encountered with conventional static or computer-based stimuli. Eye movements are recorded using eye tracking, providing an objective measurement of looking patterns. The measure is shown to be sensitive to the reduced eye contact commonly reported in autism, with the autism group spending less time looking to the eye region of the face than controls. Oxytocin administration selectively enhanced gaze to the eyes in both the autism and control groups (transformed mean eye-fixation difference per second=0.082; 95% CI:0.025–0.14, P=0.006). Within the autism group, oxytocin has the most effect on fixation duration in individuals with impaired levels of eye contact at baseline (Cohen’s d=0.86). These findings demonstrate that the potential benefits of oxytocin in autism extend to a real-time interaction, providing evidence of a therapeutic effect in a key aspect of social communication.

Real-time optical monitoring of the dip coating process

A significant part of film production by the coating industry is based on wet bench processes, where better understanding of their temporal dynamics could facilitate control and optimization. In this work, in situ laser interferometry is applied to study properties of flowing liquids and quantitatively monitor the dip coating batch process. Two oil standards Newtonian, non-volatile, with constant refractive indices and distinct flow properties - were measured under several withdrawing speeds. The dynamics of film physical thickness then depends on time as t(-1/2), and flow characterization becomes possible with high precision (linear slope uncertainty of +/-0.04%). Resulting kinematic viscosities for OP60 and OP400 are 1,17 +/- 0,03. St and 9,9 +/- 0,2 St, respectively. These results agree with nominal values, as provided by the manufacturer. For more complex films (a multi-component sol-gel Zirconyl Chloride aqueous solution) with a varying refractive index, through a direct polarimetric measurement, allowing also determination of the temporal evolution of physical thickness (uncertainty of +/- 0,007 microns) is also determined during dip coating.

Progress on holographic techniques to measure real-time phase and amplitude gratings in photosensitive materials

In this paper we present and demonstrate a technique that allows simultaneous and independent measurement of small changes in the refractive index and the absorption coefficient produced in photosensitive materials during holographic exposure. The technique is based on the synchronous detection of two-wave mixing signals in both directions of the transmitted interfering beams. By processing both signals it is possible to separate the diffraction contributions of the refractive index from the absorption coefficient and simultaneously stabilize the incident fringe pattern. The demonstration of this technique is undertaken by following the temporal evolution of the phase and amplitude modulations in photoresist films. To check the ability of the technique to perform numeric evaluations, for a positive photoresist the changes in the optical constants were measured and compared with those obtained using independent methods.

Design, construction, and performance of a real-time holographic refractometry prototype for liquid analysis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Methodology proposal for acquisition of biotelemetric data in a real time

This work presents a methodological proposal for acquisition of biometric data through telemetry basing its development on a research-action and a case study. Nowadays, the qualified professionals of physical evaluation have to use specific devices to obtain biometric signals and data. These devices in the most of the time are high cost and difficult to use and handling. Therefore, the methodological proposal was elaborate in order to develop, conceptually, a bio telemetric device which could acquire the desirable biometric signals: oxymetry, biometrics, corporal temperature and pedometry which are essential for the area of physical evaluation. It was researched the existent biometrics sensors, the possible ways for the remote transmission of signals and the computer systems available so that the acquisition of data could be possible. This methodological proposal of remote acquisition of biometrical signals is structured in four modules: Acquisitor of biometrics data; Converser and transmitter of biometric signals; Receiver and Processor of biometrics signals and Generator of Interpretative Graphs. The modules aim the obtention of interpretative graphics of human biometric signals. In order to validate this proposal a functional prototype was developed and it is presented in the development of this work.