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A fully autonomous inductive boost converter for indoor photovoltaic harvesting with maximum power point tracking circuit is implemented in a commercial 0.25um CMOS process. The converter can handle input power from 5uW up to 10mW and charge a battery or a super-capacitor up to 5V. Its control circuit consumes between 0.8uA and 2.1uA depending on the input power level, resulting in a peak end-to-end efficiency of 70% when tracking a maximum input power of 17uW.

Brain-computer interfaces (BCI) based on Steady State Visual Evoked Potential (SSVEP) can provide higher information transfer rate and require shorter calibration than BCIs based on other modalities. For safety and comfort, the frequency of the repetitive visual stimuli seliciting the SSVEP should be higher than 30 Hz. However, in such frequency range, only a limited number of frequencies can elicit sufficiently strong SSVEPs for BCI purposes. Thus, the conventional approach, consisting in presenting various repetitive visual stimuli at different frequencies, is not feasible for high frequencies. Indeed this would bring low communication bitrates. To increase the number of possible repetitive visual stimuli, we consider modulating the phase of the stimulus instead of the frequency. In this paper, we present an approach to reliably detect the stimulus phase from the recorded SSVEP.

The amount of information present in HRTFs and the required processing capabilities for real-time and inter-active binaural rendering have long been a challenge for many applications for binaural rendering. More recently, parametric methods to capture the perceptually-relevant information from HRTFs have been developed. By means of extracting perceptually-relevant attributes from HRTF pairs, binaural rendering can be performed at lower complexity compared to the employment of HRTF convolution. Furthermore, parameter-based binaural rendering can be effiently integrated with parametric audio coders. Last but not least, parametric spatial processing can be used to provide a more convincing spatial reproduction for conventional stereo signals. This paper provides an overview of the perceptual consequences and limitations of HRTF parameterization, its applications, and relevant standardization efforts.

During the last decade, a number of research activities have been performed to enable user interfaces and the underlying user activities to be migrated from one device to another. We call this “Nomadic User Interfaces”. The primary goal of these research activities has been to develop the technologies to enable this. However, not much is known about the usability aspects of Nomadic User Interfaces. In this paper we present the results of three different user tests that we conducted to investigate the usefulness and the usability issues of several prototype Nomadic User Interface systems that we developed.

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason are strong pose differences between these follow-up acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. A method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. No 3D image data is used. The accuracy of pose estimation is validated with chest phantom images under controlled geometric conditions.

Lasers will bring a further step in terms of compactness and efficiency for projection systems. However, the availability of suitable green laser sources limits the advent of laser projection. Blue diode pumped solid-state lasers are presented here as one promising way to realize green, red and orange lasers that are specifically suitedfor projection applications.

We study the effects of digital photo sharing on social connectedness of people with special needs. We target people dealing with a transition in life that forced them to live away from their family and friends. Our study included four people with spinal-cord injury staying in a rehabilitation centre and eight elderly people staying in a nursing home. Each participant was provided with a web-enabled digital photo frame and their family members were provided with a camera phone. The results of our study show positive effects. For rehabilitants photo sharing simplified the way they could reconnect to their family. For the elderly people, photo sharing served as 'food for talk'.

In this paper we present the “Breathe with the Ocean” system concept, which is a breathing guidance system that aims to help a user relax. It provides an immersive experience where the user is virtually present at an ocean shore. We describe the design and implementation of three embodiments of this concept and preliminary evaluations based on trial sessions. The feedback provided by the three systems to the user is in the form of audio, haptic (tactile) and visual (light) stimuli. Haptic stimuli are provided through a novel actuation device that we developed, the Touch Blanket. The three systems introduced are respectively a fixed-rate breathing guidance system, an adaptive breathing following system and an adaptive-rate breathing guidance system that maximizes heart-rate variability amplitude. We discuss the advantages and disadvantages of using open-loop versus closed-loop implementations of these types of systems, as well as our experiences so far in using multimodal stimuli for breathing guidance.

Breathing motion complicates many image-guided interventions working on the thorax or upper abdomen. However, prior knowledge provided by a statistical breathing model, can reduce the uncertainties of organ location. In this paper, a prediction framework for statistical motion modeling is presented and different representations of the dynamic data for motion model building of the lungs are investigated. Evaluation carried out on 4D-CT data sets of 10 patients showed that a displacement vector-based representation can reduce most of the respiratory motion with a prediction error of about 2 mm, when assuming the diaphragm motion to be known.

The design, manufacturing and application of electrowetting-based liquid lenses in optical devices are discussed. Results are presentedof applying this lens in miniature autofocus and zoom cameras, optical recording and illumination systems. Conclusions: We presented the working principle and a concept for mass manufacturing of liquid lenses and we demonstrated that they can be used for focusing and zooming in miniature cameras, for dual-layer readout inBlu-ray Disc optical recording systems and for dynamic effects in illumination systems. This shows that liquid lenses can have a significant impact on future miniature optical devices.

Stereo audio signal is often modeled as a mixture of instantaneously mixed primary components and uncorrelated ambience components. This paper focuses on the estimation of the primary-to-ambience energy ratio, PAR. This measure is useful for signal decomposition in stereo and multichannel audio coding, format conversion, and spatial audio enhancement. The conventional approaches for the estimation of the ratio are based on the ratio of eigenvalues which requires equal energies of the ambience signals. This often leads to an inaccurate estimate of PAR. An alternative measure is proposed which reduces those estimation errors but requires a priori information about the primary component signal. The performance of the method is demonstrated with synthetic signals and a large collection of stereo audio data.

Experiments were conducted to measure perceptual changes in sharpness and contrast due to two environmental factors: viewing distance and ambient illumination. A field study was completed in two retail stores in which television customers were polled about image quality at long and short viewing distances. The study identified sharpness, brightness, and contrast as the perceptual attributes most influenced by changes in viewing distance. Subsequently, a viewing experiment was conducted in the laboratory in which the sizes of just noticeable differences (JNDs) of sharpness, black level, and white level were measured at different viewing distances and ambient illumination levels. The experiment used a two up, one down staircase method with a reference to detect thresholds. It was found that sensitivity to sharpness decreased with longer viewing distance and was unaffected by ambient illumination, and sensitivity to black level decreased with either increased distance or increased illumination. Sensitivity to white level was not significantly affected by either factor. These results may be used to select display settings or design parameters to suit different viewing situations.

There is a growing interest in multi-modal signal processing: sets of related signals are jointly processed to extract information that is otherwise hidden when considering the different modalities independently. One popular problem in crossmodal processing is the localization of visual sources synchronous with audio stimuli. Audiovisual source localization allows to pinpoint and extract salient audio-video information from a scene, enabling innovative applications in communication, interaction and gaming. In this paper we aim to achieve cross-modal localization in real-time using single camera, single microphone data. Existing works use complex statistical data models or complex representations of audio and video features, limiting their applicability in realtime systems. In this paper we propose a simple yet effective algorithm that allows to detect and localize in real-time synchronous audio-video sources. The proposed approach obtains the best speaker localization performances reported to date on the popular CUAVE database, while running in real-time and without requiring any training.

A new method using a thin-film multilayer filter is described to couple light from high-power LEDs into a thin light guide such as an LCD backlight. Light emitted below the critical angle is reflected back to the LED and recycled. Large-angle emitted light passes the filter and is transported by total internal reflection in the light guide. The light guide can be as thin as 0.3mm for an LED of 1x1mm2, and the best coupling efficiency is estimated to be 82%. With this approach, a backlight system can be greatly simplified but also compactcollimators can be realized. In this paper the optical design and testing of the filter is described, and a 1mm thick, 6.5mm diameter collimator is presented. Measurements on prototypes show good agreement with the designed characteristics.

We investigate the potential to enhance breast cancer event predictors by exploiting subtype information. We do this with a two-stage approach that first determines a sample's subtype using a recent module-driven approach, and secondly constructs a subtype-specific predictor to predict a metastasis event within five years. Our methodology is validated on a large compendium of microarray breast cancer datasets,including 43 replicate array pairs for assessing subtyping stability. Note that stratifying by subtype strongly reduces the training set sizes available to construct the individual predictors, which may decrease performance. Besides sample size, other factors likeunequal class distributions and differences in the number of samplesper subtype, easily obscure a fair comparison between subtype-specific predictors constructed on different subtypes, but also between subtype specific and subtype a-specific predictors. Therefore, we constructed a completely balanced experimental design, in which none ofthe above factors play a role and show that subtype-specific eventpredictors clearly outperform predictors that do not take subtype information into account.

Appropriate design of the interaction between humans and robots will be a crucial factor for the acceptance of new robotic products. Apromising approach is to equip robots with life-like and social characteristics. A coherent personality expressed through behavior can help users to understand and predict the behavior of a robotic appliance. In this paper, we describe existing design approaches and arguethat an integrated design process is needed.

In anonymous credential schemes, users obtain credentials on certain attributes from an issuer, and later show these credentials to a relying party anonymously and without fully disclosing the attributes. In this paper, we introduce the notion of (anonymous) credential schemes with encrypted attributes, in which issuers certify credentials on encrypted attributes to users. These schemes allow for the possibility that none of the involved parties, including the user, learns the values of the attributes. In fact, we will treat several variations differing in which parties see which attributes in the clear. We present effcient constructions of these new credential schemes, starting from a credential scheme by Brands, and we show that the security of Brands' original scheme is retained. Finally, we sketch several interesting applications of these novel credential schemes.

We present a prototype of a personalized recipe advice system, whichfacilitates its users to make health-aware meal choices based onpast selections.To stimulate the adaptation of a healthier lifestylea goal setting mechanism is applied in combination with personalizedrecipe suggestions.

This paper presents a system design study for wearable sensor devices intended for healthcare and lifestyle applications based on ECG,EEG and activity monitoring. In order to meet the low-power requirement of these applications, a dual-core signal processing system is proposed which combines an ultra-low-power bio-medical Application Specific Instruction-set Processor (BioASIP) and a low power general-purpose micro-controller (MSP430). To validate the merits of the proposed architecture, system-level power analysis and trade-offs are conducted using real hardware measurements of an ECG R-peak detectionapplication. The results show that the proposed dual-core architecture consumes around 65.38µW, about 25.8x smaller than an MSP430-onlyapproach. Out of 65.38µW, the BioASIP consumes only 11µW and the rest is used in the analog front-end, A/D conversion, and control tasks.

The Discriminative Generalized Hough Transform (DGHT) is a method for object localization, which combines the standard GHT with a discriminative training technique. Thereby the aim of the discriminativetraining is to equip the models used in the GHT with individual model point weights such that the localization error in the GHT becomesminimal. In this paper we want to introduce an extension of the DGHTusing a multi-level approach to reduce processing time and to improve localization accuracy. The approach searches for the target object on multiple resolution levels and combines this information for faster and better results. The advantage of the approach is demonstrated on low-resolution, whole-body MR images, which are intended for PET attenuation correction.