Architecture and applications of the FingerMouse: a smart stereo camera for wearable computing HCI

In this paper we present a visual input HCI system for wearable computers, the FingerMouse. It is a fully integrated stereo camera and vision processing system, with a specifically designed ASIC performing stereo block matching at 5Mpixel/s (e.g. QVGA 320×240at 30fps) and a disparity range of 47, consuming 187mW (78mW in the ASIC). It is button-sized (43mm×18mm) and can be worn on the body, capturing the user's hand and processing in real-time its coordinates as well as a 1-bit image of the hand segmented from the background. Alternatively, the system serves as a smart depth camera, delivering foreground segmentation and tracking, depth maps and standard images, with a processing latency smaller than 1ms. This paper describes the FingerMouse functionality and its applications, and how the specific architecture outperforms other systems in size, latency and power consumptio

Functionality-power-packaging considerations in context aware wearable systems

Wearable computing places tighter constraints on architecture design than traditional mobile computing. The architecture is described in terms of miniaturization, power-awareness, global low-power design and suitability for an application. In this article we present a new methodology based on three different system properties. Functionality, power and electronic Packaging metrics are proposed and evaluated to study different trade offs. We analyze the trade offs in different context recognition scenarios. The proof of concept case study is analyzed by studying (a) interaction with household appliances by a wrist worn device (acceleration, light sensors) (b) studying walking behavior with acceleration sensors, (c) computational task and (d) gesture recognition in a wood-workshop using the combination of accelerometer and microphone sensors. After analyzing the case study, we highlight the size aspect by electronic packaging for a given functionality and present the miniaturization trends for ‘autonomous sensor button

Tandem: A Context-Aware Method for Spontaneous Clustering of Dynamic Wireless Sensor Nodes

Wireless sensor nodes attached to everyday objects and worn by people are able to collaborate and actively assist users in their activities. We propose a method through which wireless sensor nodes organize spontaneously into clusters based on a common context. Provided that the confidence of sharing a common context varies in time, the algorithm takes into account a window-based history of believes. We approximate the behaviour of the algorithm using a Markov chain model and we analyse theoretically the cluster stability. We compare the theoretical approximation with simulations, by making use of experimental results reported from field tests. We show the tradeoff between the time history necessary to achieve a certain stability and the responsiveness of the clustering algorithm

Capacitive Left Hand Finger and Bow Sensors for Synchronization and Rhythmical Regularity Analysis in String Ensembles

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Designing micro-patterned Ti films that survive up to 10% applied tensile strain

Reducing the strain in brittle device layers is critical in the fabrication of robust flexible electronic devices. In this study, the cracking behavior of micro-patterned 500-nm-thick Ti films was investigated via uniaxial tensile testing by in situ SEM and 4-point probe measurements. Both visual observations by SEM and 4-pt resistance measurements showed that strategically patterned oval holes, off-set and rotated by 45°, had a significant effect on limiting the extent of cracking, specifically, in preventing cracks from converging. Failure with regard to electrical conduction was delayed from less than 2% to more than 10% strai

Monitoring of mental workload levels during an everyday life office-work scenario

Personal and ubiquitous healthcare applications offer new opportunities to prevent long-term health damage due to increased mental workload by continuously monitoring physiological signs related to prolonged high workload and providing just-in-time feedback. In order to achieve a quantification of mental load, different load levels that occur during a workday have to be discriminated. In this work, we present how mental workload levels in everyday life scenarios can be discriminated with data from a mobile ECG logger by incorporating individual calibration measures. We present an experiment design to induce three different levels of mental workload in calibration sessions and to monitor mental workload levels in everyday life scenarios of seven healthy male subjects. Besides the recording of ECG data, we collect subjective ratings of the perceived workload with the NASA Task Load Index (TLX), whereas objective measures are assessed by collecting salivary cortisol. According to the subjective ratings, we show that all participants perceived the induced load levels as intended from the experiment design. The heart rate variability (HRV) features under investigation can be classified into two distinct groups. Features in the first group, representing markers associated with parasympathetic nervous system activity, show a decrease in their values with increased workload. Features in the second group, representing markers associated with sympathetic nervous system activity or predominance, show an increase in their values with increased workload. We employ multiple regression analysis to model the relationship between relevant HRV features and the subjective ratings of NASA-TLX in order to predict the mental workload levels during office-work. The resulting predictions were correct for six out of the seven subjects. In addition, we compare the performance of three classification methods to identify the mental workload level during office-work. The best results were obtained with linear discriminant analysis (LDA) that yielded a correct classification for six out of the seven subjects. The k-nearest neighbor algorithm (k-NN) and the support vector machine (SVM) resulted in a correct classification of the mental workload level during office-work for five out of the seven subject

Contact resistance and overlapping capacitance in flexible sub-micron long oxide thin-film transistors for above 100 MHz operation

In recent years new forms of electronic devices such as electronic papers, flexible displays, epidermal sensors, and smart textiles have become reality. Thin-film transistors (TFTs) are the basic blocks of the circuits used in such devices and need to operate above 100 MHz to efficiently treat signals in RF systems and address pixels in high resolution displays. Beyond the choice of the semiconductor, i.e., silicon, graphene, organics, or amorphous oxides, the junctionless nature of TFTs and its geometry imply some limitations which become evident and important in devices with scaled channel length. Furthermore, the mechanical instability of flexible substrates limits the feature size of flexible TFTs. Contact resistance and overlapping capacitance are two parasitic effects which limit the transit frequency of transistors. They are often considered independent, while a deeper analysis of TFTs geometry imposes to handle them together; in fact, they both depend on the overlapping length (LOV) between source/drain and the gate contacts. Here, we conduct a quantitative analysis based on a large number of flexible ultra-scaled IGZO TFTs. Devices with three different values of overlap length and channel length down to 0.5 μm are fabricated to experimentally investigate the scaling behavior of the transit frequency. Contact resistance and overlapping capacitance depend in opposite ways on LOV. These findings establish routes for the optimization of the dimension of source/drain contact pads and suggest design guidelines to achieve megahertz operation in flexible IGZO TFTs and circuits

Towards long term monitoring of electrodermal activity in daily life

Manic depression, also known as bipolar disorder, is a common and severe form of mental disorder. The European research project MONARCA aims at developing and validating mobile technologies for multi-parametric, long term monitoring of physiological and behavioral information relevant to bipolar disorder. One aspect of MONARCA is to investigate the long term monitoring of Electrodermal activity (EDA) to support the diagnosis and treatment of bipolar disorder patients. EDA is known as an indicator of the emotional state and the stress level of a person. To realize a long-term monitoring of the EDA, the integration of the sensor system in the shoe or sock is a promising approach. This paper presents a first step towards such a sensor system. In a feasibility study including 8 subjects, we investigate the correlation between EDA measurements at the fingers, which is the most established sensing site, with measurements of the EDA at the feet. The results indicate that 88% of the evoked skin conductance responses (SCRs) occur at both sensing sites. When using an action movie as psychophysiologically activating stimulus, we have found weaker reactivity in the foot than in the hand EDA. The results also suggest that the influence of moderate physical activity on EDA measurements is low and has a similar effect for both recording sites. This suggests that the foot recording location is suitable for recordings in daily life even in the presence of moderate movemen

Unobtrusive physiological monitoring in an airplane seat

Air travel has become the preferred mode of long-distance transportation for most of the world's travelers. People of every age group and health status are traveling by airplane and thus the airplane has become part of our environment, in which people with health-related limitations need assistive support. Since the main interaction point between a passenger and the airplane is the seat, this work presents a smart airplane seat for measuring health-related signals of a passenger. We describe the design, implementation and testing of a multimodal sensor system integrated into the seat. The presented system is able to measure physiological signals, such as electrocardiogram, electrodermal activity, skin temperature, and respiration. We show how the design of the smart seat system is influenced by the trade-off between comfort and signal quality, i.e. incorporating unobtrusive sensors and dealing with erroneous signals. Artifact detection through sensor fusion is presented and the working principle is shown with a feasibility study, in which normal passenger activities were performed. Based on the presented method, we are able to identify signal regions in which the accuracies for detecting the heart- and respiration-rate are 88 and 82%, respectively, compared to 40 and 76% without any artifact remova