6 resultados para sensor orientation

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

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According to the opinion of clinicians, emerging medical conditions can be timely detected by observing changes in the activities of daily living and/or in the physiological signals of a person. To accomplish such purpose, it is necessary to properly monitor both the person’s physiological signals as well as the home environment with sensing technology. Wireless sensor networks (WSNs) are a promising technology for this support. After receiving the data from the sensor nodes, a computer processes the data and extracts information to detect any abnormality. The computer runs algorithms that should have been previously developed and tested in real homes or in living-labs. However, these installations (and volunteers) may not be easily available. In order to get around that difficulty, this paper suggests the making of a physical model to emulate basic actions of a user at home, thus giving autonomy to researchers wanting to test the performance of their algorithms. This paper also studies some data communication issues in mobile WSNs namely how the orientation of the sensor nodes in the body affects the received signal strength, as well as retransmission aspects of a TDMA-based MAC protocol in the data recovery process.

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Thermoplastic elastomer/carbon nanotube composites are studied for sensor applications due to their excellent mechanical and electrical properties. Piezoresisitive properties of tri-block copolymer styrene-butadiene-styrene (SBS)/ carbon nanotubes (CNT) prepared by solution casting have been investigated. Young modulus of the SBS/CNT composites increases with the amount of CNT filler content present in the samples, without losing the high strain deformation on the polymer matrix (~1500 %). Further, above the percolation threshold these materials are unique for the development of large deformation sensors due to the strong piezoresistive response. Piezoresistive properties evaluated by uniaxial stretching in tensile mode and 4-point bending showed a Gauge Factors up to 120. The excellent linearity obtained between strain and electrical resistance makes these composites interesting for large strain piezoresistive sensors applications.

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A model to simulate the conductivity of carbon nanotube/polymer nanocomposites is presented. The proposed model is based on hopping between the fillers. A parameter related to the influence of the matrix in the overall composite conductivity is defined. It is demonstrated that increasing the aspect ratio of the fillers will increase the conductivity. Finally, it is demonstrated that the alignment of the filler rods parallel to the measurement direction results in higher conductivity values, in agreement with results from recent experimental work.

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Battery separators based on electrospun membranes of poly(vinylidene fluoride) (PVDF) have been prepared in order to study the effect of fiber alignment on the performance and characteristics of the membrane. The prepared membranes show an average fiber diameter of ~272 nm and a degree of porosity of ~87 %. The gel polymer electrolytes are prepared by soaking the membranes in the electrolyte solution. The alignment of the fibers improves the mechanical properties for the electrospun membranes. Further, the microstructure of the membrane also plays an important role in the ionic conductivity, being higher for the random electrospun membrane due to the lower tortuosity value. Independently of the microstructure, both membranes show good electrochemical stability up to 5.0 V versus Li/Li+. These results show that electrospun membranes based on PVDF are appropriate for battery separators in lithium-ion battery applications, the random membranes showing a better overall performance.

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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.