1,721,067 research outputs found
Flex sensor characterization against shape and curvature changes
No full textResistive flex sensors were increasingly used in different areas for their interesting property to changetheir resistance when bent. In particular, they can be applied to human segment in biomedical devices toregister static and dynamic postures. In spite of their interesting properties, such as robustness, low priceand long life, they often demonstrate non-linear response and lower sensitivity at small bending angles.This paper provides investigation to improve flex sensors linearity and sensitivity to measure body jointangles with better accuracy. To this aim, an empirical model of the sheet (or surface) resistance of theactive layer, to simulate its behavior against the layer shape and size as well as the bending angle, wasprovided, to investigate whether changes of the standard rectangular shape can improve sensitivity andlinearity. In addition, to date commercial flex sensors have been characterized only against the bendingangle with a radius of curvature smaller than the device length, so limiting the application to small jointssuch as finger or knee. In order to extend the flex sensor applications, for instance, to measure the trunkposture in back disease and rehabilitation monitoring, the sensor response against a radius of curvaturegreater than the sensor length was analyzed. Finally, a new modeling technique, based on the inversemodel of the sensor characteristic, to enable fast measurements of the bending angle or the radius ofcurvature from sensor response also in real time, and fast calibration procedures, fitting the same modelto measurements with different joint size and even device, were developed
Measurements comparison of finger joint angles in hand postures between an sEMG armband and a sensory glove
No full textThis study compares the simultaneous measurements of finger joint angles obtained with a myoelectric armband (Myo), composed of eight surface electromyography (sEMG) sensors mounted on an elastic support, and a data glove, equipped with ten flex sensor on metacarpal and proximal finger joints. The flexion angles of all finger joints in four hand postures, that is open hand, closed hand and grasping two 3D printed molds of different size, were measured with a manual goniometer, and used to create, for each finger joint, a linear model from the measurement of the corresponding flex sensor in an electronic glove, as well as a regression model from the simultaneous measurements of 8 sEMG sensors of the Myo armband. The regression models were extracted testing different algorithms from the Matlab Regression Learner Toolbox. The performance of the models of the two wearable devices were evaluated and compared, applying a standard test, taken from literature on sensory gloves to evaluate the repeatability, reproducibility and reliability of finger joint measurements. These results were also compared with those reported by published works that followed the same standard test, using data gloves based on different sensing technologies. This work aims to demonstrate that the sEMG armbands can be applied to register the static postures of each finger joint with almost the same accuracy of sensory gloves
Towards a Volterra series representation from a neural network model
No full textWe have developed a Neural Network model able to reproduce some nonlinear characteristics of an
electronic device. However, electronic devices nonlinear analysis requires an analytical model, that allows to draw
conclusions about the device behavior. Such a model can be the Volterra series representation, which is a series
that has some particular terms, named the “Volterra kernels”. We want to show in this work how a Volterra model
can be built using the parameters of the proposed Neural Network model. We present a method for estimating the
Volterra kernels using the Neural Network parameters and some simulation results
Modeling wearable bend sensor behavior for human motion capture
No full textThe possibilities offered by variable resistance bend
sensors, applied as wearable devices on body garments, to recover
human joint bend angles for body segment movement tracking,
have been investigated, underlying their advantages and drawbacks
in real-time applications. Due to their pliability, sensitivity,
and cheapness, they could be a valid alternative to movement
analysis systems, based on optoelectronic devices or inertial
electronic sensors. This paper suggests a new method for sensor
characterization under fast bend and extension movements, to
extract few parameters of a synthetic model, which provide to
the users the chance to foresee their electrical performance in
different applications. The sensor and their extracted models
were applied to register the human knee rotation during a gait
cycle, either at slow speed (83 deg/s) for a walking pattern at
5 km/h, and at high speed (650 deg/s) for a running pattern
of a sprinter at 10 m/s, and finally the finger joint rotations at
their maximum angular velocity (900 deg/s). This was done for a
twofold purpose: from one hand, to assess the model capability to
predict the sensor performance, tracking human body segment
rotations at different speed, without the need of measurement;
from the other hand, to recover in real time the actual sensor
rotation from its resistance measurement, especially in high speed
applications, where its response is distorted. With this technique,
the mean error decreases from 22.5° to 3.7° in the worst cas
Shaping resistive bend sensors to enhance readout linearity
Full text linkResistive bend sensors have been increasingly used in different areas for their interesting property to change their resistance when
bent. They can be employed in those systems where a joint rotation has to be measured, in particular biomedical systems, to
measure human joint static and dynamic postures. In spite of their interesting properties, such as robustness, low price, and long
life, the commercial bend sensors have a response which is not actually linear, as an electronic device to measure bend angles
should be, to recover human posture without distortion. In this work, different interfaces for sensor device readout were analyzed
and compared from the output response linearity point of view. In order to obtain a sensor characteristic as closer as possible to
the ideal linear one, a way to calculate the sensor characteristic with a generalized resistive strip contour, starting from an empiric
sheet resistance model, was developed, in order to find what is the more suitable nonuniform geometry
Modeling and comparing the linear performance of non-uniform geometry bend sensors
No full textResistive bend sensors have been increasingly
used in different areas for their interesting property to
change their resistance when bent. They can be employed in
those systems where a joint rotation has to be measured,
such as in biomedical systems to measure human joint static
and dynamic postures. In spite of their interesting properties
the commercial bend sensors have a resistance vs. bent angle
characteristic which is not actually ideal as a linear function,
to measure bend angles, would be. In this work, we have
developed a way to calculate the sensor resistance for
different bending angles with a generalized strip contour, in
order to predict how shaping it with different non-uniform
geometries changes the resistance dependence on bending
angles, and investigate what kind of strip geometry can lead
to a more linear behavior
Sensory Systems for Human Body Gesture Recognition and Motion Capture
No full textSensor-based systems for detecting, recognizing and measuring the position and movement of the human body in a three-dimensional space with great accuracy and precision have been widespread in last decades. Starting from consolidated optical systems, which still represent the reference for other cost effective systems, this work presents smart solutions for motion capture and posture recognition systems, either based on the most popular inertial sensors, but also flex sensors, such as the sensory gloves for measurement of bending angles of finger joints, whose development increases at the same rate of application developed to exploit the potential of these systems. Recently surface electromyography (sEMG) is gaining more and more importance in gesture recognition systems for disabled skills assessment and prosthesis control of transradial amputees
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