Mohammad Saadeh

Identification of a force-sensing resistor for tactile applications

A force-sensing resistor is a conductive polymer that exhibits a decrease in resistance as the force applied at its surface increases. The aim of this study is to identify the characteristics of the force-sensing resistor for use in a refreshable and portable E-Braille device that can assist the blind and visually impaired persons. The force-sensing resistor is placed within a component dynamic testing device that is composed of a linear actuator that can generate different displacement loading profiles and a load cell that measures the applied forces. The system records the voltage, force, and the displacement profiles. Several strategies are used in the identification process. First, the mechanical properties of the force-sensing resistor are experimentally characterized. A second-order mechanical system whose parameters are function of the exciting frequency is created based on the results of this experiment. The performance of this model is evaluated using several test inputs. In an attempt to better identify the force-sensing resistor, alternative higher order linear and nonlinear models, including Hammerstein, Wiener, and Hammerstein–Wiener, are proposed using system identification techniques. The accuracy and robustness of these models are assessed using various loading profiles. The outputs of these models are compared with the experimental results.

Modeling of Hysteresis and Backlash for a Smart Fin with a Piezoelectric Actuator

This work presents a dynamic model of a smart fin that is activated by a piezoelectric bimorph actuator, which is made by bonding two MFCs. The actuator is completely enclosed within the fin. Earlier research has indicated that the use of a linear model for the fin dynamics does not fully describe the fin. This work presents a more realistic approach to this problem by incorporating additional components into the model. Therefore, a proportional damping matrix is introduced. It is also observed that experimental results exhibit hysteresis and backlash. A Bouc-Wen hysteresis model, combined with four backlash operators, is proposed. These backlash operators are used to model the observed saturation and the non-symmetry of the response. HFSGA is used to identify the optimal set of parameters for the damping matrix constants, the Bouc-Wen model, and the backlash operators. One input case is considered for training the genetic algorithm. The results show that proposed model can predict the hysteresis of the smart fin-actuator system under various operational conditions.

Design of a Wearable Fingertip Haptic Braille Device

Existing technologies and devices have facilitated the interaction of the blind or visually impaired (BVI) with their surroundings. However, reading remains an area where the potential of these technologies is not fully utilized. This work presents preliminary studies for the design of a finger-wearable E-Braille device that will allow the BVI to read electronic documents as they would read any document in Braille. The proposed device is wearable on a single finger on of the distal and middle phalanges (dorsal side). The main elements of the device are electrotactile display and force sensor. The electrotactile display is an electric board containing a matrix of electrodes that sends current to the fingertip for stimulating the touch feeling of a particular Braille character. By sending a sequence of Braille characters to this board, information can be sent to the user of the device through the generated electrotactile feeling. The force sensor is used in a feedback control loop to maintain steady contact pressure between the fingertip and the display board throughout the reading process. The entire finger-wearable E-Braille tactile display device is composed of a housing that can be customized to individual users, a miniature dc motor, mechanical components, and main elements. The initial testing of the proposed device is underway. Preliminary results indicate that the device can provide tactile sensation similar to that of reading a Braille document. The initial assessment of the device usability is underway.

A Hybrid Master-Slave Genetic Algorithm-Neural Network Approach for Modeling a Piezoelectric Actuator

This work presents an approach for developing the model of a smart fin dynamics that is activated by a fully-enclosed piezoelectric (PZT) bimorph actuator, which is created by bonding two Macro Fiber Composites (MFCs). Observing the dynamics of the fin indicates that the use of a linear dynamic model does not adequately describe its behavior. An earlier work proposed incorporating a proportional damping matrix as well as Bouc-Wen hysteresis model and backlash operators to create a more accurate model. However, the number of parameters describing the expanded model is large, which limits its use. Therefore, there is a need for a different approach for developing an alternative model of the fin. In this work, a hybrid master-slave Genetic Algorithm (GA)-Neural Network (NN) model is proposed to identify the optimal set of parameters for the damping matrix constants, the Bouc-Wen hysteresis model and the backlash operators. A total of nine sinusoidal input voltage cases that resemble a grid of three different amplitudes excited at three different frequencies are used to train and validate the model. Three input cases are considered for training the NN architecture, connection weights, bias weights and learning rules using GA. The NN consists of three layers: an input layer that has two nodes for the amplitude and the frequency of the input voltage, an output layer that has seven nodes for the backlash, hysteresis, and damping operators, and a hidden layer that is free to have any number of nodes between two and nine. The GA constantly performs natural selection of chromosomes that propagate best compilation of NN parameters. Simulation results show that the proposed model can predict the damping, hysteresis and backlash of the smart fin–actuator system under various operational conditions.© 2012 ASME

Development of a Measuring System of Contact Force for Braille Reading Using a Six-Axis Force Sensor

The objective of the recent research effort on tactile sensation is to provide the blind or visually impaired (BVI) persons with a more natural handling of their surrounding environment. To generate natural fingertip stimulations, the forces felt by the fingertip should be characterized. This work presents an approach to measure the fingertip forces while reading Braille characters. In the proposed experimental procedure, a subject is asked to identify five individual Braille characters that are hidden from view. Each Braille character is mounted on top of a six–axis force sensor. The experiment requires that each subject places a fingertip normal to a Braille character until the character is identified. The same experiment is repeated but with the subject applying pressure in the tangential direction. A new approach is proposed to identify these forces to ensure the validity of the readings. The subject is then asked to identify the letter out of images of the Braille characters. Twenty-eight subjects participated in the experiment so far. Data are statistically analyzed to obtain a general form of force-time history during the phase of Braille character identification. Normalization of the data is explored by identifying the equivalent fingertip pressure.Copyright

Identification of a Force Sensing Resistor for Tactile Applications

A force sensing resistor (FSR) is a conductive polymer that changes resistance with the application of pressure at its surface. FSR can be used for tactile applications. In this work, the use of FSR to measure the fingertip force within an electronic Braille reading device is considered. To achieve this goal, an experimental procedure to test the FSR’s response is proposed. In this experiment, the FSR is placed between a linear actuator and a load cell. The linear actuator generates different loading profiles to mimic various tactile forces. Identification process starts by applying static loadings at the FSR’s surface. These loads are used to calibrate the FSR and study its time drift. In the next phase of the process, an up-chirp signal is used to identify the dynamics of the FSR. The resulting data are modeled using system identification techniques to obtain possible dynamic models for the FSR. Both linear and nonlinear models are proposed. The linear model is compared to Hammerstein, Wiener, and Hammerstein-Wiener nonlinear models. The accuracy and robustness of the four models are assessed using various loading profiles. Numerical criteria are developed to compare these models with respect to the experimental results.Copyright

Modeling of Hysteresis and Backlash Within a Smart Fin With a Piezoelectric Actuator

This work presents a dynamic model of a smart fin, which is activated by a piezoelectric bimorph actuator that is made by bonding two Macro Fiber Composites (MFCs). The actuator is completely enclosed within the fin. Earlier research has indicated that the use of a linear model for the fin dynamics does not fully describe the fin. This work presents a more realistic approach to the problem by incorporating additional components into the model. Therefore, a proportional damping matrix is introduced. It was also observed that experimental results exhibit hysteresis and backlash. A Bouc-Wen hysteresis model is combined with two backlash operators to model the observed saturation and the non-symmetry of the response. Hybrid Fuzzy Simplex Genetic Algorithm (HFSGA) is used to identify the optimal set of parameters for the damping matrix constants, the Bouc-Wen model, and the backlash operators. The results show that proposed method can predict the hysteresis of the smart fin–actuator system under various operational conditions.Copyright