A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the... more
A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the presented work is to combine the strengths of the two different algorithms in order to achieve a more effective optimization routine. The developed hybrid algorithm is tailored such that it has the capability to adapt to the given cost function during the optimization process. The proposed algorithm is tested on a set of different benchmark problems. In addition, the hybrid algorithm is utilized for solving the estimation problem encountered for estimating the finger force output given a surface electromyogram (sEMG) signal at the input. This estimation problem is commonly encountered while developing a control system for a prosthetic hand.
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A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the... more
A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the presented work is to combine the strengths of the two different algorithms in order to achieve a more effective optimization routine. The developed hybrid algorithm is tailored such that it has the capability to adapt to the given cost function during the optimization process. The proposed algorithm is tested on a set of different benchmark problems. In addition, the hybrid algorithm is utilized for solving the estimation problem encountered for estimating the finger force output given a surface electromyogram (sEMG) signal at the input. This estimation problem is commonly encountered while developing a control system for a prosthetic hand.
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Research Interests:
The objective of this work is to identify the motor point location from the obtained sEMG signals using Dempster Shafer theory (DST). The proposed technique is applied on data obtained from a male test subject. In particular, the sEMG... more
The objective of this work is to identify the motor point location from the obtained sEMG signals using Dempster Shafer theory (DST). The proposed technique is applied on data obtained from a male test subject. In particular, the sEMG signals and its corresponding skeletal muscle force signals from the Flexor Digitorum Superficialis are acquired at a sampling rate of 2000 Hz using a Delsys Bangnoli- 16 EMG system. The acquired sEMG signals are rectified and filtered using a Discrete Wavelet Transforms (DWT) with a Daubechies 44 mother wavelet. For the system identification, an Output Error (OE) model structure is assumed to obtain the dynamic relation between the sEMG signal and the corresponding finger force signals. Subsequently, model based probabilities and fuzzy inference based probabilities are obtained for discrete sensor locations of a sEMG sensor array. Considering these evidences, a DST based motor point location identification method is proposed. The results based on one subject show the potential of the proposed theory and approach for affectively identifying motor point locations using an array sEMG sensor.
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The weight and the cost of a wind turbine are two important factors that make wind energy competitive with other energy sources. The weight of the rotor is typically 40–80% of the total weight of the system. Thus, lowering cost by... more
The weight and the cost of a wind turbine are two important factors that make wind energy competitive with other energy sources. The weight of the rotor is typically 40–80% of the total weight of the system. Thus, lowering cost by reducing the weight of the blade is an important consideration. Another significant factor is the operational life of the machine. At present, a wind turbine’s life span is about 108 cycles or 20 years of continuous service. Innovative design solutions are needed in order to meet the criteria of improved stiffness, fatigue life, reliability, and efficiency. The directional property of an anisotropic composite material can be used to passively control wind turbine blade geometry in fluctuating wind speeds. Anisotropic materials show various levels of elastic coupling, based upon the ply angle in the layers. Structural behavior that exhibits both bending and twisting due to a pure bending load is known as twist-bend coupling. This type of behavior can be used for load reductions, particularly fatigue loads. The idea is to allow the blade to unload (reducing the speed) by allowing the wind induced bending moment to twist the blade. Increments in bending moment produce an increment in the twist that lowers the aerodynamically produced load. Higher blade stiffness can be achieved by full or partial replacement of glass fiber with carbon fiber. Carbon fibers are not used extensively on commercial wind turbine blades as they are more costly than glass fiber. The main objectives of this work are: (1) design a baseline model (made from glass fibers) of the wind turbine blade in accordance with published airfoil data; (2) conduct a finite element analysis of the blade and determine stresses, and strain within the blade; (3) develop a hybrid blade design by replacing the glass fibers with carbon fibers in the spar cap; and (4) validate the feasibility of implementing bend-twist coupling in the wind turbine blade by studying stresses, and strain behavior. By giving different orientation in the carbon fiber and changing the fiber layer, different designs are analyzed with regard to the above listed criteria.Copyright © 2011 by ASME
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A deadbeat predictive controller designed from input/output relationship of a linear system is presented in this paper. The method exploits an observable canonical form representation of the system under identification, and combines... more
A deadbeat predictive controller designed from input/output relationship of a linear system is presented in this paper. The method exploits an observable canonical form representation of the system under identification, and combines together the concepts of system identification and predictive controller design. There are two design parameters involved to determine the performance of the controller on-line. The formulation also satisfies simultaneously system identification and predictive controller design. Numerical example is given to illustrate the predictive controller performance.
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A new algorithm using Enhanced Continuous Tabu Search (ECTS) and genetic algorithm (GA) is proposed for parameter estimation problems. The proposed algorithm combines the respective strengths of ECTS and GA. The ECTS is a modified Tabu... more
A new algorithm using Enhanced Continuous Tabu Search (ECTS) and genetic algorithm (GA) is proposed for parameter estimation problems. The proposed algorithm combines the respective strengths of ECTS and GA. The ECTS is a modified Tabu Search (TS), which has good search capabilities for large search spaces. In this work, the ECTS is used to define smaller search spaces, which are used in a second stage by a GA to find the respective local minima. The ECTS covers the global search space by using a TS concept called diversification and then selects the most promising regions in the search space. Once the promising areas in the search space are identified, the proposed algorithm employs another TS concept called intensification in order to search the promising area thoroughly. The proposed algorithm is tested with benchmark multimodal functions for which the global minimum is known. In addition, the novel algorithm is used for parameter estimation problems, where standard estimation al...
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Parameter estimation is an important concept in engineering where a mathematical model of a system is identified with the help of input and output signals. The Classical Least Squares (LS) algorithm gives an unbiased estimate of the... more
Parameter estimation is an important concept in engineering where a mathematical model of a system is identified with the help of input and output signals. The Classical Least Squares (LS) algorithm gives an unbiased estimate of the parameters when the system noise is white. This property is lost when the system noise is colored — which is generally the case. In order to overcome the bias problem associated with the colored noise environment, one can use a whitening filter. The cost function in the case of a colored noise environment becomes multimodal when the signal to noise ratio is high and hence some intelligent optimization technique is required to find the global minimum. A new hybrid algorithm combining intelligent optimization techniques is proposed. This algorithm includes Enhanced Continuous Tabu Search (ECTS) and an elitism based Genetic Algorithm (GA) which is applied to the parameter estimation problem. ECTS is a modified version of Tabu Search (TS) applied to continuo...
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A control scheme for achieving object power grasping by a prosthetic hand is proposed. The control scheme is based on defining virtual spring-damper between finger tip and desired point, and a semi circular path for finger tip. It is... more
A control scheme for achieving object power grasping by a prosthetic hand is proposed. The control scheme is based on defining virtual spring-damper between finger tip and desired point, and a semi circular path for finger tip. It is shown that the suggested control scheme provides satisfactory performance in power grasping of prosthetic hand, without the need for additional complexity regarding equations for inverse kinematics, or inverse dynamics, and the information on tactile or force sensing or even object shape.
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A Condensed Hybrid Optimization Algorithm Using Enhanced Continuous Tabu Search and Particle Swarm Optimization. [ASME Conference Proceedings 2009, 89 (2009)]. Cheng-Hung Chen, Marco P. Schoen, Ken W. Bosworth. Abstract. ...
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ABSTRACT Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate... more
ABSTRACT Hard computing based optimization algorithms usually require a lot of computational resources and generally do not have the ability to arrive at the global optimum solution. Soft computing algorithms on the other hand negate these deficiencies, by allowing for reduced computational loads and the ability to find global optimal solutions, even for complex cost surfaces. This paper presents fusion of soft computing or control technique of genetic algorithm (GA) and hard computing technique of proportional integral derivative (PID) control with application to prosthetic hand. An adaptive neuro-fuzzy inference system (ANFIS) is used for inverse kinematics of the three-link index finger, and feedback linearization is used for the dynamics of the hand and the GA is used to find the optimal parameters of the PID controller. Simulation results with practical data shows good results for the prosthetic hand to hold a square object with a two-link thumb and index finger.
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Skeletal muscle force can be estimated using surface electromyographic (sEMG) signals. Usually, the surface location for the sensors is near the respective muscle motor unit points. Skeletal muscles generate a spatial EMG signal, which... more
Skeletal muscle force can be estimated using surface electromyographic (sEMG) signals. Usually, the surface location for the sensors is near the respective muscle motor unit points. Skeletal muscles generate a spatial EMG signal, which causes cross talk between different sEMG signal sensors. In this study, an array of three sEMG sensors is used to capture the information of muscle dynamics in terms of sEMG signals. The recorded sEMG signals are filtered utilizing optimized nonlinear Half-Gaussian Bayesian filters parameters, and the muscle force signal using a Chebyshev type-II filter. The filter optimization is accomplished using Genetic Algorithms. Three discrete time state-space muscle fatigue models are obtained using system identification and modal transformation for three sets of sensors for single motor unit. The outputs of these three muscle fatigue models are fused with a probabilistic Kullback Information Criterion (KIC) for model selection. The final fused output is estim...
Research Interests: Engineering, Computer Science, Biomechanics, Genetic Algorithms, Medicine, and 15 moreGenetic Algorithm, Probability, Humans, Computer Simulation, Model Selection, Crosstalk, Motor Unit, Bayesian filtering, Muscle Fatigue, Hand, Muscle contraction, Muscle Force, prosthesis Design, Discrete Time Systems, and Discrete time
The emerging technology of Augmented Reality can be applied to create novel developer tools in industrial robotics. This paper details the development of an app to interface with ABB robot controller using Microsoft HoloLens. RAPID code... more
The emerging technology of Augmented Reality can be applied to create novel developer tools in industrial robotics. This paper details the development of an app to interface with ABB robot controller using Microsoft HoloLens. RAPID code from the controller is parsed and converted to mirrored objects which can be displayed in the real world, on top and around the actual robot. This enables the user to interact with the robot in an augmented reality environment. The goal is to improve the human-robot communication by interpreting robot language and converting it to an interactive and intuitive interface.
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The arise of maintenance issues in mechanical systems is cause for decreased energy efficiency and higher operating costs for many small- to medium-sized businesses. The sooner such issues can be identified and addressed, the greater the... more
The arise of maintenance issues in mechanical systems is cause for decreased energy efficiency and higher operating costs for many small- to medium-sized businesses. The sooner such issues can be identified and addressed, the greater the energy savings. We have designed and implemented an automated predictive maintenance system that uses machine learning models to predict maintenance needs from data collected via data sensors attached to mechanical systems. As a proof of concept, we demonstrate the effectiveness of the system by predicting several operating states for a standard clothes dryer.
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Identification of a one-stage axial compressor system is addressed. In particular, we investigate the underlying dynamics of tip air injection and throttle activation to the overall compressor dynamics and the dynamics around the tip of... more
Identification of a one-stage axial compressor system is addressed. In particular, we investigate the underlying dynamics of tip air injection and throttle activation to the overall compressor dynamics and the dynamics around the tip of the compressor blades. A proposed subspace system identification algorithm is used to extract three mathematical models: relating the tip air injection to the overall dynamics of the compressor and to the flow dynamics at the tip of the compressor blade and relating the movement of the throttle to the overall compressor dynamics. As the system identification relays on experimental data, concerns about the noise level and unmodeled system dynamics are addressed by experimenting with two model structures. The identification algorithm entails a heuristic optimization that allows for inspection of the results with respect to unmodeled system dynamics. The results of the proposed system identification algorithm show that the assumed model structure for th...
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In the recent decade, a great deal of research has been devoted to active control of the unsteady flow in a wide variety of components and/or subsystems of aircraft, automobile and marine vehicles and industrial fluid machinery, because... more
In the recent decade, a great deal of research has been devoted to active control of the unsteady flow in a wide variety of components and/or subsystems of aircraft, automobile and marine vehicles and industrial fluid machinery, because small improvements in component and/or subsystem performance often lead to large payoffs. The term active flow control is used to describe the methods to actively manipulate flow fields with auxiliary power introduced to the flow. In this paper, a brief survey of the recent progress in active flow control research is made. The possibilities of further performance improvement using the theories and technologies of intelligent systems are discussed. Intelligent systems can be applied to improve sensing and actuating, increase model accuracy, and optimize the control schemes. The active flow control systems, on the other hand, may also challenge intelligent systems researchers and stimulate new development of intelligent tools.
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An efficient implementation of input design for on-line system identification is presented. The optimal input is calculated recursively based on the imminent available information content in the inverse correlation matrix of the data. The... more
An efficient implementation of input design for on-line system identification is presented. The optimal input is calculated recursively based on the imminent available information content in the inverse correlation matrix of the data. The new input is computed one step ahead of time with a predictive filter so that it will increase the information content in the inverse correlation matrix. A numerical example is provided which is based on a human respiratory system.
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The paper presents a new adaptive predictive control algorithm as well as the ability of disturbance rejection. The method combines together the concepts of system identification and adaptive predictive controller design. A multi-step... more
The paper presents a new adaptive predictive control algorithm as well as the ability of disturbance rejection. The method combines together the concepts of system identification and adaptive predictive controller design. A multi-step output predictor is generated to derive the identified matrix by a standard recursive least-square technique. A control force is also calculated in term of input/output time histories. The formulation satisfies simultaneously system identification and adaptive predictive controller design requirement for tracking purposes and showing an excellent result in disturbance rejection.
Research Interests: Computer Science, System Identification, Control Engineering, Model Predictive Control, Iterative Methods, and 12 moreAdaptive Control, Stability, Control Systems, Adaptive Systems, Identification, Tracking, Predictive models, Mathematical Model, Boolean Satisfiability, Input Output, Finite Difference Methods, and Predictive Control
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This paper presents a novel approach to the attitude determination problem of space vehicles. The proposed algorithm utilizes a modified Genetic Algorithm (GA) to solve the “lost in space” star pattern recognition problem associated with... more
This paper presents a novel approach to the attitude determination problem of space vehicles. The proposed algorithm utilizes a modified Genetic Algorithm (GA) to solve the “lost in space” star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) – reflected on an image taken by the onboard star tracker – are formulated using simple geometric descriptions. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the on board stored star map. The global minimum of the discrepancy represents the inertial coordinates of the FOV bore-sight. The concept of a Spiral Genetic Algorithms (SGA) is proposed where the search area decreases for consecutive GA, with consequently tighter constraints, making it converge to the desired location. Also the algorithm presented has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a real star map. Simulation results indicate competitive results to current star trackers in terms of accuracy.
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Attitude determination for unmanned spacecrafts usually employs star trackers. The specifications for these devices dictate fast, reliable, robust, and autonomous algorithms to satisfy various mission constraints. This results into simple... more
Attitude determination for unmanned spacecrafts usually employs star trackers. The specifications for these devices dictate fast, reliable, robust, and autonomous algorithms to satisfy various mission constraints. This results into simple algorithms for reduced power consumption and reduced overall weight. Optimizing a Star Pattern Recognition Algorithm (SPRA), using an imbedded star map, requires the optimization of the genetic operators that constitute the SPRA and the control parameters within the SPRA. Simultaneous optimization of the control parameters of the SPRA results into a multi-objective and multi-parameter constrained optimization problem. The optimizing of genetic algorithms is often time consuming and rather tedious by nature. In this work, a Multi-Objective Genetic Algorithm (MOGA) acting as a meta-level GA is applied together with a double objective transition selection scheme to achieve the optimization. This approach results in significantly expediting the cost as...
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Different types of stents are available to be implanted into blood-vessels (e.g., cardiovascular stent) or organs to maintain unobstructed blood flow or flow of tissue fluid through ducts (e.g., biliary and uretic stents and others). On... more
Different types of stents are available to be implanted into blood-vessels (e.g., cardiovascular stent) or organs to maintain unobstructed blood flow or flow of tissue fluid through ducts (e.g., biliary and uretic stents and others). On the one hand, it is imperative to use smart material such that its mechanical and elastic properties meet those of the ideal stent. A smart stent can change the orientation of the material(s) either by sensing control, temperature, or blood pressure, thus alter the overall shape of the stent (wiggling). These wiggling motions can prevent or reduce the deposit of cholesterol inside the stent’s lumen. On the other hand, there is a need for a better physiological model of how the tensile and shear stresses of a blood vessel are altered as the blood pressure changes along a defined length of that vessel and how the shape changes of the blood vessel could prevent the deposits of lipid material on the vessel wall thereby possibly decrease the likelihood of stenosis. However, the design of an ideal stent is complicated by the lack of proper materials and modeling studies, and difficulties to have an optimized design because of complexities of environmental factors. In this literature review, we therefore propose that an optimal stents design should incorporate the use of highly biocompatible material(s) of well characterized properties and with an adequately modeled mechanical design. We have discussed the importance and relevance of these issues for future stent design and fabrication.Copyright © 2007 by ASME
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The development of biosensors has been astronomical with the advent of the rapid growth of nanomaterials and nanotechnology. Nanobiosensors are becoming ubiquitous in numerous biomedical applications. Thus, there is a great impetus to... more
The development of biosensors has been astronomical with the advent of the rapid growth of nanomaterials and nanotechnology. Nanobiosensors are becoming ubiquitous in numerous biomedical applications. Thus, there is a great impetus to exploit smart nanoparticles and other nanomaterials for designing and fabricating smart nanobiosensors that are ultrasensitive and biocompatible. We are developing smart self-assembling biosensors that can detect specific biomolecules (e.g., enzymes, cofactors, metabolites, drugs, hormones, etc.) from micro- to nanomolar levels. Applications of the biosensors include detection of organ dysfunction and/or failure (e.g., liver malfunction, heart failure, etc.), early detection of malignant cancers, toxicant identification, and other biomarkers of diseases. Although nanobiosensors that possess high sensitivity and specificity have been designed and marketed, one fundamental issue remains to be resolved. This important issue is one concerning biocompatibil...
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Research Interests: Engineering, Computational Modeling, Fuzzy Logic, Energy Conversion, Control Systems, and 15 moreFuzzy Control, Control system, Noise, Damping, Computer Model, Intelligent System, Prediction Model, Energy Production, Power Take Off, Control Strategy, Force, Hybrid Control, Electrical And Electronic Engineering, Prediction Method, and model error
Research Interests: Sensory Feedback and SEMG
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Electromyography (EMG) signals are widely used for clinical and biomedical applications. One of the rapidly advancing fields of application of EMG is in the control of smart prosthetic devices for rehabilitation purposes. This paper... more
Electromyography (EMG) signals are widely used for clinical and biomedical applications. One of the rapidly advancing fields of application of EMG is in the control of smart prosthetic devices for rehabilitation purposes. This paper presents the investigation of the use of System Identification (SI) for modeling sEMG-Finger force relation in the pursuit of improving the control of a smart prosthetic hand. Finger force and sEMG data are generated by having the subject perform a number of random motions of the ring finger to simulate various force levels. Post-processing of the sEMG signal is performed using spatial filtering. The linear and nonlinear spatial filters are compared based on the ‘kurtosis’ improvements and also based on the fit values of the models obtained using system identification, in particular the Hammerstein-Wiener models. The results of the modeling using linear spatial filters were found to be in the region of 30-45%, some of these linear spatial filter masks we...
Parmod Kumar, CH Chen, Anish Sebastian, Madhavi Anugolu, Chandrasekhar Potluri, Amir Fassih, Yimesker Yihun, Alex Jensen, Yi Tang, Steve Chiu, Ken Bosworth, DS Naidu and Marco P. Schoen Measurement and Control Engineering Research Center... more
Parmod Kumar, CH Chen, Anish Sebastian, Madhavi Anugolu, Chandrasekhar Potluri, Amir Fassih, Yimesker Yihun, Alex Jensen, Yi Tang, Steve Chiu, Ken Bosworth, DS Naidu and Marco P. Schoen Measurement and Control Engineering Research Center College of Science ...
Research Interests: Computer Science, Spline smoothing and regression, Model Selection, IEEE, Active Force Control, and 10 moreData Fusion, adaptive neuro fuzzy inference system (ANFIS), Spatial Distribution, Mathematical Model, Skeletal Muscle, Spatial Filtering, Akaike Information Criterion, Curve fitting, Force Control, and Smoothing Spline
Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements... more
Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements are based on single sensor data. In this paper, array sensors are used along with a proposed sensor fusion scheme that result in a simple Multi-Input-Single-Output (MISO) transfer function. Experimental data is used along with system identification to find this MISO system. A Genetic Algorithm (GA) approach is employed to optimize the characteristics of the MISO system. The proposed fusion-based approach is tested experimentally and indicates improvement in finger/hand force estimation.
Research Interests: Engineering, System Identification, Genetic Algorithms, Medicine, Genetic Algorithm, and 14 moreSensor Arrays, Humans, Noise, Male, Sensor Fusion, Electromyography, Transfer Function, Surface Properties, Reproducibility of Results, Fingers, Experimental Data, Transfer Functions, Frequency Domain, and Biomechanical Phenomena
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AbstractEffective use of upper extremity prostheses depends on the two critical aspects of precise position and force control. Surface electromyographic (sEMG) signals can be used as a control input for the position and force actions... more
AbstractEffective use of upper extremity prostheses depends on the two critical aspects of precise position and force control. Surface electromyographic (sEMG) signals can be used as a control input for the position and force actions related to the prosthesis. In this paper, ...
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Abstract:-This paper presents a short study on the hybridization of a swarm based optimization algorithm with a single agent based algorithm. Swarm based algorithms and single agent based algorithms have each distinct advantages and... more
Abstract:-This paper presents a short study on the hybridization of a swarm based optimization algorithm with a single agent based algorithm. Swarm based algorithms and single agent based algorithms have each distinct advantages and disadvantages. One ...
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Abstract: - This paper presents the investigation of the use of System Identification (SI) for modeling sEMG-Finger Force relation in the pursuit of improving the control of prosthetic hands. Finger force and sEMG data is generated by... more
Abstract: - This paper presents the investigation of the use of System Identification (SI) for modeling sEMG-Finger Force relation in the pursuit of improving the control of prosthetic hands. Finger force and sEMG data is generated by having the subject perform a number of random ...
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... Marco P. Schoen† ... Pn i ,i = 1,2,...,n. (4) Using Eqn. (4), in conjunction with the actual UCAV heading ψn +βn, altitude commands are given to the UCAV autopilot to accomplish collision avoidance among all UCAVs in the battle-field.... more
... Marco P. Schoen† ... Pn i ,i = 1,2,...,n. (4) Using Eqn. (4), in conjunction with the actual UCAV heading ψn +βn, altitude commands are given to the UCAV autopilot to accomplish collision avoidance among all UCAVs in the battle-field. ...
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Elevated plantar pressure plays a major role in foot problems in diabetic patients. High pressures interrupt arterial blood flow, which is further compounded by the fact that diabetic patients lose sensory feedback from their feet, hence... more
Elevated plantar pressure plays a major role in foot problems in diabetic patients. High pressures interrupt arterial blood flow, which is further compounded by the fact that diabetic patients lose sensory feedback from their feet, hence are not able to change their stance leading to unnatural pressure points. This can lead to dermal ulcerations, necrosis, and ultimately to partial or total amputation of the foot. This paper presents a preliminary design of an intelligent shoe-insert that automatically monitors critical foot parameters in diabetic patients. The objective is to collect information on plantar pressure, temperature and moisture and come up with a system that would help in the prevention of foot ulcerations. This would be accomplished by keeping track of these parameters and sounding alarms when critical thresholds may be reached. This paper describes a comprehensive monitoring system with sensing, A/D, data storage, interpretation, transmission and alarm sounding capabilities in a single unit.Copyright © 2006 by ASME
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ABSTRACT Human muscle motion is initiated in the central nervous system where a nervous signal travels through the body and the motor neurons excite the muscles to move. These signals, termed myoelectric signals, can be measured on the... more
ABSTRACT Human muscle motion is initiated in the central nervous system where a nervous signal travels through the body and the motor neurons excite the muscles to move. These signals, termed myoelectric signals, can be measured on the surface of the skin as an electrical potential. By analyzing these signals it is possible to determine the muscle actions the signals elicit, and thus can be used in manipulating smart prostheses and teleoperation of machinery. Due to the randomness of myoelectric signals, identification of the signals is not complete, therefore the goal of this project is to complete a study of the characterization of one set of hand motions using current system identification methods. The gripping motion of the hand and the corresponding myoelectric signals are measured and the data captured with a personal computer. Using computer software the captured data are processed and finally subjected to several system identification routines. Using this technique it is possible to construct a mathematical model that correlates the myoelectric signals with the matching hand motion.