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Motion difficulties, specifically the walk and displacement, are very common afflictions, mainly caused by some type of injury. The recurrent kind of rehabilitation treatments involve exercises of active and passive mobility. The success in the treatment and the early return to sports activity depends largely on the rehabilitation process. This should begin immediately after the production of the wound or the surgical process to repair the damage. The objective of this work is to develop a low-cost, easy manufacturing and assembly device, capable of providing exercises of active mobility. We designed an affordable and adaptable six-bar Watt linkage, coupled to a conventional leg extension machine. Structural and dynamic studies determine its safeness and its efficiency. The results of the kinematic and dynamic studies showed that the available range of motion for the different configurations goes from 24° to 109°. Its structural integrity was analyzed, pointing out that the weakest link had a Factor of Safety of 1.3, while the highest presents a value of 14.7, so that, the material overpasses the load needs. Based on the obtained results, a six-bar linkage is a viable option for the development of low-cost, therapeutic active devices.

Fuzzy processors are used for control actions in nonlinear mechatronic systems where high processing speed is required. The Field Programmable Gate Arrays (FPGA) are a good option to implement low cost fuzzy hardware in a short development time. A very important block in fuzzy hardware is the fuzzifier, since it affects directly in the accuracy of the result and in the processing time for obtaining a fuzzy number. There have been many design methodologies intended for enhancing the performance of this block. This paper presents a parallel fuzzifier circuit called α-BSSF. Its main design characteristics are the use of α-levels for membership representation, usage of integer numbers, and avoiding time-consuming operations. As result, we obtained a fuzzifier that shows advantages in the reduction of the response time and computational resources against the existing sequential fuzzification methods. This proposal is targeted not only for T1FS, but also for T2FS, since the membership calculation through fuzzifier is applied in the same way but twice.

Load distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with techniques that use integral reasoning produce easy understanding medical tools for assisting in treatment, early detection, and the development of preventive strategies. The present research compares the classification of human plantar foot alterations using Fuzzy Cognitive Maps (FCM) trained by Genetic Algorithm (GA) against a Multi-Layer Perceptron Neural Network (MLPNN). One hundred and fifty-one subject volunteers (aged 7–77) were classified previously with the flat foot (n = 70) and cavus foot (n = 81) by specialized physicians of the Piedica diagnostic center. The trial walking was conducted using plantar pressure platforms FreeMed®. The foot surface was divided into 14 areas that included toe 1 st to 5th, metatarsal joint 1st to 5th, lateral midfoot, medial midfoot, lateral heel, and medial heel. Pressure data were normalized for each area. Better performance in the classification using small amounts of data were found by using Fuzzy rather than non-Fuzzy approach.

This paper describes an experiment done to locate surfaces in three dimensions using a single pulse-echo sonar in the air. The results aim that is possible build a 3D map of obstacles discarding many fake points produced by noise, speckle, cross-talking, multiple reflections and a wide beam pattern.

Force distribution on foot surface allows to understand the human mechanical behavior, providing detailed information for the evaluation of foot alterations. In diagnosis for diseases related to plantar pathologies, there are many devices for plantar pressure measurement, and corresponding algorithms for data analyzing, providing medical tools for assisting in treatment, early detection, and the development of preventive strategies. In medicine, use of computational intelligence is increasing, making the diagnostic processes faster and more accurate. Clinical Decision Support Systems (CDSS) can handle large amounts of data to improve decision-making, helping to prevent the deterioration of people's health. Numerous approaches have been applied over the past few decades to solve medical problems such as hepatitis, diabetes, liver disease, pathological gait, and plantar diseases, among others. This paper presents the developments reported in the literature for detecting diseases through plantar pressure data and the corresponding algorithms for its analysis and diagnosis, using different electronic measurements systems. Finally, we present a discussion about the future work required to improve in the field of plantar pressure diagnosis algorithms using different approaches suggested by the authors as potential candidates. In this sense, hybrid systems which include fuzzy concepts are the most promising methodology.

Gait is an important part of our life, as it affects many daily activities. Special footwear is fundamental to obtain an ergonomic gait and to extract data for analysis. The plantar foot pressure can be employed to detect many kinds of disorders, suggest improvements in treatments, rehabilitation tasks, patient monitoring, development of orthopedic devices, and other applications. In recent years, attention to this topic has grown and is reflected in many works issued in both commercial and academic groups, and has focused on the development of devices for foot plantar pressure measurement with applications in medicine, sports, and research. First works on this subject appeared around 1963 and have continuously evolved with emerging technologies. This paper reviews the reported developments in the field of footwear-embedded sensors for gait measurement, monitoring, diagnosis, and analysis in rehabilitation. Future work is proposed to improve the field of measurement of the footprint with electronic devices.

When performing commutation at induction motors based in PWM, a change in the switching frequency can take several clock cycles to be reflected in the windings generating harmonics that could damage the motor or generate an erroneous modulation. Most of the high-performance inverters use the Space Vector PWM given its minor switching losses and its capability to reduce the harmonics in the output signals. Nonetheless, the SVPWM requires complex calculation in online operation, which is the major concern for real-time implementations. Even that there are problems related to the development of technology that does not use the sine waveform to drive an induction motor and considering the availability and capability of Direct Digital Synthesizers (DDS) technology, we developed a hardware–software system to propose a modulation strategy called Space Vector DDS. The SVDDS can synthesize any digital waveform besides the sine waveform, becoming a more versatile approach. This proposal is the first one to couple the DDS in the commutation of an induction motor. As summary, the main features of our SVDDS system are its capability to synthesize any discrete waveform, improvement of control response parameters (13% for a load test and 12% for a speed test, compared with SVPWM), a low value of the total harmonic distortion index (4.88%) and reduction of the mathematical processing (system response of 21.364 ns).

Mexico is adopting the competence-based model for education improvement. One of the major problems is to quantify the results of assessment to provide a grade considering subjective data. It commonly results in the assignation of an arbitrary grade which is estimated by the experience of the teacher using the evidence from the students. This paper presents a fuzzy system for calculating the grade assignment at undergraduate courses considering the student competences. The obtained results are compared against the grades that are calculated with the traditional average method and those obtained with the pass-fail checklists method.

Mobility is an important part of our daily life, hence the good health of our lower extremities is essential. Gait analysis using kinetic data along with medical Decision Support System or Computer Aided Diagnosis provide to physicians support in gait disorder detection, the risk of foot ulcerations especially in diabetic patients, leg discrepancy, footprint pathologies, and many other applications in biomedical diagnosis. To increase confidence in the system, it is necessary to use a technique which uses a comprehensive reasoning and provide explanations to discover new relationships and combination of features. The present research is an attempt to assess the viability of investigating human footprint alterations using Fuzzy Cognitive Maps (FCM) combined with a Genetic Algorithm (GA), and it is part for preparation of investigating more efficient algorithms in the future. In the proposed method, GA is used to learn the weight matrix of an FCM model applied to identify alterations in the human footprint. Using historical plantar pressure data obtained by electronic platforms, combined with FCM and optimization algorithm, a promising outcome is presented in the field of Computer-Aided Diagnosis.

The aim of this review is to analyse the different existing technologies for gait rehabilitation, focusing mainly in robotic devices. Those robots help the patient to recover a lost function due to neurological gait disorders, accidents or after injury. Besides, they facilitate the identification of normal and abnormal features by registering muscle activity providing the doctor important data where he can observe the evolution of the patient.A deep literature review was realized using selected keywords considering not only the most common medical and engineering databases, but also other available sources that provide information on commercial and scientific gait rehabilitation devices. The founded literature for this review corresponds to control techniques for gait rehabilitation robots, since the early seventies to the present year.Different control strategies for gait analysis in rehabilitation devices have been developed and implemented such as position control, force and impedance control, haptic simulation, and control of EMG signals. These control techniques are used to analyze the force of the patient during therapy, compensating it with the force generated by the mechanism in the rehabilitation device. It is observed that the largest number of studies reported, focuses on the impedance control technique. Leading to include new control techniques and validate them using the necessary protocols with ill patients, obtaining reliable results that allows a progressive and active rehabilitation.With this exhaustive review, we can conclude that the degree of complexity of the rehabilitation device influences in short and long-term therapeutic results since the movements become more controlled. However, there is still a lot of work in the sense of motion control in order to perform trajectories that are more alike the natural movements of humans. There are many control techniques in other areas, which seek to improve the performance of the process. These techniques may possibly be applicable in gait rehabilitation devices, obtaining controllers that are more efficient and that adapts to different people and the necessities that entail every disease. Implications for Rehabilitation Rehabilitation helps people to improve the activities of their daily life, allowing them to observe their progress in the functional abilities as the months pass by with intensive and repetitive therapies. There is a mobility issue when the patient needs to move to the hospital or to the laboratory, which is not always feasible. For overcoming it, patients use the equipment at home to perform their daily therapy. However, they need the sufficient knowledge about its operation, also about the therapeutic movements, the therapy duration and the movement speed. Besides, is necessary to place the equipment in a proper and lively environment that helps to forget or reduce pain while the patient moves his joints progressively. The purpose of robotic rehabilitation devices is to generate repetitive and progressive movements, according to the motor disability. There are training trajectories to follow, which motivate patients to generate active movements. The benefits of robotic rehabilitation depend on the ability of each patient to adapt to the speed and load variations generated by the device, improving and reinforcing motor functions in therapy, especially in patients with advanced disabilities in early rehabilitation. Multi-joint rehabilitation devices are more effective than single-joint rehabilitation devices because they involve a higher number of muscles in the therapy. The greater the number of degrees of freedom (DoF) of the device, it cushions its effect in the patient because the inertia is reduced and higher torques are generated. The assistive technological devices allows to explore different rehabilitation techniques that motivate the patient in therapy, increasing appropriately the energy and pressure in the blood which is reflected in gradually recovering his ability to walk.

In this paper, an ultrasonic arc map method for flat mapping is extended to three-dimensional space replacing the circumference arcs by spherical caps. An enclosed environment is scanned by employing a single ultrasonic device. The range, position, and orientation of the transducer are used to digitize the uncertainty caps and place them in a three-dimensional map. Through the spatial voting method, the generated voxels are elected in order to distinguish those which mark the true position of an obstacle and discard those that are produced by cross talk, noise, fake ranges, and angular resolution. The results show that it is possible to obtain sufficient information to build a three-dimensional map for navigation by employing inexpensive sensors and a low power data processing. En este artículo, un método de mapa de arcos ultrasónicos para mapeo plano es extendido al espacio tridimensional, remplazando los arcos de circunferencia por casquetes esféricos. Un ambiente cerrado es explorado empleando solo un dispositivo ultrasónico. La distancia, posición y orientación del transductor son utilizadas para digitalizar casquetes de incertidumbre y colocarlos en un mapa tridimensional. A través del método de votación espacial, los voxeles generados son elegidos con el propósito de distinguir aquellos que marcan la posición real de un obstáculo y descartar aquellos producidos por diafonía, ruido, lecturas falsas y la resolución angular. Los resultados muestran que es posible obtener suficiente información para construir un mapa tridimensional para navegación mediante el empleo de sensores de bajo costo y un procesamiento de datos de baja potencia.

Resumen—En este documento se presenta un metodo para medir la distancia del centroide de un objeto segmentado en una imagen de color con respecto a un punto de referencia fijo. El algoritmo se probo mediante una secuencia de imagenes de color, analizando mas de 100 posiciones verticales diferentes de una esfera alojada en el interior de una columna cilindrica transparente de acrilico con diametro y longitud constante. El algoritmo propuesto integra tecnicas de correccion por balance de blancos y de calibracion de la camara con sus parametros intrinsecos, ademas, se prueba un nuevo metodo de segmentacion en color utilizado para calcular distancias del mundo real a partir de imagenes en color RGB. Los resultados obtenidos reflejan una alta confiabilidad ya que el 100% de las mediciones realizadas tuvo un error menor a 1.64% con un nivel de precision mas alto que el instrumento utilizado de referencia, en un rango de distancia de 0 a 1340 mm.

Fuzzy systems have been explored in diverse application fields which require reaching fuzzy inferences at high computer rates. To accomplish this task, fuzzy hardware is the best choice. At inference engine, conjunction and disjunction operations play a very important role for decision making. Common operations in existing fuzzy hardware are minimum, maximum, algebraic product and probabilistic sum. In order to extend the applicability of existing fuzzy hardware, it is necessary to consider a wider range of operations. It is even desirable to have configurable circuits which take advantage of hardware resources. This work presents the hardware implementation of configurable circuits for the realization of diverse fuzzy t-norm and t-conorm operations. Resultant circuits are low hardware resource consumers which makes them efficient to be used as add-in modules for existing fuzzy hardware in FPGA or ASIC. Comparative results are presented showing the advantages of these circuits.

The ultrasound is a widely extended technique in non-destructive testing (NDT). Some its advantages are: low cost, safety and simplicity to be implemented, environment friendly and reliability. The ultrasound probes are useful to detect gaps, corrosion, breakages, changes of density and impurities in materials. However, the C-Scan used to produce a 3D image is complex and requires the use of a special probe made of a transducers matrix and a powerful computer to run the image processing algorithm. The cross-talk, spurious echoes and the position uncertainty of the reflected point make it harder to locate in the space the true points. This work describes the ultrasonic arc maps (UAM) technique and proposes to use them in NDT. Originally, the UAM was developed in robotics, where it showed good features to locate the true reflected points using a simple pulse-echo transducer. The algorithms for data processing are fast, easier to program and could be embedded in a digital system like a microcontroller or a FPGA.

Computers are becoming indispensable for manipulating most everyday consumer products, ranging from communications and domestic electronics to industrial processes monitoring and control. High performance computer design is not only subject to the technology used for its implementation, it is also a matter of efficient training. The skills that must prevail in a good computer designer come from the type of courses taken and the tools employed during them. This work shows the design of an 8-bit RISC soft-core processor dedicated to a complete understanding of computer architecture. We consider this Processor an effective hands-on training solution for the comprehension of a computer from its lowest level up to testing.

Computers are becoming indispensable for manipulating most everyday consumer products, ranging from c ommunications and domestic electronics to industrial processes monitoring and control. High performance computer design is not only subject to the technology used for its implementation, it is also a matter of efficient training. The skills that must preva il in a good computer designer c o me from the type of courses taken and the tools employed during them. This work shows the design of an 8 - bit RISC soft - core processor dedicated to a complete understanding of computer architecture. We consider this Processo r an effective hands - on training solution for the comprehension of a computer from its lowest level up to testing.

The design of controllers for nonlinear uncertain dynamical systems is one of the most important challenging tasks in control engineering. In this paper, we propose a fuzzy system for controlling a nonlinear uncertain plant. We show that alternative techniques of fuzzy control can improve or complement conventional techniques in these kind of plants.

Knowledge-based systems have the ability to realize inferences out of pre-defined rules. As the antecedents are driven into the fuzzy system, the system infers to obtain the consequents. These consequents are used to obtain crisp output data. The aggregation operator combines these consequents to obtain a unified shape from which a unique result can be obtained. The way to handle the aggregation varies according to the type of membership functions involved. This paper presents a way of realizing aggregation operation when the membership functions are represented by means of a-levels, showing that this case is suitable for discrete fuzzy system implementations.

Fuzzy systems are broad used for the decision making task given its capability of extract knowledge from an expert and translate it into rules that define described system. Implementations are made according to speed requirements of the problem, for the case of critical real time systems hardware is the best choice. One important issue on fuzzy systems is the final step, defuzzifier, when computed fuzzy data is turned into crisp data. There are many different defuzzifier methods from which most used for hardware purposes are Center Of Gravity and Mean Of Maxima. This work presents hardware implementation for Center of Slice Area Average defuzzifier, for digital soft-core implementation; its main advantages are reduction on resource consumption and reduction of calculation time without loss of accuracy.

Fuzzy theory applications have been explored and analyzed on fields as pattern recognition, control, data classification, signal processing, expert systems, among others. To accomplish this, more complex calculations and faster processing speed are required, turning fuzzy hardware implementation to be the perfect choice. Fuzzy operations as t-norms and t-conorms are used in fuzzy systems as conjunction and disjunction operations respectively. Commonly used t-norms for hardware implementation are minimum and algebraic product, first one is cheaper to implement; second consumes more resources. On this work FPGA technology is used to implement basic fuzzy t-norms as minimum, Lukasiewicz and drastic product into an 8 bit single circuit that allows operation selection. Timing, resources and comparative results are presented.

Operations used in fuzzy systems to realize conjunction and disjunction over fuzzy sets are commonly minimum and maximum because they are easy to implement and provide good results when fuzzy system is tuned, but tuning of the system is a hard work that can result on knowledge lost. A good choice to tune the system without loss of previously stated knowledge is by using parametric classes of conjunction and disjunction operations, but these operations must be suitable to be efficiently implemented on digital hardware. In this paper, the problem of obtain effective digital hardware for parametric operations of fuzzy systems is studied. The methods for generation of parametric classes of fuzzy conjunctions and disjunctions by means of generators and basic operations are considered. Some types of generators of parametric fuzzy operations simple for hardware implementation are proposed. New hardware implementation for parametric operations with operation selection is presented.

The problem of effective hardware implementation of parametric operations of fuzzy systems is studied in this paper. The methods of generation of parametric classes of fuzzy conjunctions and disjunctions by means of introduced generators and basic operations are considered. Several types of generators of parametric fuzzy operations simple for hardware implementation are proposed. Examples of hardware implementation of proposed parametric operations are presented.