Carlos Andrés Pérez-Ramírez

Autonomous University of Queretaro · Facultad de Ingeniería

Epilepsy, a neurological disorder, affects millions of persons worldwide. It is distinguished by causing recurrent seizures in patients, which can conduct to severe health problems. Consequently, it is essential to offer a method capable of timely predicting a seizure before its appearance, so patients can avoid possible injuries by taking preventi...

Breast cancer is one the main death causes for women worldwide, as 16% of the diagnosed malignant lesions worldwide are its consequence. In this sense, it is of paramount importance to diagnose these lesions in the earliest stage possible, in order to have the highest chances of survival. While there are several works that present selected topics i...

Civil infrastructures are one of the fundamentals pillars for the optimal functioning of modern society. Despite the considerations used in structural design, time and scarce maintenance can lead to the deterioration of structures; hence, the loss of their continuous, safe and economic operation is not achieved. Structural monitoring systems make i...

The economic and personal consequences that a car accident generates for society have been increasing in recent years. One of the causes that can generate a car accident is the stress level the driver has; consequently, the detection of stress events is a highly desirable task. In this article, the efficacy that statistical time features (STFs), su...

Sudden cardiac death (SCD) is deemed as one of the main causes of death in humans. Therefore, the prediction of an SCD event will help people to receive timely treatment, allowing saving their life. In this sense, this article introduces a new methodology based on the adroit fusion of fractal dimension (FD) algorithms and a fuzzy logic system for p...

Epilepsy is a brain disorder that affects about 50 million persons around the world and is characterized by generating recurrent seizures, which can put patients in permanent because of falls, drowning, burns, and prolonged seizures that they can suffer. Hence, it is of vital importance to propose a methodology with the capability of predicting a s...

During the last years, civil infrastructure has experienced an increasing development to satisfy the society’s demands such as communication, transportation, work and living spaces, among others. In this sense, the development and application of methods to guarantee the structure optimal operation, known as Structural Health Monitoring schemes, are...

A new multiple signal classification (MUSIC)-based methodology is presented for detecting and locating multiple damage types in a truss-type structure subjected to dynamic excitations. The methodology is based mainly on two steps: in step 1, the MUSIC method is employed to obtain the pseudo-spectra of vibration signatures, healthy and damaged, to b...

In this paper, an automatic method to process and quantify the metabolites of a magnetic resonance spectroscopy signal is presented. Signals obtained from a region of the left thalamus were analyzed. The obtained results were compared with the ones obtained using a Phillips’ commercial magnetic resonance software. Three features of the signal corre...

Heart diseases are among the most common death causes in the population. Particularly, sudden cardiac death (SCD) is the cause of 10% of the deaths around the world. For this reason, it is necessary to develop new methodologies that can predict this event in the earliest possible stage. This work presents a novel methodology to predict when a perso...

An accurate response prediction model is of great importance in various applications such as damage detection, structural health monitoring, and vibration control. Development of such a methodology for large civil structures is challenging because of their size and complicated behavior and noise-contaminated, nonlinear, and nonstationary nature of...

Sudden cardiac death (SCD) is considered one of the main causes of death among people. Hence, an early prediction of an SCD event will allow saving people lives because receive timely medical procedures. In this paper, a methodology to predict SCD of an automatic manner using ECG signals, fractal dimension (FD), neural networks is presented. Three...

Truss-type designs are widely used in civil structures. Despite the fact that they are robust and reliable structures, different kinds of damage can appear. In order to avoid human and economic losses, the development and application of damage-detection methodologies are paramount. In this work, a methodology based on the empirical mode decompositi...

Sudden cardiac death (SCD) is one of the main causes of death among people. A new methodology is presented for predicting the SCD based on ECG signals employing the wavelet packet transform (WPT), a signal processing technique, homogeneity index (HI), a nonlinear measurement for time series signals, and the Enhanced Probabilistic Neural Network cla...

Squirrel-cage induction motors (SCIMs) are key machines in many industrial applications. In this regard, the monitoring of their operating condition aiming at avoiding damage and reducing economical losses has become a demanding task for industry. In the literature, several techniques and methodologies to detect faults that affect the integrity and...

In the last years, the occurrence of natural hazards around the world has evinced the necessity of having structural health monitoring schemes that can allow the continuous assessment of the structural integrity of the civil structures or infrastructures, in order to avoid potential economic or human loses; further, it also allows the application o...

Nowadays, the accurate identification of natural frequencies and damping ratios play an important role in smart civil engineering, since they can be used for seismic design, vibration control, and condition assessment, among others. To achieve it in practical way, it is required to instrument the structure and apply techniques which are able to dea...

Induction motors, vital elements into the industry, are more likely to be influenced by different faults during their lifetime service. Even when they can keep working without affecting the line processes, in most cases, an increase in the production costs usually occurs. Bearing fault detection is an important topic due to the fact that this failu...

Monitoring of voltage variations is a demanding issue for academic and industrial fields due mainly to their negative impact on equipment. In this work, a methodology based on adaptive filter using the least mean squares algorithm for tracking of voltage variations and a fuzzy logic system for automatic classification are proposed. The proposal con...

A major trust of modal parameters identification (MPI) research in recent years has been based on using artificial and natural vibrations sources because vibration measurements can reflect the true dynamic behavior of a structure while analytical prediction methods, such as finite element models, are less accurate due to the numerous structural ide...

The accurate estimation of modal parameters such as natural frequencies and damping ratios is an important concern since their values allow the condition assessment of the structure, vibration control, as well as to build or update a proper model of the structure. Unfortunately, an accurate estimation of these values represents a challenge since th...

Due to the relevance and severity of damages caused in induction motors by broken rotor bars (BRBs), the development and application of new detection methods that offer an efficient and reliable diagnosis in terms of processing and performance are still demanding tasks. This paper presents a methodology based on the Synchrosqueezing transform for d...

The development and application of techniques and methodologies for the analysis of power quality (PQ) signals that offer a more efficient and reliable analysis in terms of processing and performance are still issues for industrial and academic fields, mainly considering the quick growing of the PQ data in modern power systems. In this regard, an i...

Many applications related to modeling, control and condition assessment of smart structures require an accurate identification of natural frequencies and damping ratios. This identification is generally carried out through artificial and natural vibration sources. The latter is often preferred in many situations; yet their analysis represents a cha...

Accurate estimation of the fundamental frequency of civil structures is crucial for many applications; in particular, this estimation becomes more important when it helps to avoid or minimize human, economic, and structural damages as the case of the design and analysis of high-rise buildings subjected to earthquakes. Although many techniques have...

Over the past few years, power quality (PQ) monitoring has become an important topic because of the negative impact of different machines to the electrical network and to the susceptibility of critical equipment. There are different disturbances that affect the PQ; therefore, in order to apply a proper solution, these have to be correctly detected...

Induction motors, important elements into the industry, are susceptible to faults during its lifetime service; yet, they can keep working without affecting the process, but increasing the production costs as they consume more electrical current. Broken rotor bars (BRB) detection is an important topic due to the fact that this failure is silent and...

The implementation of signal filters in a real-time form requires a tradeoff between computation resources and the system performance. Therefore, taking advantage of low lag response and the reduced consumption of resources, in this article, the Recursive Least Square (RLS) algorithm is used to filter a signal acquired from a fiber-optics-based sen...

Civil structures are known for having a non-linear and time-variant behavior, these features make a challenging task the use of linear methods for modeling the dynamical behavior since they only model time-invariant systems. To overcome this limitation, several approaches based on non-parametric methods have been proposed, however, the selection of...

This paper proposes the implementation of an algorithm for the parallel self-parking of a tricycle mobile robot. Knowing the dimensions of the mobile robot, our strategy consists in validating the minimal distance required by the robot to perform the parking task. The robotic platform is equipped with an ultrasonic sensor centered in the front part...