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Sandoval-Ibarra Y.,National Polytechnic Institute of Mexico | Diaz-Ramirez V.H.,National Polytechnic Institute of Mexico | Kober V.,CICESE | Kober V.,Chelyabinsk State University | Diaz A.,Mexicali Institute of Technology
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

A locally-adaptive algorithm for speech enhancement based on local spectral regularization is presented. The algorithm is able to retrieve a clean speech signal from a noisy signal using locally-adaptive signal processing. The proposed algorithm is able to increase the quality of a noisy signal in terms of objective metrics. Computer simulation results obtained with the proposed algorithm are presented and discussed in processing speech signals corrupted with additive noise. © 2016 SPIE.


Fernandez D.,Baolab Microsystems | Martinez-Alvarado L.,Mexicali Institute of Technology | Madrenas J.,Polytechnic University of Catalonia
IEEE Journal of Solid-State Circuits | Year: 2012

A field-programmable analog array (FPAA) using a standard-CMOS wide-dynamic-range translinear element (TE) is introduced. The FPAA configurable analog blocks (CABs) are based on a reconfigurable translinear cell (RTC), capable of implementing the basic circuit elements required by translinear and log-domain circuit design. The interfacing is provided by an I/O programmable cell, which allows for easier connectivity between the signal-processing core and the external circuitry. As a proof-of-concept, a 5 × 5 RTC FPAA testchip was implemented in 0.35-μm CMOS technology. A set of various circuit primitives, such as one- and four-quadrant multipliers, an Euclidean distance operator and a fourth-order log-domain filter, were mapped on the chip in order to demonstrate the versatility of the approach. FPAA bandwidth reaches 20 MHz with a power consumption of 30 μW/TE and precision errors below 3%. © 2011 IEEE.


Diaz-Ramirez A.,Mexicali Institute of Technology | Dominguez E.,Mexicali Institute of Technology | Martinez-Alvarado L.,Autonomous University of Baja California
International Symposium on Technology and Society, Proceedings | Year: 2016

Accidental falls are one of the main causes of deaths and severe injuries of people over 65 years old. For this reason, the development of fall detection systems for the elderly has been an important research topic. In this paper, a non-invasive fall detection system for older people, based on the use of a wireless sensor network (WSN), is proposed. It uses the acoustic signal sensed by a node of the WSN, as well as signal processing and pattern recognition techniques to detect a fall. The model uses a signal-processing algorithm based on the use of cross-correlation to measure the similarity between the sampled signal and a reference template signal, which represents a fall event. If these two signals are similar, then the Mel-frequency cepstral coefficients (MFCC) of the fall sound are extracted. Afterwards, the dynamic time warping (DTW) method is used for pattern recognition. The evaluation of the proposed system showed a very good detection rate. © 2015 IEEE.


Diaz-Ramirez A.,Mexicali Institute of Technology | Mejia-Alvarez P.,CINVESTAV | Leyva-Del-Foyo L.E.,Metropolitan Autonomous University
Journal of Applied Research and Technology | Year: 2013

Schedulability conditions are used in real-time systems to verify the fulfillment of the temporal constraints of task sets. In this paper, a performance analysis is conducted for the best-known real-time schedulability conditions that can be used in online admission control on uni-processor systems executing under the Rate-Monotonic scheduling policy. Since Liu and Layland introduced the Rate-Monotonic scheduling algorithm, many research studies have been conducted on the schedulability analysis of real-time periodic task sets. However, in most cases, the performance of the proposed schedulability conditions were compared only against the Liu and Layland test and not against the remaining schedulability tests. The goal of this paper is to provide guidelines for system designers in order to decide which schedulability condition provides better performance under different task characteristics. Extensive simulation experiments were conducted to evaluate the inexact schedulability conditions and compare their performance and computational complexity.


Calafate C.T.,Polytechnic University of Valencia | Lino C.,Leon Institute of Technology | Diaz-Ramirez A.,Mexicali Institute of Technology | Cano J.-C.,Polytechnic University of Valencia | Manzoni P.,Polytechnic University of Valencia
Sensors (Switzerland) | Year: 2013

The use of wireless sensor networks (WSN) in tracking applications is growing at a fast pace. In these applications, the sensor nodes discover, monitor and track an event or target object. A significant number of proposals relating the use of WSNs for target tracking have been published to date. However, they either focus on the tracking algorithm or on the communication protocol, and none of them address the problem integrally. In this paper, a comprehensive proposal for target detection and tracking is discussed. We introduce a tracking algorithm to detect and estimate a target location. Moreover, we introduce a low-overhead routing protocol to be used along with our tracking algorithm. The proposed algorithm has low computational complexity and has been designed considering the use of a mobile sink while generating minimal delay and packet loss. We also discuss the results of the evaluation of the proposed algorithms. © 2013 by the authors; licensee MDPI, Basel, Switzerland.


Mayorga P,Mexicali Institute of Technology
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

In this paper a novel Lung Sound Automatic Verification (LSAV) system and front-end Quantile based acoustic models to classify Lung Sounds (LS) are proposed. The utilization of Quantiles allowed an easier and objective assessment with smaller computational demand. Moreover, less-complex Gaussian Mixture Models (GMM) were computed than those previously reported. The LSAV system allowed us to reach practically negligible error in healthy (normal) LS verification. LASV system efficiency and the optimal GMM's were evaluated by using Equal Error Rate (EER) and Bayesian Information Criterion (BIC) techniques respectively. These approaches could provide a tool for broader medical evaluation which does not rely, as it is often the case, on a qualitative and subjective description of LS.


Mayorga P.,Mexicali Institute of Technology
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2010

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.


Mayorga P.,Mexicali Institute of Technology | Druzgalski C.,California State University, Long Beach | Gonzalez O.H.,Mexicali Institute of Technology | Lopez H.S.,Mexicali Institute of Technology
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2012

In this paper a novel Lung Sound Automatic Verification (LSAV) system and front-end Quantile based acoustic models to classify Lung Sounds (LS) are proposed. The utilization of Quantiles allowed an easier and objective assessment with smaller computational demand. Moreover, less-complex Gaussian Mixture Models (GMM) were computed than those previously reported. The LSAV system allowed us to reach practically negligible error in healthy (normal) LS verification. LASV system efficiency and the optimal GMM's were evaluated by using Equal Error Rate (EER) and Bayesian Information Criterion (BIC) techniques respectively. These approaches could provide a tool for broader medical evaluation which does not rely, as it is often the case, on a qualitative and subjective description of LS. © 2012 IEEE.


Diaz-Ramirez A.,Mexicali Institute of Technology | Murrieta F.N.,Mexicali Institute of Technology | Atempa J.A.,Mexicali Institute of Technology | Bonino F.A.,Mexicali Institute of Technology
Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCoSS 2013 | Year: 2013

As a consequence of the aging of the world population, society and governments must face major challenges regarding people's health. In recent years, researches have been interested in investigating how the technology can be used to improve the healthcare and assistance of patients with dementia, as the Alzheimer's disease. In this paper, we propose a non-intrusive pervasive model to assist patients with dementia, based on the use of a wireless sensor network. Using high availability and low cost binary sensors, the proposed model is able to determine in real-time the location of a patient, and to emit alerts if one leaves a safe place without supervision. © 2013 IEEE.


Mayorga P.,Mexicali Institute of Technology | Druzgalski C.,California State University, Long Beach | Gonzalez O.H.,Mexicali Institute of Technology
2012 Pan American Health Care Exchanges, PAHCE 2012 - Conference, Workshops, and Exhibits. Cooperation / Linkages: An Independent Forum for Patient Aare and Technology Support | Year: 2012

Anthropogenic activities associated to population growth impact overall health and contribute to elevated rates of cardiovascular and respiratory diseases. In this paper we propose the Lung Sound Automatic Verification (LSAV), and other modalities to represent acoustic lung signals obtained by auscultation using a digital stethoscope. The utilization of quantiles allowed a) an easier and objective assessment with smaller computational demand, b) building of less-complex Gaussian Mixed Models (GMM) than those reported previously, and c) to reach practically negligible error in healthy LS verification. These approaches relate the lung sound energy to its characteristic frequency components, which in addition to a reliable verification technique simplified the normal lung sound recognition. Once the LS are evaluated, it would be possible to simplify classification if an individual auscultatory evaluation falls into the category of normal or abnormal indicators thus providing a tool for broader medical evaluation which does not rely, as it is often the case, on a qualitative and subjective description of these sounds. © 2012 IEEE.

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