Martinez-Villaseñor, Lourdes
Thumbnail Image
Preferred name
Martinez-Villaseñor, Lourdes
Official Name
Martínez Villaseñor, María de Lourdes
Alternative Name
lmartine
Main Affiliation
ORCID
Scopus Author ID
55521085100
Researcher ID
N-7607-2018

Research Output
Now showing 1 - 6 of 6
No Thumbnail Available
Publication

Editorial: Artificial intelligence in brain-computer interfaces and neuroimaging for neuromodulation and neurofeedback

2022 , Ponce, Hiram , Yinong, Chen , Martinez-Villaseñor, Lourdes

Neuromodulation and neurofeedback are two alternative non-pharmacological ways of treating neurological related diseases and disorders (Grazzi et al., 2021; Hamed et al., 2022). Neuromodulation refers to as the modulation of brain function via the application of weak direct current (Lewis et al., 2016). Neurofeedback is a psychophysiological procedure that provides models of neural activity to subjects aiming to control them online (Marzbani et al., 2016). Both alternatives have been successfully applied in a variety of neurological conditions including Parkinson's disease, chronic pain, epilepsy, depression, essential tremor, among many others (Tsatali et al., 2019; Baptista et al., 2020; Hamed et al., 2022). Typical challenges in these types of treatment are related to the way of collecting data, the improvement in the efficiency of the methods, the interpretability of feedback signals, to name a few (Johnson et al., 2013; Lewis et al., 2016; Marzbani et al., 2016; Papo, 2019). © 2023 Frontiers Media S.A. All rights reserved

View
No Thumbnail Available
Publication

Challenges in Data Acquisition Systems: Lessons Learned from Fall Detection to Nanosensors

2018 , Peñafort Asturiano, Carlos J. , Santiago, Nestor , Nuñez-Martínez, José , Ponce, Hiram , Martinez-Villaseñor, Lourdes

Falls are a major public health problem in elderly people often causing fatal injuries. It is important to assure that injured people receive assistance as quick as possible. Fall detection systems have gain more relevance nowadays. As more databases and fall detection systems are developed, there is more need to identify the challenges encountered in building and creating them. This paper addresses pre-processing, inconsistency and synchronization challenges that occur when creating a multimodal database for fall detection. We present different algorithms used to tackle these issues. We describe the issues and the corresponding solutions in order to document the lessons learned that could help others in data acquisition for multimodal databases. Applying the solutions to the issues found so far, we acquired an organized multimodal database for fall detection with 17 subjects. Furthermore, these lessons learned can be applied for data nanosensors acquisition and storage. © 2018 IEEE.

View
No Thumbnail Available
Publication

Modeling and simulation for designing a line walking chameleon-like legged robot

2022 , Ponce, Hiram , Acevedo, Mario , Martinez-Villaseñor, Lourdes , Díaz Ramos, Gabriel , Mayorga Acosta, Carlos

Legged robots have been developed to move on uneven terrains. They can move smoother and step over obstacles easily, and they are more versatile in various environmental scenarios. These features make them desirable for maintenance and/or search-and-rescue tasks where mobility is restricted on these complex terrains. A problem arises when legged robots are required to walk on the top of narrow support, e.g. thin beams or tubes. In this work, we present the design of a line walking legged robot for narrowed support. To achieve this goal, we get inspiration from the chameleon locomotion. From these observations, we simulate the robot, design an intelligent control strategy for self-balancing and walking, and we implement a robot prototype. The experimental results show that the balance controller provides a tilt angle of 2.24±2.21∘, while the robot walks in a straight line with a maximum offset of 3.0 cm and with a walking velocity of 0.2 cm/s. Our results demonstrate that the robot can move on narrowed support lines. We anticipate that the design of legged robots inspired by the chameleon locomotion might open wider possibilities for rescue and maintenance missions. © 2022 Elsevier B.V.

View
No Thumbnail Available
Publication

Feature Selection Methods Evaluation for CTR Estimation

2016 , Miralles-Pechuán, Luis , Ponce, Hiram , Martinez-Villaseñor, Lourdes

The most widespread payment model in online advertising is Cost-per-click (CPC). In this model the advertisers pay each time that a user generates a click. In order to enhance the income of CPC Advertising Networks, it is necessary to give priority to the most profitable adverts. The most important factor in the profitability of an advert is Click-through-rate (CTR), which is the probability that a user generates a click in a given advert. In this paper we find which feature selection method between PCA, RFE, Gain ratio and NSGA-II is better suited, or if otherwise, the machine learning classification methods work best without any feature selection method. ©2016 IEE

View
No Thumbnail Available
Publication

Comparative Analysis of Artificial Hydrocarbon Networks versus Convolutional Neural Networks in Human Activity Recognition

2020 , Ponce, Hiram , Martinez-Villaseñor, Lourdes

Human activity recognition (HAR) has gained interest in the research communities in order to know the behavior and context of users for medical, sports performance evaluation, ambient assisted living and security applications. Recent works suggest that convolutional neural networks (CNN) are very competitive machine learning techniques for HAR. Nevertheless, CNN require many computational resources, high number of parameter tuning, and many data samples for training. In this paper, we present a comparative analysis of a novel technique, artificial hydrocarbon networks (AHN), with CNN on human activity recognition classification task. We choose to compare AHN with CNN given that it is a very well-suited machine learning technique for HAR. We show that AHN architecture is simpler to set up than CNN, it needs less hyper-parameter configuration and has a slightly better accuracy performance. © 2020 IEEE.

View
No Thumbnail Available
Publication

Modeling and Control Balance Design for a New Bio-inspired Four-Legged Robot

2019 , Ponce, Hiram , Acevedo, Mario , Morales, Elizabeth , Martinez-Villaseñor, Lourdes , Mayorga-Acosta, Carlos , Díaz Ramos, Gabriel

Bio-inspired robots have chosen to propose novel developments aiming to inhabit and interact complex and dynamic environments. Bio-inspired four-legged robots, typically inspired on animal locomotion, provide advantages on mobility, obstacle avoidance, energy efficiency and others. Balancing is a major challenge when legged robots require to move over uncertain and sharp terrains. It becomes of particular importance to solve other locomotion tasks such as walking, running or jumping. In this paper, we present a preliminary study on the modeling and control balance design of a bio-inspired four-legged robot for standing on its aligned legs in a straight line. The proposed robot is loosely inspired on the bio-mechanics of the chameleon. Thus, a mathematical modeling, simulation, intelligent control strategy, prototype implementation and preliminary results of control balance in our robot are presented and discussed. © Springer Nature Switzerland AG 2019.

View