The study of signals, processes, and systems has motivated the development of different representations that can be used to analyze and understand them. Classical ways of studying the behavior of signals are the time domain and frequency domain representations. For the analysis of non-stationary signals, time-frequency representations have become an essential tool to understand how the frequency content of signals changes with time. A common time-frequency technique employed in the literature is the wavelet transform. Nevertheless, selecting an adequate mother wavelet to perform the wavelet transform has become challenging due to the diverse available wavelet families. This paper reviews the applications and uses of a particular class of wavelet basis known as the Generalized Morse Wavelets. This class of wavelet family provides a systematic framework to choose and generate a wavelet for general-purpose use. This study reviews the application of Generalized Morse Wavelets in biomedical engineering, dynamical systems analysis, electrical engineering, geophysics, and communication systems. Moreover, the parameters of the Generalized Morse Wavelets used in each study are presented. The results of this study reveal that Generalized Morse Wavelets have proven helpful in studying signals, systems, and processes in areas ranging from biomedical engineering to geophysics. Nonetheless, the parameters of the Generalized Morse Wavelets are yet to be chosen through a rigorous methodology and argumentation. Therefore, there is an opportunity to generate methods for selecting the parameters of the Generalized Morse Wavelets based on the characteristics of the signals, systems, or processes under research.

Exoskeletons are an essential part of humankind’s future. The first records regarding the subject were published several decades ago, and the field has been expanding ever since. Their developments will be imperative for humans in the coming decades due to our constant pursuit of physical enhancement, and the physical constraints the human body has. The principal purpose of this article is to formalize research in the field of exoskeletons and introduce the field to more researchers in hopes of expanding research in the area. Exoskeletons can assist and/or aid in the rehabilitation of a person. Recovery exoskeletons are mostly used in medical and research areas; performance exoskeletons can be used in any area. This systematic review explains the precedents of the exoskeletons and gives a general perspective on their general present-day use, and provides a general categorization model with a brief description of each category. Finally, this paper provides a discussion of the state-of-the-art, and the current control techniques used in exoskeletons.

Road surfaces suffer from sources of deterioration, such as weather conditions, constant usage, loads, and the age of the infrastructure. These sources of decay generate anomalies that could cause harm to vehicle users and pedestrians and also develop a high cost to repair the irregularities. These drawbacks have motivated the development of systems that automatically detect and classify road anomalies. This study presents a narrative review focused on road surface anomaly detection and classification based on vibration-based techniques. Three methodologies were surveyed: threshold-based methods, feature extraction techniques, and deep learning techniques. Furthermore, datasets, signals, preprocessing steps, and feature extraction techniques are also presented. The results of this review show that road surface anomaly detection and classification performed through vibration-based methods have achieved relatively high performance. However, there are challenges related to the reproduction and heterogeneity of the results that have been reported that are influenced by the limited testing conditions, sample size, and lack of publicly available datasets. Finally, there is potential to standardize the features computed through the time or frequency domains and evaluate and compare the diverse set of settings of time-frequency methods used for feature extraction and signal representation.

Rapid technological evolution defines the first two decades of the millennium. This phenomenon has increased the digital gap, disparities, and inequalities in global and local contexts. This paper reports a systematic literature mapping of 180 articles published from 2000 to 2021 discussing the digital gap. The documents were retrieved using boolean operations in two databases, adding terms related to gender, age, ethnicity, and disabilities, focusing on population groups that are especially vulnerable to the effects of this phenomenon. The method included categorizing the retrieved documents to provide a general view of the most concerning topics in the academic and research community. This analysis concludes (a) the approaches to address this topic are diverse, as this is a multilayered, complex, and interconnected issue; (b) many studies refer to developed countries; however, fewer are those who observe or analyze the underdeveloped regions; (c) the majority of published papers in the last decade report information and communication technologies (ICT) and their role in bridging the gap, showing an opportunity area for designing these technologies considering more accessible approaches through flexible technology approaches; (d) this study’s results are a valuable source of information to identify the design requirements for accessible products and service systems. The last section provides a detailed explanation of the findings.

Current tendencies of product, project and services development focus on a higher consideration of the User Experience (UX). Therefore, traditional training and teaching methodologies need to adapt to prepare the students to develop strategies for problem solving for their professional education. Such needs have risen and interest in tendencies such as education and Industry 4.0 has grown. This paper presents and analyzes the process and results of a teaching implementation methodology based on Challenge-Based Learning (CBL). The paper describes the process followed, explaining the methodology precedents that led to the final implementation case. It also mentions previous experiments on product analysis and home automation developments that are linked to implementation of the technology. This case’s implementation, analysis and experimentation integrated the use of Emotional Domotics (ED) Tools for the UX analysis, to grant feedback and compare the students’ results with the bio-metrical and emotional computational analysis. The methodology, described through this document, allowed the students to better understand and experience some of the implications of an interconnected system with instant information feedback. This allowed them to better grasp part of the impact that the tendency towards the Internet of Things (IoT) is currently having, and the impact of the improvement proposals from the students.

Analyzing data related to the conditions of city streets and avenues could help to make better decisions about public spending on mobility. Generally, streets and avenues are fixed as soon as they have a citizen report or when a major incident occurs. However, it is uncommon for cities to have real-time reactive systems that detect the different problems they have to fix on the pavement. This work proposes a solution to detect anomalies in streets through state analysis using sensors within the vehicles that travel daily and connecting them to a fog-computing architecture on a V2I network. The system detects and classifies the main road problems or abnormal conditions in streets and avenues using Machine Learning Algorithms (MLA), comparing roughness against a flat reference. An instrumented vehicle obtained the reference through accelerometry sensors and then sent the data through a mid-range communication system. With these data, the system compared an Artificial Neural Network (supervised MLA) and a K-Nearest Neighbor (Supervised MLA) to select the best option to handle the acquired data. This system makes it desirable to visualize the streets’ quality and map the areas with the most significant anomalies.