IEEE Latin America Transactions

Upper-Limb robotic exoskeletons for stroke rehabilitation: A comprehensive review, comparative classification, and design guidelines

Luis Vázquez-Sánchez — 2026-05-26

This paper presents a structured review of upper-limb robotic exoskeletons for post-stroke rehabilitation, focusing on mechanical design principles, biomechanical compatibility, control strategies, actuation systems, and mechanical human–machine interfaces. State of the art developments were analyzed through major scientific databases and classified according to degrees of freedom, portability, sensing modalities, and rehabilitation objectives. The review highlights current design trends, limitations in commercial systems, and challenges related to kinematic alignment, workspace validation, and ergonomic integration.Based on the identified research gaps, particularly in cost-effectiveness, portability, and anthropometric adaptability—a 5-degree-of-freedom upper-limb exoskeleton, is presented as a case oriented design proposal. The architecture incorporates forward and inverse kinematic modeling to ensure compatibility with physiological ranges of motion of the shoulder, elbow, and wrist. Lightweight materials such as Polyoxymethylene and aluminum are considered to reduce distal inertia and improve wearability. This work contributes a comparative classification framework and biomechanically grounded design guidelines aimed at facilitating accessible and scalable neurorehabilitation technologies.

Crosstalk Reduction in High-Speed Microstrip Interconnects Using a Greek Key Guard Trace

Gobinath Arumugam — 2026-05-21

This work presents a method for suppressing near-end crosstalk (NEXT) and far-end crosstalk (FEXT) in high-speed microstrip interconnects using a Greek key patterned defective microstrip guard trace. The structure increases effective capacitance and modifies the inductive path between coupled lines, improving electromagnetic isolation without increasing line spacing. A full parametric study is carried out in HFSS to evaluate the effect of defect width and unit-cell spacing on crosstalk behavior. The results show that a defect width of 0.01 mm with a spacing of 1.0 mm provides the strongest suppression, achieving NEXT of −57.53 dB and FEXT of −51.70 dB at 10 GHz. When compared with conventional guard traces, the proposed design delivers more than 60% improvement in NEXT and over 80% improvement in FEXT. Analysis shows saturation after 0.025 mm defect width, beyond which no significant improvement can be achieved. The proposed structure provides an optimal and compact method to reduce coupling effects in high-speed PCB designs with high density.

Single-Layer Low-Profile Wideband Antenna Based on Non-Uniform Radiating Elements

Thai Nguyen-Dinh — 2026-05-21

This paper presents a single-layer low-profile antenna with wideband operation based on non-uniform radiating elements. The antenna is first designed with four square patches with center excitation. Then, multiple patches with different dimensions are positioned on both sides to produce two adjacent resonances in the high frequency. Accordingly, wideband operation with single layer configuration can be obtained. The final antenna has overall dimensions of 1.04 λ × 0.61 λ × 0.02 λ at 5.2 GHz. The measured on the fabricated antenna demonstrate wideband operation of 15.4%, ranging from 4.8 to 5.6 GHz. Across this band, the realized gain remains above 5.0 dBi with a peak of 7.9 dBi. Furthermore, the antenna maintains stable radiation patterns, and the front-to-back ratio (FBR) consistently exceeds 16 dB. Compared with existing single-layer wideband designs, the proposed antenna offers the lowest profile while providing a well-balanced combination of bandwidth, gain, and FBR.

Material Circularity Index (MCI) assessment of distributed generation technologies for Mexico’s energy transition

Diana L. Ovalle-Flores — 2026-05-25

This study evaluates the circularity performance of ten distributed generation (DG) technologies in Mexico using a streamlined Material Circularity Index (MCI) framework. The analysis integrates Life Cycle Inventory (LCI) data to quantify material flows during construction and End-of-Life stages, with a specific focus on the recovery potential (α) of critical materials, including steel, copper, and silicon. The results reveal significant disparities across technologies. Biogas and hydroelectric systems exhibit the highest circularity scores (0.36), reflecting favorable material recovery profiles, whereas wind (0.15) and solar photovoltaic systems (0.30) are constrained by the presence of composite materials and electronic waste, which limit recyclability. These findings underscore the dominant role of End-of-Life infrastructure in shaping circularity outcomes within emerging energy systems. The study demonstrates that material recovery potential is a critical determinant of circular performance in the Mexican DG context and identifies key technological and systemic barriers to circularity. By providing a comparative, data-driven assessment, this work offers policy-relevant insights to support the transition toward a more resource-efficient and circular distributed energy sector.

Generation Expansion Planning Toward the Decarbonization of the Baja California Sur Electrical System

Antonino Lopez Rios — 2026-05-21

This article analyzes the energy transition and decarbonization of the Baja California Sur Interconnected System (BCSIS), an isolated electrical grid with a high dependence on fossil fuels. It proposes a generation expansion plan (GEP) that incorporates renewable technologies such as wind power, photovoltaic (PV), concentrated solar power (CSP), and battery energy storage systems (BESS), with the aim of improving reliability, reducing greenhouse gas (GHG) emissions, and lowering operating costs. To achieve this, three expansion scenarios are evaluated for the period 2025–2039, using simulations carried out with PLEXOS® software.

Multi-Objective Financial Optimization of Shared-Savings ESCOs for Renewable Energy Self-Consumption

Diego Arias Cazco — 2026-05-21

This paper presents a multi-objective optimization model for structuring financially viable contracts in self-supply energy projects based on Energy Service Companies (ESCO). The proposed methodology uses Pareto frontier analysis to evaluate the trade-off between user benefits (through savings allocation, β) and ESCO revenues (through the cost-sharing factor, α), incorporating a levelized cost approach to ensure financial balance under a project finance framework.

Key variables, including the optimal ESCO contract duration and the sensitivity to electricity tariffs, discount rates, and system capacity factor, are analyzed using Pareto frontiers and contour maps to identify regions of optimal financial performance.

The methodology is validated through a case study, demonstrating its applicability for structuring optimal Energy Savings Performance Contracts (ESPC). Additionally, debt coverage indicators (DSCR, LLCR, and PLCR) are incorporated to assess financial feasibility.

The proposed approach provides a robust decision-making tool for users, investors, and regulators seeking sustainable distributed generation business models supported by project financing structures.

The Pragmatic Openness of Open RAN: Navigating the Path from Vendor Lock-in to Interoperability Islands

Nima Afraz — 2026-05-25

Open Radio Access Network (Open RAN) promises to dismantle traditional vendor lock-in through disaggregation and standardization. This article analyzes its current trajectory, finding that the ecosystem is not evolving toward universal interoperability but is instead consolidating into “islands of interoperability” or pre-validated multi-vendor clusters that risk becoming new forms of lock-in. Through a review of global deployments and industry collaboration patterns, we examine the technical and market forces that may contribute to this fragmentation. We argue that while these islands represent a pragmatic compromise that increases operator choice, they also pose a significant long-term risk to the open ecosystem by stifling innovation and competition. Ultimately, we conclude that avoiding permanent fragmentation is not a technical challenge alone but a strategic imperative. It requires a concerted shift from writing standards to enforcing rigorous, transparent certification and fostering a market that rewards true interoperability over closed partnerships. The future of Open RAN depends on building bridges between these islands to preserve its foundational promise.

FrIDA-AR: An Integrated Framework for Underground Water Infrastructure Visualization using GIS and Augmented Reality

Albio Souza Leite Júnior — 2026-05-25

This paper presents FrIDA-AR, an integrated framework designed to enhance the management of Water Distribution Networks (WDNs) through Geospatial Information Systems (GIS) and Augmented Reality (AR). Unlike traditional methods that rely on 2D maps and physical excavations, FrIDA-AR provides a 3D overlay of underground infrastructure in realtime. The methodology employs a quadrant-based segmentation logic to ensure mobile scalability and low latency. Results from a case study in Pelotas-RS, Brazil, demonstrate that the framework achieves a stable AR registration with high visual fidelity, offering a scalable solution for utility maintenance in low-resource settings.

MoTI: An MQTT-Oriented Architecture Enabling Interoperability of IoT Devices in Industry 4.0

Camila Cabral de Barros — 2026-05-21

The increasing adoption of Industrial Internet of Things (IIoT) systems intensifies the need for secure and interoperable communication across heterogeneous industrial environments. This paper proposes MoTI (MQTT-oriented Things Interoperability), a modular architecture that integrates MQTT-based communication, mutual TLS authentication, structured metadata logging, and decentralized storage through IPFS. The solution was implemented and experimentally validated using 1500 messages distributed across three Quality of Service (QoS) levels under controlled load conditions. Considering the complete end-to-end processing pipeline, including MQTT transmission, metadata registration, IPFS persistence, and acknowledgment, statistical analysis revealed significant variability differences across QoS levels. QoS levels 1 and 2 exhibited stable and predictable RTT behavior, whereas QoS level 0 showed substantially higher dispersion and extreme outliers. The results demonstrate that stronger delivery guarantees can be adopted without significant impact on average response time, reinforcing the suitability of QoS 2 for delay-sensitive industrial applications. MoTI provides a practical, experimentally validated approach for secure, traceable, and scalable cross-organizational data exchange in distributed industrial environments.

Intelligent Bearing Fault Detection: Deep Learning Model Assessment and Embedded System Deployment

Andres Felipe Cotrino Herrera — 2026-05-21

Bearings are vital parts used in many industrial settings; however, their failures can greatly reduce system efficiency and operational reliability. In this context, AI-driven predictive maintenance is an effective approach for identifying and classifying bearing faults via vibration analysis. This study creates a custom dataset by recording vibration signals from a DC motor operating under various fault conditions (bearing without lubrication, bearing with one missing ball, and bearing with two missing balls), as well as under normal operation (bearing without failure), using an accelerometer and a controlled test bench. Furthermore, four neural network models — Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Transformer — were trained and evaluated based on accuracy, recall, and F1-score. The CNN model performed best, achieving a 99.95% accuracy on the validation dataset. This model was then implemented on an ESP32, reaching 94.2% accuracy during real-time testing. These results demonstrate that AI-based fault detection systems can be effectively deployed on resource-limited platforms, providing a promising solution for predictive maintenance and educational efforts to boost STEM skills.

Table of Contents July 2026

Daniel Ulises Campos Delgado — 2026-05-21