Disability is defined as a condition of the human body that limits the execution of a task or activity. According to the World Health Organization (WHO), 15% of the world's population suffers from it, recent studies indicate that the growing prevalence are a significant problem and that, consequently, the demand for rehabilitation services is rising considerably. For this reason, different authors propose the use of exoskeletons in rehabilitation therapies as an alternative solution. Thanks to the progress of this kind of technology, it is possible to create robotic systems that help people with disabilities to recover, totally or partially, the original movement of their affected limbs. This Innovative Review Article presents an exhaustive review of the main features of upper-limb exoskeletons such as Degrees of Freedom (DoF), mechanism type, rehabilitation mode, movements allowed, applications and Technology Readiness Level (TRL). Firstly, the study provides a brief description of the biomechanics of the upper limbs of the human body. Next, the material, the rehabilitation modes and the Technology Readiness Level (TRL) of each of these devices are analyzed. As a result, it was observed that aluminum and PLA are the most used materials for exoskeletons' manufacturing. In addition, it was noticed that most of these exoskeletons perform passive rehabilitation. Besides, it was identified that the most common applications are the assistance and rehabilitation in the affected limb of patients who have suffered a stroke. Finally, using TLR scale, it was determined that these mechatronic systems are between TRL5 and TRL8.

Musculoskeletal model is a useful tool to evaluate complex biomechanical problems, simulate and evaluate injuries, estimate muscle-tendon forces, and joint torques during motion and predict the effects of orthopedic surgeries. Moreover, the musculoskeletal model is a rich source of information to develop robotics exoskeleton aiming to restore the normal gait after some injuries. This article presents a full musculoskeletal model in an open source framework to perform biomechanical analysis of the human lower limb in order to simulate both, healthy and pathological gait. Fourteen bones, 88 Hill-type muscle-tendon segments, 10 ligament segments for each knee, and 6 joints for each lower limb were modeled. The model allows us to simulate different injuries of the lower limb such as ictus, stroke, etc, by sending different signal profiles to muscle-tendon segments, emulating the functional electrical stimulation (FES). At the same time, forces and torques could be computed for muscles and joints. Hence, the proposed model can be suitable not only to perform a complete biomechanical analysis for medical purposes but also for exoskeleton controller design and actuators dimensioning. In order to validate the model, it was exported to Simulink® environment to simulate the joints range of motion, muscle moment arm, and joint torque, then these data were compared with the medical literature. All simulations results show that the data from the model are according to previously published works. Furthermore, the model was validated using real data obtained by our own gait capture system and by CODA® motion software for normal and pathological gait. Finally, the goodness-of-fit of our model was assessed using the Root Mean Square Error (RMSE) and the Normalized Mean Square Error (NMSE), the values of these indices suggest that the model estimated the kinematics and kinetics parameters of healthy and pathological gait successfully.

Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user’s kinetic parameters. Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept. Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator. Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies. Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.

This article presents an investigation about the different applications of mobile robots in the fight against the Covid-19 pandemic. It shows the different contributions of companies around the world that seek to adapt to the new needs in order to be able to mitigate the progress of the Covid-19 using mobile robots as a tool, focusing primarily in the area of health and service.

Agriculture represents the main source of food in the world, but it also represents challenges such as population growth, urbanization and aging, global economic growth, investment, trade, and food prices and competition for natural resources. The development of technology can help us cope with these challenges. The internet of things (IoT) technology represents the future of computing and communications. These can be useful to improve traditional agriculture methods around the world. By implementing these modern technologies is possible to reduce costs and maintenance and, to increase the performance of our agriculture processes and goods. Particularly, one of this relatively new technology is the LoRa communication protocol that uses long wavelengths for the communication link to obtain long ranges. This is extremely useful in agriculture where the communicating areas are extensive crop fields and greenhouses. This paper proposes and presents the development of a mobile LoRaWANgateway device that can be applied to increase greenhouses' productivity and accuracy. The presented development includes the use of a Heltec's Mini LoRa Gateway controlled by a Raspberry Pi 3 B+. It is powered by an external Li-On battery and uses a defined number of LoRa nodes with sensors. Sensors will measure humidity and temperature and send the data, which are gathered by the mobile LoRaWAN gateway. These data are processed using third-party free online services. This document illustrates and explains the development and application of data collectors for agriculture and their advantages.

For hen breeders, hatching eggs in large quantities is a production problem, when they are incubated by hens. This paper describes the development of an intelligent system for a hen egg incubator. This incubation system, based on Arduino, LabVIEW, Google Firebase and MIT App Inventor can control temperature, humidity and egg rotation automatically. In addition, the system can help farmers to monitor the intelligent incubator remotely. Successful hatched hen eggs are typically around 87.55%, 0.41 % hatched defectively, 1.84% hatched but die at birth, and 10.20 % not hatched, so an intelligent temperature and humidity control system can improve the successful hatching rate. The objective of this system is not to offer it for sale, but to make it available for researchers and farmers so that they can replicate it and carry out experiments. In order to do this, the system was kept as simple as possible.