Alejandro Rafael Garcia Ramirez

By Alejandro Rafael Garcia Ramirez, Cleiton Eduardo Saturno, Mauro José Conte, Jéferson Fernandes da Silva, Mísia Farhat, Fabiana de Melo Giacomini Garcez Garcez, Ana Carolina Savall and Elaine Carmelita Piucco

Children who suffer from cerebral palsy (CP) face specific challenges, which arise due to motor dysfunction and communication disorders. In some cases, communication is only possible through eye movements and blink, as well as, low amplitude movements of the fingers and toes. Augmentative and alternative communication (AAC) strategies can be used to promote communication in these complex cases. This chapter discusses our experience developing AAC computer’s solutions for children with motor and communication disorders. Software and hardware approaches are discussed. This chapter describes solutions developed for desktop computers and mobile devices. These solutions act as complements of therapist’s activities, helping disabled people to communicate, and promoting social inclusion.

Part of the book: Cerebral Palsy

By Marion Hersh, Marcelo Gitirana Gomes Ferreira and Alejandro Rafael Garcia Ramirez

Part of the book: Assistive Technologies in Smart Cities

By Diego Stéfano Fonseca Ferreira, Augusto Loureiro da Costa, Wagner Luiz Alves De Oliveira and Alejandro Rafael Garcia Ramirez

In this work, a system level design and conception of a System-on-a-Chip (SoC) for the execution of cognitive agents in robotics will be presented. The cognitive model of the Concurrent Autonomous Agent (CAA), which was already successfully applied in several robotics applications, is used as a reference for the development of the hardware architecture. This cognitive model comprises three levels that run concurrently, namely the reactive level (perception-action cycle that executes predefined behaviours), the instinctive level (receives goals from cognitive level and uses a knowledge based system for selecting behaviours in the reactive level) and the cognitive level (planning). For the development of such system level hardware model, the C++ library SystemC with Transaction Level Modelling (TLM) 2.0 will be used. A system model of a module that executes a knowledge based system is presented, followed by a system level description of a processor dedicated to the execution of the Graphplan planning algorithm. The buses interconnecting these modules are modelled by the TLM generic payload. Results from simulated experiments with complex knowledge bases for solving planning problems in different robotics contexts demonstrate the correctness of the proposed architecture. Finally, a discussion on performance gains takes place in the end.

Part of the book: Robotics Software Design and Engineering

By Edi Moreira M. de Araujo, Augusto Loureiro da Costa and Alejandro R.G. Ramirez

In this chapter, the main methods of communication among multi-robot systems involved in Machine-to-Machine (M2M) applications, especially with regard the communication, reliability, stability and security among these robots, presenting various concepts through papers already published. A comparative study was carried out between two communication protocols applied in M2M technologies, the Queue Telemetry Transport (MQTT) developed by IBM along with Eurotech and the Constrained Application Protocol (CoAP). A study and survey of the characteristics of each of the protocols was carried out, as well as the method of operation of each of them and how both can be used in applications involving multiple robots. It was concluded that both protocols are considered ideal for use in in applications involving multi-robot systems. However, although the two protocols have been designed for application in environments with limited communication, the MQTT exchange protocol has advantages over CoAP, as a lower ovehead between message exchanges.

Part of the book: Robotics Software Design and Engineering

By Teddy Ordoñez Nuñez, Raimundo Celeste Ghizoni Teive and Alejandro Rafael Garcia Ramirez

For a person when carrying out household chores or even when walking on the streets, there is a risk of falling. This risk increases throughout the years due to the natural aging process. In this work, a bibliographic review was performed to find related papers who discussed different techniques for fall classification. The aim of this study was to develop two ML models: an SVM and a k-NN model, to classify the fall. An accelerometer, gyroscope, and magnetometer located on the waists of 15 volunteers are the application sensors. The extracted features were the mean, standard deviation, and range for each sensor. The best accuracy obtained was 93.89%, a sensitivity of 85.10%, and a specificity of 96.99%. All results were obtained by simulations, by using the test set separated in the first stage of the implementation. So, a shortcoming is the fact that the ML models were not tested with a hardware implementation. In future works, the models can be embedded into a microcontroller and classify data in real time.

Part of the book: Cognitive Robotics and Adaptive Behaviors

By Alejandro Rafael Garcia Ramirez

Part of the book: Trends in Assistive Technologies