• assistive technologies
• artificial intelligence
• machine learning
• speech recognition
• dysarthria

The thesis investigates the synergy among recent information and communication technologies toward the development of personalized assistive technology solutions for people with disabilities. Three separate case studies have been analysed within the framework of Artificial Intelligence (AI), machine learning and Internet of Things (IoT). The presented applications exploit open source pieces of hardware and software, low cost components with the aim of addressing open challenges for the current assistive technology, including: i) Isolated word recognition system for people with speech disorders, particularly in presence of dysarthria, with the aim of supporting the natural speech interaction with computers and appliances in a personalized smart home context; ii) Computer vision system for users who are blind or visually impaired, aimed at supporting the awareness of the user's surrounding environment, considering smart city scenario; iii) Human computer interfaces based on smart sensors and IoT technologies, especially designed for people with severe motor disabilities.