Human Machine Interaction

Description

In recent decades, people’s daily lives have been transformed by the fast ICT developing. In particular, the spreading of smart products and the possibilities to connect IoT devices together have changed the living environments. Moreover, the population ageing, which is a process that has been going on at the global level for a while, will increasingly affect the number of people with mental and physical impairments as well as various age-related chronic diseases. Advances in Human-Machine Interaction (HMI) have the potential to support the daily life of people, with or without impairment, by proposing interactive systems able to manage its knowledge about the user (i.e., who is using the system) and the environment (i.e., the context in which the user-system interaction takes place) in order to adapt information content, functions, and interaction modalities according to different users and context of use. To this end, a method that leads to the single instance construction in the interfaces design is inappropriate as it cannot accommodate the differences resulting from the needs of individual users. Therefore, the requirement of a systematic process (flow) that includes alternative decisions making procedures according to these differences is necessary. To achieve this objective, the research aims to develop new methods to support the design of new adaptive systems or to make an existing system adaptive. The main innovative aspects are:

  • The effective combination of adaptable and adaptive elements. Adaptable User Interfaces can be defined as systems in which the activation of user-computer interaction is performed by the final user through the selection of a specific user profile from a predefined list. Instead, Adaptive user interfaces are systems that autonomously change its structure, contents and elements according to the users’ needs and context of use;
  • The adoption of a Design for All approach, which allows improving the user experience of people with and without disabilities;
  • The adoption of an users-centered approach that means fitting the system to the users’ needs and involving them in the design process.

Laboratories

Usability and Interaction Design Lab 

Publications
  1. Gullà F., Menghi, R., Papetti, A., Carulli, M., Bordegoni, M., Gaggioli, A., Germani, M., 2018. Prototyping adaptive systems in smart environments using virtual reality. International Journal for Interactive Design and Manufacturing. https://doi.org/10.1007/s12008-018-00522-x
  2. Gullà, F., Papetti, A., Menghi, R., Germani, M., 2018. A Method to Make an Existing System Adaptive. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-91238-7_8
  3. Gullà, F., Ceccacci, S., Menghi, R., Germani, M., 2018. How touch glove and expertise influence the basic touch gestures performances for people with Systemic Sclerosis. ACM International Conference Proceeding Series, pp. 281-286. doi: 10.1145/3197768.3197773
  4. Menghi, R., Gullà, F., Germani, M., 2018. Assessment of a smart kitchen to help people with Alzheimer’s disease. Lecture Notes in Computer Science, 10898 LNCS, pp. 304-309. doi: 10.1007/978-3-319-94523-1_30
  5. Gullà, F., Ceccacci, S., Menghi, R., Cavalieri, L., Germani, M., 2017. Adaptive interface for smart home: A new design approach. Lecture Notes in Electrical Engineering, 426, pp. 107-115. doi: 10.1007/978-3-319-54283-6_8
  6. Menghi, R., Ceccacci, S., Gullà, F., Cavalieri, L., Germani, M., Bevilacqua, R., 2017. How older people who have never used touchscreen technology interact with a tablet. Lecture Notes in Computer Science, 10513 LNCS, pp. 117-131. doi: 10.1007/978-3-319-67744-6_8
  7. Gullà, F., Ceccacci, S., Menghi, R., Germani, M., 2016. An adaptive smart system to foster disabled and elderly people in kitchen-related task. ACM International Conference Proceeding Series 29-June-2016. doi: 10.1145/2910674.2910678
  8. Gullà, F., Cavalieri, L., Ceccacci, S., Germani, M., 2016. A BBN-based Method to Manage Adaptive Behavior of a Smart User Interface. Procedia CIRP, 50, pp. 535-540. doi: 10.1016/j.procir.2016.04.162
  9. Gullà, F., Ceccacci, S., Germani, M., Cavalieri, L., 2015. Design adaptable and adaptive user interfaces: A method to manage the information. Biosystems and Biorobotics 11, pp. 47-58. doi: 10.1007/978-3-319-18374-9_5
  10. Gullà, F., Cavalieri, L., Ceccacci, S., Germani, M., Bevilacqua, R., 2015. Method to design adaptable and adaptive user interfaces. Communications in Computer and Information Science, 528, pp. 19-24. doi: 10.1007/978-3-319-21380-4_4
Scientific Manager
Working group