IT and Informatics for Health and Well-being

Research activities:

Measurements in dermatology are still largely performed manually. This can introduce errors and subjective bias, and is often prohibitively time consuming. Modern computer vision techniques can be used to perform the same measurements objectively and (more) reproducibly, while dramatically cutting time and costs.

  • Automated segmentation and registration of dermatoscopically imaged lesions
  • Automated full-body detection of new and evolving melanocytic lesions
  • Automated full-body evaluation of psoriasic lesions

People: Enoch Peserico (contact person)

In our aging society the costs for healthcare is skyrocketing. In this scenario, however, ICT may provide the mean both to introduce a new, holistic dimension unifying the concept of reactive healthcare with the one of proactive well-being, and to guarantee an economy of scale. In fact, maintaining healthy life styles from young age may reduce the costs
involved in care for the elderlies.

Our research activities focus on the problems related to memory disfunctions that are typical of the elderlies.

  • mobile and pervasive computing
  •  context aware systems
  •  systems to support reduced memory abilities in aging
  •  systems to enhance daily efficiency
  • systems to guarantee prolonged independent living.

People: Mauro Migliardi (contact person), Carlo Ferrari, Loris Nanni

Support to medical diagnosis with classification and data mining techniques

People: Loris Nanni (contact person), Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci

Brain-Machine Interfaces and  Human-Machine Interfaces based on Neuromusculoskeletal models are the two major research topics on Neurorobotics. In particular, the research group focuses on developing new wearable devices to acquire, process and classify neuro-signals to control assistive robots for disable users. with the goal of improving the current neuro-motor rehabilitation processes.

  • Biomechanical models of human movement

  • Neuromusculoskeletal modeling and simulation
  • Detection and classification of movement intentions

  • EMG-based control of virtual and robotic prostheses 

  • Brain-Machine Interface


People: Emanuele Menegatti (contact person), Enrico Pagello