iFeel

Next step in continuous human health monitoring

We aim at providing an integrated platform that enables real-time human health monitoring in terms of motion tracking, articular stress monitoring, and fatigue analysis.

We are a spinoff of the Artificial and Mechanical Intelligence Lab at the Italian Institute of Technology.

Based on our extensive and in depth research analysis we developed ground breaking technology.

The combination of iFeel wearable devices and the power of iFeel algorithms gave birth to a stunning new technology: whole-body wearable technology for real-time fatigue analysis to prevent human musculoskeletal diseases by enhancing ergonomic user experience.

Think of a suit equipped with iFeel wearable devices, sensorized shoes and flexible . The output is transferred to the iFeel AI algorithm, which is able to:

  • track human motions
  • analyse the fatigue in the back-end
  • provide the user with the feedback through the interface

Case studies

Industrial field

We carried out a deep research in diverse fields such as industry and it came to light that the only monitoring tool consisted of a manual and visual inspection at an industrial site. This process has been used for more than 200 years and results are not effective since a visual inspection is only the tip of the iceberg. Try to think about the huge amount of economic resources spent on (MSDs) treatment and just imagine what would happen, thanks to our technology, we were able to prevent human fatigue and bring about immediate action.

Rehabilitation field

The lack of quantitative analysis is not only common in the industrial field, but also in the rehabilitation process in case of gait disorders and prosthesis implementation. The rehabilitation process expects the patient to refer to a rehabilitation center where monitoring takes place. However, those centers are costly and not easily nor always accessible. Notwithstanding these issues, a quantitative and continuous monitoring is still missing. What if we were able to provide patients and rehabilitation professionals with a and easy-to-use technology? And what if this new technology was able to continuously monitor the changes in their rehabilitation process and optimize it based on their needs? In this way the rehabilitation process can be completely tailored on the patient’s needs.

Team

Our founding team is a group of professionals with diverse backgrounds in research and development both in industry and academia. We strongly believe that our team is not only the sum of single skills but a real integration. We are a multi-cultural, multilingual team and we all share a passion for technological development and innovation focused on the being.

Technical Expertise

  • Electronics

  • Software
  • Biomedical Engineering
  • Complex Cyber-Physical Systems
  • Applied Machine Learning
  • Artificial Intelligence

Organizational Expertise

  • Multi-year Project Planning
  • Agile Management & Execution
  • Financial Planning
  • Technology Transfer from academia to industry
  • Digital Marketing
  • Science Communication

Enrico Valli

Enrico Valli received the MSc degree in electronic engineering from the University of Bologna with a research thesis on System-on-Chip developed at the University of Southampton. After a long work experience in ESA, he joined IIT where he is now involved in the development of a wearable wireless sensors network.

Enrico Valli

Claudia Latella

Claudia Latella received her BEng in Biomedical Engineering and MEng in Bioengineering at the University of Genova (Italy). After a working period, she came back to the academic environment starting her Ph.D in November 2014 at the Italian Institute of Technology where she obtained her Ph.D title in March 2018.  Since then, she is a Post Doc researcher in the Artificial and Mechanical Intelligence Research line at IIT.

Claudia Latella

Daniele Pucci

After receiving his PhD title in France and a long experience as Post Doc at IIT, Daniele Pucci is now Principal Investigator of Artificial and Mechanical Intelligence Research Line at IIT. The main AMI lab research focus is on the humanoid robot locomotion problem, with specific attention on the control and planning of the associated nonlinear systems. In December 2019, Daniele Pucci was awarded as Pioneer of the Year Under 35 Europe from the MIT Technology Review magazine. He's now coordinating the newborn ergoCub project with INAIL aiming at developing new wearable technologies and humanoid robots to support humans in different fields.

Daniele Pucci

Marta Caracalli

Marta Caracalli received her MSc in Translation and Interpreting from the University of Genoa in 2016 with Spanish and Russian are her main domains. After different work experiences, she joined IIT in 2019 as Assistant supporting iCub Research Lines. In the iFeel team she takes care of the administrative and organizational aspects.

Marta Caracalli

Gianluca Milani

Gianluca Milani received his MSc degree at University of Pavia in Electrical Engineering in 2017. From 2017 to 2019, he has been working as a Consultant at ‘Centro Elettro-tecnico Sperimentale Italiano’ (CESI), supporting international grid operators in developing electrical and energy infrastructures. In 2019 he moved to Genoa, where he is currently working as a Visiting Scientist in the Artificial and Mechanical Intelligence (AMI) lab of IIT. Here, his main activity concerns the electronic design of wearable devices, to be applied in different fields such as robotics, teleoperation and healthcare.

Gianluca Milani

Gianmarco Gatti

Gianmarco Gatti has studied Industrial design In Politecnico di Milano and he has graduated in master of Design& engineering in 2020. In July 2021 he joined IIT as Research fellow at the Artificial and Mechanical Intelligence research line, and he is currently involved as Industrial designer in the EU project ErgoCub and in the development of a wearable wireless sensors technology called iFeel.

Gianmarco Gatti

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Acknowledgements

An.Dy project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 731540

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. xxxx). Overall budget € xxxx. ERC Project Info.

xxx is a research project funded from the European Union’s Horizon 2020 research and innovation actions (RIA) scheme under grant agreement no. xxxx.

© xxx PROJECT