Research and Development

Our team is constantly active in research and development of innovative and disruptive solutions for human-machine interaction.

Shorten the gap between the patient and the outside world

A multidisciplinary approach

Braincontrol AAC is the result of a multidisciplinary approach that combines different elements and discipline in order to obtain a modular, customizable and adaptable platform to the needs of users:

  • Wearable sensors for biofeedback data acquisition;
  • Artificial intelligence for application and classification of biofeedbacks;
  • Robotics to empower rehabilitation and remote interaction;
  • Assistive technologies for improving the quality of life.

This is the starting point of a new Human-Computer Interaction era.

Current State

Compelling needs

There are over 140 million people globally with paralysis due to neuromuscular degenerative diseases such as multiple sclerosis, amyotrophic lateral sclerosis-ALS or due to stroke, traumatic injury and aging process. Over 20 million of these are completely paralyzed and have communication difficulties.

To date, the main assistive technologies provide voice-controlled, eye-tracking or residual movement based solutions. Voice-controlled systems based on speech recognition cannot be used by millions of patients who cannot speak due to these pathologies; eye-tracking systems, based on tracking pupil movements, are often not portable and cannot be used by all patients, as well as other devices based on residual movements.

Furthermore, the existing solutions are often vertical, making it difficult to personalize the various types of disabilities and their evolution in the case of neurodegenerative diseases. 

Finally, for these types of diseases, an effective tool for the functional and cognitive assessment of patients is also lacking.

Our approach

Smart Multimodal Platform

BrainControl AAC is a multimodal and horizontal platform, customizable and adaptable in order to meet the specific needs of each patient at any time and responding to the different degrees and types of impairment caused by the pathology.

The heart of the system is a pattern classifier of signals coming from wearable biometric sensors such as EEG or inertial and environmental such as 2d and 3d cameras, based on a Machine Learning and Artificial Intelligence technology for the personalization of the different needs in various patients.

The Brain Computer Interface (BCI) is based on a research line called Motor Imagery which uses 12 types of movements: 6 rotations and 6 directions.  These thoughts create unique patterns of electrical activity in our brain that can be identified. The general pattern of electrical activity is the same from person to person with small differences, that can be aligned with a calibration of the system.

The primary objective is to use the platform as an AAC device. In the near future it will be validated, through a clinical trial, as a tool for the functional and cognitive assessment of patients. Future versions will implement advanced home automation features such as lights, alarms and temperature, but also robotics such as avatar and exoskeletons.

Ongoing research

Improvement of quality of life

The platform could be easily applicable to a large number of patients, at home and hospital, making improvements on their quality of life and giving them the opportunity to communicate with relatives. This allows to preserve their working activities even at home until it will be possible. New technologies as Braincontrol, based on artificial intelligence, could help in managing patients at home, reducing costs for hospitalization.

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