Autonomous social robotics for pediatric assistance and active aging

Research

In traditional neurorehabilitation therapies, there is often a loss of interest and engagement due to their intrinsic characteristics. They are repetitive, long, hard and boring.

Aim

  • To validate RoboTherapist as a general framework for hands-off robotic rehabilitation activities focused on promoting the patients’ motivation while meeting the clinical criteria. Through sensors like a 3D camera, the patient can be corrected and rewarded according to performance. The main beneficiaries of this novel methodology are pediatric and geriatric patients with motor or cognitive disorders. The market potential includes hospitals, associations, insurance providers and rehabilitation units.

Problem to Solve

Neurorehabilitation therapies are very important to recover neuronal connections through physical or cognitive exercises. However, these treatments are often long, hard, repetitive and boring. This causes disengagement and high dropout rates among the patients.

Therapists must spend a large proportion of their time motivating these patients to continue their exercises, which places great socio-economic strain on the healthcare system. There is currently no commercial solution to ease the therapist's workload, that is also extensible and customizable enough to meet clinical needs.

Innovation

The philosophy of RoboTherapist is to develop neurorehabilitation therapies based in social interaction, exploiting the affective bonds established between the patient and the robot, which minimizes the risk of possible physical injuries.

A sophisticated artificial intelligence system provides the robot with enough autonomy to drive a whole rehabilitation session without human intervention, reacting coherently to unexpected situations. The system is very easy to configure for specific treatments and can generate precise clinical reports automatically. RoboTherapist can be easily applied to other pathologies and patient groups, as well as sensors and robots.

Team

Project leader. Faculty member

Fernando Fernández Rebollo

Project leader

Main developer. PhD student

José Carlos González Dorado

Main developer. PhD student

José Carlos Pulido Pascual

MENTOR

Global Product Marketing Manager

Raúl Zurita

B. Braun España

Partners

Obra social “la Caixa”
Caixa Capital Risc
Validate-19

Scientific Area

Neurosciences

Business area

Therapeutic

Research center

Universidad Carlos III de Madrid