The Augmented Human Assistant project is an ambitious scientific and technological endeavour that aims at providing solutions to alleviate the current and upcoming social, psychological and economical burden related to sedentarism and aging related morbidities. It brings together innovation and research in a cross-disciplinary consortium with expertise in such diverse areas such as Human Functioning and Performance, Augmented Reality (AR) technologies, serious games for health, physiological signal

acquisition systems, computer vision systems, robot navigation and intelligent scene assessment. The contributions of this complementary expertise are organized in 3 major work packages:

WP1 – Augmented Reality Training;

WP2 – Human State Awareness;

WP3 – Virtual Coach. Each of these work packages is responsible for a so called AHA module, which are the core technological components of the AHA static platform.

WP4 – Robotic Assistance Platform results from the integration of the static platform
with a mobile robotic device.

WP5 – End user evaluation is a transversal work package to evaluate the
separate components as well as the static and mobile platforms in realistic scenarios.

Dissemination and exploitation are addressed in WP6.

The integrated AHA system will be composed by a mobile robotic platform with advances in perception, navigation and control skills; leveraged with an extended set of sensors for human sensing and emotional state estimation; serious gaming abilities through novel augmented reality methods yielding extended feedback modalities for physical exercising and motor rehabilitation; and a virtual coach system with technologies and techniques that assist and encourage users while they perform rehabilitation exercises, and instills better compliance with their prescribed exercise regimen. Such platform will define a new class of assistive devices for healthy, elderly and patient users, allowing new modalities of interaction and engagement not yet available in the state-of-the-art.

The technologies and techniques that we are proposing in this project are expected to lead to better adherence to training/rehabilitation, hence better and faster outcomes. Specifically, we are proposing personalization technologies that will adapt the physical training uniquely to each user and each exercise session in the context of an overall rehabilitation process. We will deploy our technologies in end user trials that explore various combinations of technology and user engagement.