PHAROS - PHysical Assistant RObot System

• Autor(a) principal: Costa, Ângelo
• Data de Publicação: 2018
• Outros Autores: Martinez-Martin, Ester, Cazorla, Miguel, Julian, Vicente
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/60129
• topic: robot assistant; deep learning; cognitive assistant; elderly physical exercise; human exercise recognition; gesture recognition; ambient assisted living; Science & Technology

The great demographic change leading to an ageing society demands technological solutions to satisfy the increasing varied elderly needs. This paper presents PHAROS, an interactive robot system that recommends and monitors physical exercises designed for the elderly. The aim of PHAROS is to be a friendly elderly companion that periodically suggests personalised physical activities, promoting healthy living and active ageing. Here, it is presented the PHAROS architecture, components and experimental results. The architecture has three main strands: a <i>Pepper robot</i>, that interacts with the users and records their exercises performance; the <i>Human Exercise Recognition</i>, that uses the Pepper recorded information to classify the exercise performed using Deep Leaning methods; and the <i>Recommender</i>, a smart-decision maker that schedules periodically personalised physical exercises in the users’ agenda. The experimental results show a high accuracy in terms of detecting and classifying the physical exercises (97.35%) done by 7 persons. Furthermore, we have implemented a novel procedure of rating exercises on the recommendation algorithm. It closely follows the users’ health status (poor performance may reveal health problems) and adapts the suggestions to it. The history may be used to access the physical condition of the user, revealing underlying problems that may be impossible to see otherwise.