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PHAROS- 物理助理机器人系统。

PHAROS-PHysical Assistant RObot System.

机构信息

ALGORITMI Center, University of Minho, 4704-553 Braga, Portugal.

RoViT, University of Alicante, 03690 San Vicente del Raspeig (Alicante), Spain.

出版信息

Sensors (Basel). 2018 Aug 11;18(8):2633. doi: 10.3390/s18082633.

Abstract

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 , that interacts with the users and records their exercises performance; the , that uses the Pepper recorded information to classify the exercise performed using Deep Leaning methods; and the , 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.

摘要

人口结构的巨大变化导致社会老龄化,这需要技术解决方案来满足老年人日益多样化的需求。本文介绍了 PHAROS,这是一个互动机器人系统,旨在为老年人推荐和监测专门设计的体育锻炼。PHAROS 的目标是成为一个友好的老年伴侣,定期为用户提供个性化的体育活动,促进健康的生活和积极的老龄化。文中介绍了 PHAROS 的体系结构、组成部分和实验结果。该体系结构有三个主要部分:一个是交互部分,与用户交互并记录他们的运动表现;一个是分析部分,使用 Pepper 记录的信息,使用深度学习方法对执行的运动进行分类;还有一个是智能决策部分,在用户日程中定期安排个性化的体育锻炼。实验结果表明,在检测和分类 7 个人的体育锻炼方面具有很高的准确性(97.35%)。此外,我们在推荐算法中实现了一种新的锻炼评级方法。它密切关注用户的健康状况(表现不佳可能揭示健康问题),并根据情况进行调整。历史记录可以用来了解用户的身体状况,揭示可能无法通过其他方式发现的潜在问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a272/6111326/1e644a30649e/sensors-18-02633-g001.jpg

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