Street rehab: Linking accessibility and rehabilitation

Street rehab: Linking accessibility and rehabilitation
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街道康复:将无障碍与康复联系起来

DOI:
10.1109/embc.2016.7591401
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发表时间:
2016
期刊:
--
影响因子:
--
通讯作者:
Holloway C
Holloway C
中科院分区:
--
文献类型:
--
作者:
Holloway C

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作为众包云服务无障碍路线项目(ARCCS)的一部分,我们使用ARCCS传感器进行了一系列实验,以识别轮椅使用者的推动方式。ARCCS的目标是利用一套校准良好的传感器来建立一个处理链,然后提供关于位置、环境性质和生理努力的已知精度的地面真相。在本文中,我们关注两个分类问题:1)人们在推自己时使用的推方式;2)这个人是被服务员推还是自己推(与推方式无关)。解决第一个问题使我们能够开发出一种粒度级别,以推动超越复原和可访问性的分类。第一个问题是使用腕式ARCCS传感器解决的,第二个问题是使用轮式ARCCS传感器解决的。在室内和室外环境下,推风格分为半圆形和弧形两种,准确率和召回率都很高(95%)。ARCCS传感器还被证明能够以近乎完美的精度和召回率识别随从和自我推进,而不需要佩戴在身上的传感器。
As part of the Accessible Routes from Crowdsourced Cloud Services project (ARCCS) we conducted a series of experiments using the ARCCS sensor to identify push style of wheelchair users. The aim of ARCCS is to make use of a set of well-calibrated sensors to establish a processing chain that then provides ground truth of known accuracy about location, the nature of the environment, and physiological effort. In this paper we focus on two classification problems 1) The push style employed by people as they push themselves and 2) Whether the person is being pushed by an attendant or pushing themselves (independent of push style). Solving the first enables us to develop a level of granularity to pushing classification which transcends rehabilitation and accessibility. The first problem was solved using a wrist-mounted ARCCS sensor, and the second using a wheel-mounted ARCCS sensor. Push styles were classified between semi-circular and arc styles in both indoor and outdoor environments with a high-decrees of precision and recall (>95%). The ARCCS sensor also proved capable of discerning attendant from self-propulsion with near perfect accuracy and recall, without the need for a body-worn sensor.
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