Cleaning Behavior Estimation for Self-Supported Cognitive Rehabilitation System

Hiroki Kojima, M. Kitano, K. Yokota, Sho Ooi, Mutsuo Sano
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引用次数: 2

Abstract

People suffering from brain injury can present complications such as attention disorder, memory disorder, functional disorder, and aphasia, which limit their capacity to perform activities of daily living. We aim to implement a system for cognitive rehabilitation based on daily routines. For instance, we previously reported the benefits of cognitive rehabilitation through cooking. In this paper, we focus on cognitive rehabilitation based on cleaning tasks, which are as important as cooking for daily living. We tested the system with the help of a patient from the Osaka Prefecture Self-Reliance Center for People with Disabilities on November 9, 16 and 30, 2017. We propose and test a system that detects some cleaning tools and a human skeleton to assess the patients' behavior while cleaning, and rehabilitation is guided using indoor navigation. Object recognition allowed to integrate information about the cleaning tools to determine different cleaning behaviors. In addition, we tracked the patient to determine her state from a library of five states for the recognized skeleton in different cleaning areas. By detecting the cleaning tools and person's state, we estimated the cleaning behavior. As state estimation may retrieve a high rate of misidentification of the person's state, we implemented an error correction algorithm for estimating the cleaning behavior based on previous states, thus improving the system accuracy. We evaluated the university environment before testing the system, and determined the accuracy of both object recognition and person's state for estimating the cleaning behavior.
自我支持认知康复系统的清洁行为评估
脑损伤患者可能出现注意力障碍、记忆障碍、功能障碍和失语症等并发症,从而限制他们进行日常生活活动的能力。我们的目标是实现一个基于日常生活的认知康复系统。例如,我们之前报道过烹饪对认知康复的好处。在本文中,我们关注的是基于清洁任务的认知康复,清洁任务在日常生活中与烹饪一样重要。2017年11月9日、16日和30日,我们在大阪府残疾人自立中心的一名患者的帮助下对该系统进行了测试。我们提出并测试了一个系统,该系统可以检测一些清洁工具和人体骨骼,以评估患者在清洁时的行为,并使用室内导航指导康复。物体识别允许整合有关清洁工具的信息,以确定不同的清洁行为。此外,我们对患者进行了跟踪,从不同清洁区域识别的骨骼的五种状态库中确定她的状态。通过检测清洁工具和人的状态,对清洁行为进行估计。由于状态估计可能对人的状态有很高的误认率,我们实现了一种基于先前状态估计清洁行为的纠错算法,从而提高了系统的准确性。在测试系统之前,我们对大学环境进行了评估,并确定了物体识别和人的状态对估计清洁行为的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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