A novel multifunctional intelligent bed integrated with multimodal human–robot interaction approach and safe nursing methods

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS
Donghui Zhao, Yuhui Wu, Chenhao Yang, Junyou Yang, Houdei Liu, Shuoyu Wang, Yinlai Jiang, Yokoi Hiroshi
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引用次数: 0

Abstract

The authors propose a multifunctional intelligent bed (MIB) that integrates multiple modes of interaction to improve the welfare of mobility-impaired users and reduce the workload of medical personnel. The MIB features independent autonomous omnidirectional movement, position adjustment, multi-degree-of-freedom (DOF) movement regulation and posture memory functions to facilitate comfortable and convenient interaction for mobility-impaired users. In particular, an integrated “MIB-state perception-interaction interfaces” system is established, and a bed fall risk detection algorithm and assisted get-up-transfer algorithm is proposed. By recognising and sharing human body state characteristics, nursing collaboration can be achieved with caregivers or other nursing robots. Comprehensive experiments demonstrate that the MIB is a novel MIB that is highly adaptable to the environment, convenient to interact with and safe. By integrating the proposed algorithms, daily safety monitoring, assisted get-up and defecation tasks can be effectively accomplished. This technology demonstrates excellent applicability and promising prospects for implementation in hospitals, nursing centres and homes catering to elderly and disabled individuals with mobility impairments.

Abstract Image

一种新型多功能智能床,融合了多模式人机交互方法和安全护理方法
作者提出了一种集成多种交互模式的多功能智能床(MIB),以提高行动不便用户的福利,减轻医务人员的工作量。MIB具有独立的自主全向运动、位置调节、多自由度运动调节和姿势记忆功能,为行动不便的用户提供舒适方便的互动。特别是,建立了一个集成的“MIB状态感知交互接口”系统,并提出了跌倒风险检测算法和辅助起床转移算法。通过识别和共享人体状态特征,可以与护理人员或其他护理机器人实现护理协作。综合实验表明,MIB是一种对环境适应性强、交互方便、安全的新型MIB。通过集成所提出的算法,可以有效地完成日常安全监测、辅助起床和排便任务。这项技术在医院、护理中心和为行动不便的老年人和残疾人提供服务的家庭中具有良好的适用性和良好的应用前景。
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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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