Baltazar André R, Petry Marcelo R, Silva Manuel F, Moreira António Paulo
Departamento de Engenharia Eletrotécnica e de Computadores, Faculdade de Engenharia da, Universidade do Porto, Porto, Portugal.
CRIIS - Centro de Robótica Industrial e Sistemas Inteligentes, INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Porto, Portugal.
SN Appl Sci. 2021;3(3):354. doi: 10.1007/s42452-021-04304-1. Epub 2021 Feb 22.
The transport of patients from the inpatient service to the operating room is a recurrent task in a hospital routine. This task is repetitive, non-ergonomic, time consuming, and requires the labor of patient transporters. In this paper is presented a system, named Connected Driverless Wheelchair, that can receive transportation requests directly from the hospital information management system, pick up patients at their beds, navigate autonomously through different floors, avoid obstacles, communicate with elevators, and drop patients off at the designated operating room. As a result, a prototype capable of transporting patients autonomously in hospital environments was obtained. Although it was impossible to test the final developed system at the hospital as planned, due to the COVID-19 pandemic, the extensive tests conducted at the robotics laboratory facilities, and our previous experience in integrating mobile robots in hospitals, allowed to conclude that it is perfectly prepared for this integration to be carried out. The achieved results are relevant since this is a system that may be applied to support these types of tasks in the future, making the transport of patients more efficient (both from a cost and time perspective), without unpredictable delays and, in some cases, safer.
在医院日常工作中，将患者从住院部转运至手术室是一项重复性任务。这项任务具有重复性、不符合人体工程学、耗时且需要患者转运人员付出劳动。本文介绍了一种名为“联网无人驾驶轮椅”的系统，它能够直接从医院信息管理系统接收运输请求，在病床处接载患者，在不同楼层自主导航，避开障碍物，与电梯通信，并将患者送至指定的手术室。结果，获得了一个能够在医院环境中自主运输患者的原型。尽管由于新冠疫情，无法按计划在医院对最终开发的系统进行测试，但在机器人实验室设施中进行的广泛测试以及我们此前在医院集成移动机器人的经验，使我们能够得出结论，该系统已为进行这种集成做好了充分准备。取得的成果意义重大，因为这是一个未来可能应用于支持此类任务的系统，能使患者运输更高效（从成本和时间角度来看），不会出现不可预测的延误，并且在某些情况下更安全。
