JUST TELL ME: A Robot-assisted E-health Solution for People with Lower-extremity Disability

Alexander Coutras, Omar Obidat, Michelle Zhu, Weitian Wang
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Abstract

Robotics technology has been increasingly applied to healthcare contexts to enhance efficiency and safety in healthcare processes in recent years. People with mobility impairments and disabilities often require caretakers in their lives. Fortunately, robots can provide attention and assistance consistently for them instead of human caretakers. Motivated by this, we develop a robot-assisted e-health solution to empower the patients' daily lives and improve their wellbeing in this study. A transfer learning-based approach is proposed to train the robot to understand and identify patients' needs through a small dataset. Using the proposed approach, the robot is able to understand the patient's needs through speech recognition and recognize objects that the patient has requested. The proposed solution is experimentally implemented in real-world human-robot interactive healthcare contexts. Results and analysis indicate the success and accuracy of our approaches.
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JUST TELL ME:机器人辅助的下肢残疾人电子医疗解决方案
近年来,机器人技术越来越多地应用于医疗保健环境,以提高医疗保健过程的效率和安全性。有行动障碍和残疾的人在生活中往往需要照顾者。幸运的是,机器人可以代替人类看护者持续地为他们提供关注和帮助。受此启发,我们开发了一个机器人辅助的电子医疗解决方案,以增强患者的日常生活能力,并在本研究中改善他们的健康状况。提出了一种基于迁移学习的方法,通过小数据集训练机器人理解和识别患者的需求。利用所提出的方法,机器人能够通过语音识别了解患者的需求,并识别患者所要求的物体。提出的解决方案在现实世界的人机交互医疗保健环境中实验性地实现。结果和分析表明,我们的方法是成功和准确的。
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