Meinhold Waiman, Yamakawa Yoshinori, Honda Hiroshi, Mori Takayuki, Izumi Shin-Ichi, Ueda Jun
Biorobotics and Human Modeling Laboratory, Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
NITI-ON Co. Ltd., Funabashi, Japan.
Front Robot AI. 2021 Mar 16;8:618656. doi: 10.3389/frobt.2021.618656. eCollection 2021.
The deep tendon reflex exam is an important part of neurological assessment of patients consisting of two components, reflex elicitation and reflex grading. While this exam has traditionally been performed in person, with trained clinicians both eliciting and grading the reflex, this work seeks to enable the exam by novices. The COVID-19 pandemic has motivated greater utilization of telemedicine and other remote healthcare delivery tools. A smart tendon hammer capable of streaming acceleration measurements wirelessly allows differentiation of correct and incorrect tapping locations with 91.5% accuracy to provide feedback to users about the appropriateness of stimulation, enabling reflex elicitation by laypeople, while survey results demonstrate that novices are reasonably able to grade reflex responses. Novice reflex grading demonstrates adequate performance with a mean error of 0.2 points on a five point scale. This work shows that by assisting in the reflex elicitation component of the reflex exam via a smart hammer and feedback application, novices should be able to complete the reflex exam remotely, filling a critical gap in neurological care during the COVID-19 pandemic.
深部腱反射检查是患者神经学评估的重要组成部分，包括两个环节：反射激发和反射分级。传统上，这项检查由训练有素的临床医生亲自进行，既要激发反射，又要对反射进行分级，但这项工作旨在让新手也能进行该检查。新冠疫情推动了远程医疗和其他远程医疗服务工具的更多使用。一种能够无线传输加速度测量值的智能肌腱锤，能够以91.5%的准确率区分正确和错误的敲击位置，从而向用户提供关于刺激是否合适的反馈，使外行人也能激发反射，而调查结果表明新手有能力合理地对反射反应进行分级。新手反射分级表现良好，在五分制量表上平均误差为0.2分。这项工作表明，通过智能锤和反馈应用程序协助反射检查中的反射激发环节，新手应该能够远程完成反射检查，填补新冠疫情期间神经科护理的一个关键空白。
