A Smart Tendon Hammer System for Remote Neurological Examination

Waiman Meinhold, Yoshinori Yamakawa, Hiroshi Honda, Takayuki Mori, Shin Ichi Izumi, Jun Ueda

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number618656
JournalFrontiers in Robotics and AI
Volume8
DOIs
Publication statusPublished - 2021 Mar 16

Keywords

  • COVID-19 pandemic
  • IoT
  • neurology
  • reflex
  • remote diagnosis

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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