Development of a vibratory cueing system using an implicit method to increase walking speed in patients with stroke: a proof-of-concept study

Kazuhiro Yasuda*, Yuki Hayashi, Anna Tawara, Hiroyasu Iwata

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

One of the main sequelae of stroke is dificulty walking, which is characterized by a decreased gait velocity and asymmetrical walking patterns. The purpose of this research was initially focused on developing a vibro-tactile cueing device that recognizes an implicit increase in cadence frequency. Subsequently, a proof-of-concept study with patients who had experienced stroke was conducted to examine the applicability of the system that had been developed. We applied Weber’s law to provide an implicit method for increasing cueing frequency. This law involves the calculation of just-noticeable difference (JND) relative to a previous state. Throughout training with the proposed cueing device, patients marginally increased cadence, and their cadence and gait speeds were significantly increased post-test. Hip circumduction gait (i.e., abnormal gait patterns) did not change significantly throughout training. Notably, patients reported that they were unaware of any changes associated with the vibration stimulus. Our result demonstrates the immediate changes to cadence and gait speed that occurred through training with the proposed implicit cueing device. However, the result of this study is confined to immediate gait changes after training and utilized only a small sample of stroke patients. Thus, the limited volume of data obtained prevents rigorous analysis regarding the applicability of this training method. Nonetheless, these results are promising and provide a starting point from which to base larger studies.

Original languageEnglish
Article number1
JournalROBOMECH Journal
Volume7
Issue number1
DOIs
Publication statusPublished - 2020 Dec 1

Keywords

  • Cueing
  • Gait training
  • Haptic device
  • Implicit motor learning
  • Stroke

ASJC Scopus subject areas

  • Modelling and Simulation
  • Instrumentation
  • Mechanical Engineering
  • Control and Optimization
  • Artificial Intelligence

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