Questioning classic patient classification techniques in gait rehabilitation: Insights from wearable haptic technology

Theodoros Georgiou*, Simon Holland, Janet van der Linden, Glenis Donaldson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Classifying stroke survivors based on their walking abilities is an important part of the gait rehabilitation process. It can act as powerful indicator of function and prognosis in both the early days after a stroke and long after a survivor receives rehabilitation. This classification often relies solely on walking speed; a quick and easy measure, with only a stopwatch needed. However, walking speed may not be the most accurate way of judging individual’s walking ability. Advances in technology mean we are now in a position where ubiquitous and wearable technologies can be used to elicit much richer measures to characterise gait. In this paper we present a case study from one of our studies, where within a homogenous group of stroke survivors (based on walking speed classification) important differences in individual results and the way they responded to rhythmic haptic cueing were identified during the piloting of a novel gait rehabilitation technique.

Original languageEnglish
Title of host publicationeHealth 360°
EditorsKostas Giokas, Laszlo Bokor, Frank Hopfgartner
Number of pages13
ISBN (Electronic)9783319496559
ISBN (Print)9783319496542
Publication statusPublished - 2017
Event2016 International Summit on eHealth 360° - Budapest, Hungary
Duration: 14 Jun 201616 Jun 2016

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X


Conference2016 International Summit on eHealth 360°


  • Classification
  • Haptic Bracelets
  • Rhythmic haptic cueing
  • Stroke

ASJC Scopus subject areas

  • Computer Networks and Communications


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