scholarly journals Questioning Classic Patient Classification Techniques in Gait Rehabilitation: Insights from Wearable Haptic Technology

Author(s):  
Theodoros Georgiou ◽  
Simon Holland ◽  
Janet van der Linden ◽  
Glenis Donaldson
GeroPsych ◽  
2016 ◽  
Vol 29 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Véronique Cornu ◽  
Jean-Paul Steinmetz ◽  
Carine Federspiel

Abstract. A growing body of research demonstrates an association between gait disorders, falls, and attentional capacities in older adults. The present work empirically analyzes differences in gait parameters in frail institutionalized older adults as a function of selective attention. Gait analysis under single- and dual-task conditions as well as selective attention measures were collected from a total of 33 nursing-home residents. We found that differences in selective attention performances were related to the investigated gait parameters. Poorer selective attention performances were associated with higher stride-to-stride variabilities and a slowing of gait speed under dual-task conditions. The present findings suggest a contribution of selective attention to a safe gait. Implications for gait rehabilitation programs are discussed.


2012 ◽  
Author(s):  
Alasdair Matthew Goodwill ◽  
Skye Stephens ◽  
Sandra Oziel ◽  
Nicola Bowes

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.


Sign in / Sign up

Export Citation Format

Share Document