Use of an Enactive Insole for Reducing the Risk of Falling on Different Types of Soil Using Vibrotactile Cueing for the Elderly.
BACKGROUND
Our daily activities imply displacements on various types of soil. For persons with gait disorder or losing functional autonomy, walking on some types of soil could be challenging because of the risk of falling it represents.


METHODS
In this paper, we present, in a first part, the use of an enactive shoe for an automatic differentiation of several types of soil. In a second part, using a second improved prototype (an enactive insole), twelve participants with Parkinson's disease (PD) and nine age-matched controls have performed the Timed Up and Go (TUG) test on six types of soil with and without cueing. The frequency of the cueing was set at 10% above the cadence computed at the lower risk of falling (walking over the concrete). Depending on the cadence computed at the lower risk, the enactive insole activates a vibrotactile cueing aiming to improve gait and balance control. Finally, a risk index is computed using gait parameters in relation to given type of soil.


RESULTS
The frequency analysis of the heel strike vibration allows the differentiation of various types of soil. The risk computed is associated to an appropriate rhythmic cueing in order to improve balance and gait impairment. The results show that a vibrotactile cueing could help to reduce the risk of falling.


CONCLUSIONS
Firstly, this paper demonstrates the feasibility of reducing the risk of falling while walking on different types of soil using vibrotactile cueing. We found a significant difference and a significant decrease in the computed risks of falling for most of types of soil especially for deformable soils which can lead to fall. Secondly, heel strike provides an approximation of the impulse response of the soil that can be analyzed with time and frequency-domain modeling. From these analyses, an index is computed enabling differentiation the types of soil.
Department of Applied Sciences, University of Quebec at Chicoutimi (UQAC), REPARTI centre, Chicoutimi, Quebec, Canada.
Martin J-D
MJ
Otis
Department of Applied Sciences, University of Quebec at Chicoutimi (UQAC), REPARTI centre, Chicoutimi, Quebec, Canada.
Johannes C
JC
Ayena
Department of Health Sciences, University of Quebec at Chicoutimi, Chicoutimi, Quebec, Canada.
Louis E
LE
Tremblay
Department of Electrical Engineering and Computer at the Center for intelligent machine, McGill University, Montreal, Quebec, Canada.
Pascal E
PE
Fortin
Department of Mathematics and Computer Sciences, University of Quebec at Chicoutimi, Chicoutimi, Quebec, Canada.
Bob-Antoine J
BA
Ménélas
D000054:Acceleration; D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D016022:Case-Control Studies; D003463:Cues; D003710:Demography; D004581:Electronics; D005260:Female; D061826:Foot Orthoses; D005583:Fourier Analysis; D005684:Gait / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000503:physiopathology; D012306:Risk; D012815:Signal Processing, Computer-Assisted; D012987:Soil; D014110:Touch / Q000502:physiology*; D014732:Vibration; D016138:Walking / Q000502:physiology
D012987:Soil