When compared to other cueing, it seems that audio could be a better neurofeedback for reducing the risk of falling over different walking surfaces, which represent important risk factors for persons with gait disorder or lost functional autonomy.
Abstract-It is known that the physical conditions of an environment might represent an important risk of falling. In this paper, we report an ongoing project toward the creation of intelligent clothes aiming at preventing falls related to such conditions. The package described here is centered on an intelligent shoe. The developed prototype counts two main parts: hardware and software. The material is composed of a set of sensors and actuators, distributed in strategic positions of the shoe, while the software is a soft real-time system running on a Smartphone. Our prototype has been served for the differentiation of physical properties of soils (concrete, broken stone, sand and dust stone).
The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.
Considering the current pyramidal age of developed countries it appears that there is a need for tools that can automatically evaluate a person's ability to maintain balance. Proposed system, is a serious game running on the Android OS. It uses an augmented sole in order to measure movements realized by the user. For this evaluation, the same exercises proposed in the Berg Balance Scale are used; however they do receive a more motivating and engaging appeal through several events. When using the proposed system, a detailed analysis of the movements realized by the user can be done.
BackgroundOur 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.MethodsIn 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.ResultsThe 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.ConclusionsFirstly, 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.
Abstract-To prevent accidental falls, we have designed an augmented shoe aiming at assisting a user when walking. To this, the risk level (low, medium, high and very high) represented by the current situation is conveyed to the user through vibrotactile messages. In this paper, we describe the design of a serious game dedicated to learning of these signals. The game is centered on a virtual maze, whose parts are associated with the four risk levels. To explore this maze, fitted with a pair of the augmented shoes, the user is invited to walk in a room, completely empty, whose dimensions are mapped to those of the virtual maze. When moving, for each area explored the corresponding signal is delivered to the user through the augmented shoes. An initial experiment confirmed the idea that vibrotactile messages can serve for communicating the level of risk.
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