Conception, réalisation et évaluation d’un système interactif dédié à la réduction des risques de chutes pour les personnes atteintes de la maladie de Parkinson

Nos activités quotidiennes impliquent des déplacements sur différents types de sol. Pour des personnes souffrant d'un trouble d’équilibre ou de perte d'autonomie, marcher sur certains sols pourrait s’avérer difficile. Il est d’ailleurs connu que 44% des chutes surviennent en trébuchant ou en glissant sur une surface. Ainsi, en raison du risque de chute que représenteraient certains sols, le premier facteur de risque qui devrait être étudié serait le type de sol. Dans cette thèse, nous présentons l'utilisation d'une chaussure interactive pour la différenciation automatique de six types de sol qui possèdent des propriétés physiques différentes. L'analyse de leur vibration lors du coup de talon a permis de les différencier. En effet, un coup de talon au sol donne une approximation de la réponse impulsionnelle du sol, qui peut être analysée aussi bien dans le domaine temporel que fréquentiel. À partir de ces analyses, un indice permettant la différenciation a été calculé. À l'aide d'un second prototype amélioré et adapté aux tailles des pieds, des personnes atteintes de la maladie de Parkinson (PAMP) ; des personnes âgées sans cette maladie et des jeunes adultes en bonne santé ont effectué deux tests cliniques sur différents types de sol. Un indice du risque de chute en fonction des paramètres d’équilibre est également calculé. De cette deuxième expérience, nous avons conclu que le type de sol affecte grandement l’équilibre humain, les paramètres de la marche et donc le niveau du risque de chute. Dans l’objectif de normaliser les paramètres de la marche, plusieurs recherches ont démontré les effets positifs d’une stimulation auditive et/ou visuelle sur les troubles d’équilibre en particulier chez les PAMP. Cependant, dans ces travaux, peu d'études ont évalué l’effet de la stimulation vibrotactile sous la plante du pied tout en la comparant aux autres types de stimulation. Ainsi, dans une troisième partie de notre thèse, nous avons utilisé et comparé trois types de stimulation (auditive, visuelle et vibrotactile). La fréquence de la stimulation a été fixée à 10% au-dessus de la cadence calculée sur le sol ayant le plus faible risque de chute. En fonction de la cadence obtenue, le second prototype (une semelle interactive) peut activer une stimulation vibrotactile visant à améliorer la marche et le contrôle de l'équilibre. Afin d’évaluer l’effet des stimulations utilisées sur le niveau du risque de chute sur un sol, nous avons comparé ces derniers résultats (avec stimulation) avec ceux obtenus dans la deuxième expérimentation (sans stimulation). Nos résultats suggèrent qu'une stimulation appropriée pourrait contribuer à la réduction d’un niveau du risque de chute sur un sol. Nous avons trouvé une différence significative et une diminution des risques de chutes calculés pour la plupart des types de sol en particulier pour les sols déformables qui peuvent faire chuter une personne présentant un trouble de la marche ou en perte d'autonomie. Our daily activities imply displacements on different types of soil. For people with a balance disorder or losing functional autonomy, walking on some types of soil could be difficult. It is known that 44% of falls occur by stumbling or sliding on a surface. Thus, due to the risk of falling of some soils, the first risk factor that should be studied would be the type of soil. In this thesis, we present the use of an interactive shoe for the automatic differentiation of six types of soil with different physical properties. The analysis of their vibration during the heel strike allows differentiating them. Indeed, a heel strike on the soil gives an approximation of the impulse response of the soil, which can be analyzed both in the temporal and frequency domain. From these analyzes, an index allowing differentiation was computed. Using a second improved prototype adapted to the size of the feet, people with Parkinson's disease (PD); the elderly without this disease and healthy young people carried out two clinical tests on different types of soil. An index of the risk of falling as a function of the gait parameters is also computed. From this second experiment, we concluded that the types of soil greatly affect the human balance, the walking parameters and therefore the level of risk of falling. To regulate walking and balance parameters, several studies have demonstrated the positive effects of auditory and/or visual stimulation on balance disorders, particularly in PD participants. However, in these works, few studies have evaluated the effect of vibrotactile stimulation under the sole of the foot while comparing it with other types of stimulation. Thus, in a third part of our thesis, we used and compared three types of stimulation (auditory, visual and vibrotactile). The frequency of stimulation was set at 10% above the cadence evaluated on the soil with the lowest risk of falling. Based on this cadence, the second prototype (an interactive insole) could activate a vibrotactile stimulation to improve walking and balance control. To evaluate the effect of the stimulations on the level of risk of falling over the soil, we compared these results (with stimulation) with those obtained in the second experiment (without stimulation). Our results suggest that an appropriate stimulation may contribute to reducing the risk of falling on soil. We found a significant difference and reduction in the risk of falls computed for most types of soil, particularly for deformable soils that can lead a person with a walking disorder or losing functional autonomy to fall

Home-based risk of falling assessment test using a closed-loop balance model

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 (COP) 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

Risk of falling assessment on different types of ground using the instrumented TUG

Degradation of postural control observed with aging is responsible for balance problems in the elderly, especially during the activity of walking. This gradual loss of performance generates abnormal gait, and therefore increases the risk of falling. This risk worsens in people with neuronal pathologies like Parkinson and Ataxia diseases. Many clinical tests are used for fall assessment such as the Timed up and go (TUG) test. Recently, many works have improved this test by using instrumentation, especially body-worn sensors. However, during the instrumented TUG (iTUG) test, the type of ground can influence risk of falling. In this paper, we present a new methodology for fall risk assessment based on quantitative gait parameters measurement in order to improve instrumented TUG test. The proposed measurement unit is used on different types of ground, which is known to affect human gait. The methodology is closer to the real walking environment and therefore enhances ability to differentiate risks level. Our system assesses the risk of falling's level by quantitative measurement of intrinsic gait parameters using fuzzy logic. He is also able to measure environmental parameters such as temperature, humidity and atmospheric pressure for a better evaluation of the risk in activities of daily living (ADL)

An Efficient Home-Based Risk of Falling Assessment Test Based on Smartphone and Instrumented Insole

The aim of this study is to improve and facilitate the methods used to assess risk of falling among older people at home. We propose an automatic version of One-Leg Standing (OLS) test for risk of falling assessment by using a Smartphone and an instrumented insole. For better clinical assessment tests, this study focuses on exploring methods to combine the most important parameters of risk of falling into a single score. Twenty-three volunteers participated in this study for evaluating the effectiveness of the proposed system which includes eleven elderly participants: seven healthy elderly (67.16 ± 4.24 years), four Parkinson disease (PD) subjects (70 ± 12.73 years); and twelve healthy young adults (28.27 ± 3.74 years). Our work suggests that there is an inverse relationship between OLS score proposed and risk of falling. Proposed instrumented insole and application running on Android could be useful at home as a diagnostic aid tool for analyzing the performance of elderly people in OLS test

Wearable devices for classification of inadequate posture at work using neural networks

Inadequate postures adopted by an operator at work are among the most important risk factors in Work-related Musculoskeletal Disorders (WMSDs). Although several studies have focused on inadequate posture, there is limited information on its identification in a work context. The aim of this study is to automatically differentiate between adequate and inadequate postures using two wearable devices (helmet and instrumented insole) with an inertial measurement unit (IMU) and force sensors. From the force sensors located inside the insole, the center of pressure (COP) is computed since it is considered an important parameter in the analysis of posture. In a first step, a set of 60 features is computed with a direct approach, and later reduced to eight via a hybrid feature selection. A neural network is then employed to classify the current posture of a worker, yielding a recognition rate of 90%. In a second step, an innovative graphic approach is proposed to extract three additional features for the classification. This approach represents the main contribution of this study. Combining both approaches improves the recognition rate to 95%. Our results suggest that neural network could be applied successfully for the classification of adequate and inadequate posture

Comparing auditory, visual and vibrotactile cues in individuals with Parkinson’s disease for reducing risk of falling over different types of soil

Introduction: Several researches have demonstrated the positive benefits of auditory and visual cueing in the gait improvements among individuals with Parkinson’s disease (PD). However, few studies have evaluated the role of vibrotactile cueing when compared to auditory and visual cueing. In this paper, we compare how these stimuli affect the risk of falling while walking on six types of soil (concrete, sand, parquet, broken stone, and two types of carpet). Methods: An instrumented Timed Up and Go (iTUG) test served to evaluate how audio, visual and vibrotactile cueing can affect the risk of falling of elderly. This pilot study proposes twelve participants with PD (67.7 ± 10.07 years) and nine age-matched controls (66.8 ± 8.0 years). Both groups performed the iTUG test with and without cueing. The cueing frequency was set at 10% above the cadence computed at the lower risk level of falling (walking over the concrete). A computed risk of falling (ROFA) index has been compared to the TUG time (total TUG duration). Results: The index for evaluating the risk of falling appears to have a good reliability (ICC > 0.88) in this pilot study. In addition, the minimal detectable change (MDC) suggests that the proposed index could be more sensitive to the risk of falling variation compared to the TUG time. Moreover, while using the cueing, observed results suggest a significant decrease in the computed risk of falling compared to ‘without cueing’ for most of types of soil especially for deformable soils, which can lead to fall. Conclusion: 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 loss functional autonomy

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