The variability of the steps preceding obstacle avoidance (approach phase) is dependent on the height of the obstacle in people with Parkinson's disease
نویسندگان
چکیده
Gait variability may serve as a sensitive and clinically relevant parameter to quantify adjustments in walking and the changes with aging and neurological disease. Variability of steps preceding obstacle avoidance (approach phase) are important for efficiency in the task, especially in people with Parkinson's disease (PD). However, variability of gait during the approach phase to obstacle avoidance in people with PD has been rarely reported, particularly when ambulating obstacles of different heights. The aim of the present study was to investigate the effects of obstacle height on step-to-step variability (step-to-step variability provides information on the variation between the "equivalent steps" for all trials, and walking variability (indicates the within-step variability of each, providing information about the modulations between the steps performed. of spatial-temporal parameters during the approach phase to obstacle avoidance in people with PD and neurologically healthy older people. Twenty-eight older people; 15 with PD and 13 neurologically healthy individuals (control group), participated in the study. Participants were instructed to walk at their preferred speed until the end of the pathway and to avoid the obstacle when it was present. Each subject performed 10 trials of the following tasks: unobstructed walking, low obstacle avoidance (3cm length, height equal ankle's height, 60 cm wide), intermediate obstacle (3cm length, low plus high obstacle height divided by 2, 60 cm wide) avoidance and high obstacle avoidance (3cm length, knee's height, 60 cm wide). The obstacle was positioned 4m from to the start position. The step-to-step and walking variability of the spatial-temporal parameters (acquiring with GAITRite®) of the four steps before obstacle avoidance were analyzed. MANOVAs were used to compare the data. PD group showed the characteristic gait deficits associated with PD. The obstacle increased the spatial-temporal variability (step-to-step and walking variability) during the approach phase to the obstacle. Specifically, both groups increased i) the step-to- step variability of the step length during low obstacle avoidance when compared to the other conditions; ii) the variability during low obstacle avoidance in the last step before obstacle (n-1) compared to higher obstacle avoidance; iii) variability during higher obstacle avoidance in further steps (n-3 and n-4). In conclusion, the presence of the obstacle during walking increased the variability of spatial-temporal parameters in older people with PD and the control group during the steps preceding obstacle avoidance. In addition motor planning (and motor adaptations) was initiated much earlier in the approach phase for the higher obstacle conditions compared to the low obstacle condition.
منابع مشابه
Dynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملDirect Optimal Motion Planning for Omni-directional Mobile Robots under Limitation on Velocity and Acceleration
This paper describes a low computational direct approach for optimal motion planning and obstacle avoidance of Omni-directional mobile robots within velocity and acceleration constraints on the robot motion. The main purpose of this problem is the minimization of a quadratic cost function while limitation on velocity and acceleration of robot is considered and collision with any obstacle in the...
متن کاملDesigning Path for Robot Arm Extensions Series with the Aim of Avoiding Obstruction with Recurring Neural Network
In this paper, recurrent neural network is used for path planning in the joint space of the robot with obstacle in the workspace of the robot. To design the neural network, first a performance index has been defined as sum of square of error tracking of final executor. Then, obstacle avoidance scheme is presented based on its space coordinate and its minimum distance between the obstacle and ea...
متن کاملA Navigation System for Autonomous Robot Operating in Unknown and Dynamic Environment: Escaping Algorithm
In this study, the problem of navigation in dynamic and unknown environment is investigated and a navigation method based on force field approach is suggested. It is assumed that the robot performs navigation in...
متن کاملOptimal Trajectory Planning of a Mobile Robot with Spatial Manipulator For Spatial Obstacle Avoidance
Mobile robots that consist of a mobile platform with one or many manipulators mounted on it are of great interest in a number of applications. Combination of platform and manipulator causes robot operates in extended work space. The analysis of these systems includes kinematics redundancy that makes more complicated problem. However, it gives more feasibility to robotic systems because of the e...
متن کامل