Shirin Tajali1, Mohammad Mehravar2, Hossein Negahban3, Jaap H van Dieën4, Mohammad-Jafar Shaterzadeh-Yazdi1, Razieh Mofateh1. 1. Musculoskeletal Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. 2. Musculoskeletal Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. Electronic address: mohammad.mehravar@gamil.com. 3. Department of Physical Therapy, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran; Orthopedic Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. 4. Department of Human Movement Sciences, Research Institute MOVE, VU University, Amsterdam, the Netherlands.
Abstract
BACKGROUND: Falling is a significant problem in patients with multiple sclerosis (MS) and the majority of falls occur during dynamic activities. Recently, there have been evidences focusing on falls and local stability of walking based on dynamic system theory in the elderly as well as patients with cerebral concussion. However, in patient with MS, this relationship has not been fully investigated. The aim of this study was to investigate local stability of walking as a risk factor for falling in patients with MS. METHODS: Seventy patients were assessed while walking at their preferred speed on a treadmill under single and dual task conditions. A cognitive task (backward counting) was used to assess the importance of dual tasking to fall risk. Trunk kinematics were collected using a cluster marker over the level of T7 and a 7-camera motion capture system. To quantify local stability of walking, maximal finite-time Lyapunov exponent was calculated from a 12-dimensional state space reconstruction based on 3-dimensional trunk linear and angular velocity time series. Participants were classified as fallers (≥1) and non-fallers based on their prospective fall occurrence. FINDINGS: 30 (43%) participants recorded ≥1 falls and were classified as fallers. The results of multiple logistic regression analysis revealed that short-term local dynamic stability in the single task condition (P<0.05, odds ratio=2.214 (1.037-4.726)) was the significant fall predictor. INTERPRETATION: The results may indicate that the assessment of local stability of walking can identify patients who would benefit from gait retraining and fall prevention programs.
BACKGROUND:Falling is a significant problem in patients with multiple sclerosis (MS) and the majority of falls occur during dynamic activities. Recently, there have been evidences focusing on falls and local stability of walking based on dynamic system theory in the elderly as well as patients with cerebral concussion. However, in patient with MS, this relationship has not been fully investigated. The aim of this study was to investigate local stability of walking as a risk factor for falling in patients with MS. METHODS: Seventy patients were assessed while walking at their preferred speed on a treadmill under single and dual task conditions. A cognitive task (backward counting) was used to assess the importance of dual tasking to fall risk. Trunk kinematics were collected using a cluster marker over the level of T7 and a 7-camera motion capture system. To quantify local stability of walking, maximal finite-time Lyapunov exponent was calculated from a 12-dimensional state space reconstruction based on 3-dimensional trunk linear and angular velocity time series. Participants were classified as fallers (≥1) and non-fallers based on their prospective fall occurrence. FINDINGS: 30 (43%) participants recorded ≥1 falls and were classified as fallers. The results of multiple logistic regression analysis revealed that short-term local dynamic stability in the single task condition (P<0.05, odds ratio=2.214 (1.037-4.726)) was the significant fall predictor. INTERPRETATION: The results may indicate that the assessment of local stability of walking can identify patients who would benefit from gait retraining and fall prevention programs.
Authors: Tobia Zanotto; Manuel E Hernandez; Cristina N Medrano; Kenneth R Wilund; Jacob J Sosnoff Journal: Front Neurosci Date: 2020-12-07 Impact factor: 4.677