Dual-tasking and the effect of short-term training on risk of falling in patients with COPD Farahnaz FallahTafti and Jennifer Yentes Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE 68182 INTRODUCTION METHODS CONT’D Patients with chronic obstructive pulmonary disease (COPD) have a significant deficit in their balance control compared to healthy controls. In addition, these patients are estimated to have falls five times more often than other older adults annually [1,2]. These falls are one of the main causes of injuries, reduced functioning, and mortality. Therefore, assessment of fall risk and stability plays a critical role in fall prevention in these patients. Although, postural control is thought of as an automatic task, it does require attention. Allocating attention to postural control may decrease when engaging in a dual-task. Both tasks may require a portion of information processing capacity and if one exceeds the level of total capacity, performance of one or both will deteriorate. It also depends on the resources that every task requires [3,4]. Fall risk is directly linked to postural and dynamic stability, which could be analyzed by gait variability. PURPOSE: The present study is designed to investigate how gait variability will change in patients with COPD during dual tasking in order to identify subjects that are at greater risk of fall. Secondly, the effect of dual-task training on postural control will be determined. (a) (b) (c) METHODS (d) (f) Figure 1. a)IMU node Actigraph. b)pedar-x system. c)IMU node that is attached to the back of subject. d) pedar-x insoles consist of 99 piezo sensors each pair. f) subject with all equipment walking on the uneven surface. Postural control will be assessed under single and dual task conditions. The subjects will be divided into three groups as seen in the table below: Data Analysis: One tri-axial IMU (Motion tracker: ActiGraph GT9X Link + ActiLife) will be attached at the lower back (i.e., L5/S1) in order to observe sway changes (Figure 1) [5]. In-shoe center of pressure, stride time, duration of gait cycle, and swing time will be determined by pedar-x pressure sensors (Novel Electronics, Inc., St. Paul, MN) placed in the subjects’ shoes. Stride time variability and swing time variability will be defined by standard deviation of each subjects stride time and swing time. Gait variability parameters, stride time and swing time variability, will be analyzed as predictive parameters for future falls [6]. Proposed Statistical Design: Repeated measures analysis of variance (ANOVA) (3 groups x 4 conditions x 2 time points) will be used in order to investigate if there was any significant difference between the groups, conditions, or an effect of training. Regression analysis will be used to determine the association of gait variability with future falls. Group 1 Group 2 Group 3 Healthy Control Patients with COPD (No Training) Patients with COPD (Trained) Participants will be asked to perform four experimental conditions: Condition 1 Condition 2 Condition 3 Condition 4 Single task, even surface Single task, uneven surface Dual task, even surface Dual task, uneven surface The dual-task condition(s) consists of carrying a tray with glasses of water on it while walking . Subjects will be asked to walk at their normal pace continuously for 10 minutes on the large fields for each of the four conditions with 15 minutes rest in between trials. Conditions will be randomized. Training protocol: Training on the postural challenging dual-tasks plus complementary balance training will be done over a 6 week period, three sessions of 45 minutes training each week. Post test and Follow up: Upon completion of the training, subjects will return to complete the four experimental conditions again. Untrained and control groups will be asked to return for follow up and repeat the four experimental conditions again. Afterwards, in order to determine risk of falls, all subjects will be asked to report their fall status weekly for 6 months. REFERENCES [1] Crişan, et al. (2015) PLoS One, 10, e0120573. [2] Yentes, et al. (2011) Respir Med, 105(1), 80–87. [3] Springer, et al. (2006) Mov Disord, 21(7), 950-957. [4] Pellecchia, et al. (2003) Gait Posture, 18, 29-34. [5] Seimetz, et al. (2012) Biomed Sci Instrum, 48, 386-392. [6] Hausdorff, et al. (2001) Arch Phys Med Rehabil, 82, 1050-1056. Other Contributor Logos Go Here