Observational Study of 180° Turning Strategies Using Inertial Measurement Units and Fall Risk in Poststroke Hemiparetic Patients

Abstract

ObjectiveWe analyzed spontaneous 180° turning strategies in poststroke hemiparetic patients by using inertial measurement units (IMUs) and the association of turning strategies with risk of falls.MethodsWe included right paretic (RP) and left paretic (LP) post-stroke patients, and healthy controls (HCs) from a physical and rehabilitation department in France between July 2015 and October 2015. All subjects were right-handed and right-footed for mobilization tasks. Participants were instructed to turn 180° in a self-selected direction after a 10-m walk while wearing three IMUs on their trunk and both feet. We defined three turning patterns based on the number of external steps (pattern I = 1; II = 2–4 steps; and III ≥ 5) and four turning strategies based on the side chosen to turn (healthy or paretic) and the stance limb used during the first step of the turn (healthy or paretic). Falls in the 6 months after measurement were investigated.ResultsWe included 17 RP [mean (SD) age 57.5 (9.5) years (range 43–73)], 20 LP patients [mean age 60.7 (8.8) years (range 43–63)], and 15 HCs [mean age 56.7 (16.1) years (range 36–83)]. The LP and RP groups behaved similarly in turning patterns, but 90% of LP patients turned spontaneously to the paretic side versus 59% of RP patients. This difference increased with turning strategies: 85% of LP versus 29% of RP patients used strategy 4 (paretic turn side with paretic limb). Patients using strategy 4 had the highest rate of falls.ConclusionWe propose to consider spontaneous turning strategies as new indicators to evaluate the risk of fall after stroke. IMU could be routinely used to identify this risk and guide balance rehabilitation programs.

Can We Accurately Measure Axial Segment Coordination during Turning Using Inertial Measurement Units (IMUs)?

“…The ICC demonstrates a value from zero (which implies no agreement) to one (which implies perfect agreement). Furthermore, paired t-tests were used to compare the means of all axial segment movement parameters and stepping parameters obtained using the two systems, which included: reorientation onset of head (1), thorax (2) and feet (3,4), head and thorax end-time (5, 6), peak head yaw velocity (7), peak head-thorax separation angle (8), total step (9), turn duration (10), step frequency (11) and step size (12). All mean values are presented with SD unless stated otherwise.…”

“…The measurement of movements other than level walking are key in the assessment of individuals with neurological impairments. One such movement is turning, which is frequently used as part of routine clinical assessments and includes "turn 180 • " and "turn 360 • ", which have been used in the assessment of falls risk in the elderly [12], and movement disorders including Stroke Survivors [13] and in people with Parkinson's Disease [14]. Therefore, the aim of this study is to validate the use of IMUs to examine turning characteristics in healthy participants by comparing IMU data to data generated by a Vicon motion analysis system.…”

Comparison of 360° Turn Cycles among Individuals after Stroke and Healthy Older Adults

“…Specifically, turning among stroke survivors is compromised by either declined sensorimotor function [7] or slower self-paced movement speed [8]; however, comparative studies on kinematic analysis while turning among stroke survivors and healthy controls are lacking. Bonnyaud et al investigated turning in the Timed Up and Go (TUG) task with respect to spatiotemporal and kinematic parameters associated with stroke [9,10], and few other studies reported turning phases using inertial sensors for 180 • turning [11,12]. Bonnyaud et al reported that movement speed, cadence, and step length were reduced on both the paretic and non-paretic side among individuals after stroke during TUG.…”

Value of gait analysis for measuring disease severity using inertial sensors in patients with multiple sclerosis: protocol for a systematic review and meta-analysis

“…Motion capture systems based on these wearable sensors have become widely used for the biomechanical analysis of human movement. InertiaLocoGraphy (ILG), the quantification of gait with IMUs, was first reported 70 years ago [10] and has now been implemented in a wide range of neurological and non-neurological diseases [11, 12]. It can be used both at the hospital, mainly for short tests, and at home for more long-term physiological gait assessment [13].…”