Multi-sensor assessment of dynamic balance during gait in patients with subacute stroke. (16th August 2017)

• Record Type: Journal Article
• Authors: Bergamini, Elena; Iosa, Marco; Belluscio, Valeria; Morone, Giovanni; Tramontano, Marco; Vannozzi, Giuseppe
• Is Part Of: Journal of biomechanics. Volume 61(2017)
• Page Start: 208
• Page End: 215
• Publication Date: 2017-08-16
• Subjects: Stroke -- Gait stability -- Acceleration -- Inertial sensors -- Locomotion -- Fall risk; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2017.07.034
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: The capacity to maintain upright balance by minimising upper body oscillations during walking, also referred to as gait stability, has been associated with a decreased risk of fall. Although it is well known that fall is a common complication after stroke, no study considered the role of both trunk and head when assessing gait stability in this population. The primary aim of this study was to propose a multi-sensor protocol to quantify gait stability in patients with subacute stroke using gait quality indices derived from pelvis, sternum, and head accelerations. Second, the association of these indices with the level of walking ability, with traditional clinical scale scores, and with fall events occurring within the six months after patients' dismissal was investigated. The accelerations corresponding to the three abovementioned body levels were measured using inertial sensors during a 10-Meter Walk Test performed by 45 inpatients and 25 control healthy subjects. A set of indices related to gait stability were estimated and clinical performance scales were administered to each patient. The amplitude of the accelerations, the way it is attenuated/amplified from lower to upper body levels, and the gait symmetry provide valuable information about subject-specific motor strategies, discriminate between different levels of walking ability, and correlate with clinical scales. In conclusion, the proposed multi-sensor protocol could represent a useful tool to quantify gait stability, support clinicians in the identification of patients potentially exposed to a high risk of falling, and assess the effectiveness of rehabilitation protocols in the clinical routine.