A Similarity Index for Balance Assessment between Older Adults with and without Balance Deficits

Abstract

Falls in older adults can cause disabling health even though falls are largely preventable. A combination of fall risk factors can be modified or predicted to minimize devastating complications. However, clinical balance assessment tools often have contradictory results since fall risks are individualized and multifactorial. The assessment tools are often practically limited to detecting sensitive changes between older adults with and without balance deficits. Recently, a similarity index (SI) has been developed to predict fall risks based on kinematic data during gait. The combined limb motions to those of a prototype derived from healthy individuals in the gait cycle might be differentiated from individuals with gait pathologies. The analyzed calculations result in response vectors that would be compared to controls-derived prototype response vectors. Furthermore, the normalized SI, based on the vector representing the data distribution, could be generated from the enhanced (dis)similarities dataset of subjects following an intervention (prototype response vectors). These quantified indices for compensatory patterns provide a further understanding of optimal injury prevention and specific rehabilitation strategies for older adults with balance deficits. This chapter will propose a novel sensitive measure, the SI, for older adults with orthopedic and neurologic dysfunction compared with control subjects.