Chapter Six - Digital gait and balance measures

Abstract

New technologies can quickly and accurately quantify hundreds of gait and balance impairments during both prescribed tasks (active monitoring) and during daily life (passive monitoring). Functional mobility requires neural control of several domains that are impaired by movement disorders: (1) Gait; (2) Automatic Postural Responses (APRs), (3) Anticipatory Postural Adjustments (APAs), and (4) Postural Sway during stance. In addition, gait, itself, is composed of several different components (pace, timing, asymmetry, variability, dynamic postural stability, and turning). Each mobility domain and each gait component are supported by different neural networks, affected by different movement disorders and responsive to different treatments. Selecting the appropriate objective mobility outcome(s) for a particular clinical and/or research purpose depends on the purpose of the mobility outcome(s) and the relative importance of the statistical characteristics of those metrics for a particular type of movement disorder. Neural control of turning is more challenging than straight walking so may be more sensitive to impairments by movement disorders. Movement disorders often affect the automaticity of gait, increasing gait variability, impairing the ability to dual-task while walking and increasing prefrontal activity while walking. There are potential benefits for measuring the quality of gait and turning during daily life with body-worn sensors, but also quite a few outstanding challenges that must be better resolved before widespread use for clinical trials and clinical practice.