Abstract
In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion’s translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.
Highlights
W ALKING has been described as a skill that is acquired through motor learning [1]
We identify the existing gap by seeing how researchers have combined multiple features extracted from gait accelerometry signals into a derived Acceleration gait measures (AGMs) that could potentially be a marker for walking-related changes in physical function
There is a disparity in the literature reviewing the different mapping of AGMs to aspects of motor skill
Summary
W ALKING has been described as a skill that is acquired through motor learning [1]. The hallmark of a motor skill is a smooth and efficient movement that requires minimal attention [1]. Other walking measures that are a better match to specific aspects of motor skill may prove to be useful when evaluating the gait of older adults. One way of making better use of this new data source is to develop metrics that match the motor skills of interest in older adults This endeavor will require a collaborative effort between researchers in geriatrics of mobility and experts in engineering and data analytics. Previous studies found that older adults adopt more conservative gait patterns than younger adults, potentially to compensate for degeneration in physiological systems such as those associated with vision, sensation, and lower limb strength [23], [27] These conservative gait patterns result in reduced walking velocities and accelerations, accompanied by reduced step length and increased step width [23]. The structure of this review paper is divided into six areas, as summarized in Figure 1: motor skill and walking definitions (Figure 1–A1; Section II), accelerometer data collection (Figure 1–B; Section III), signal pre-processing tasks (Figure 1–C; Section III), deriving and categorizing AGMs (Figure 1–D; Section III), mapping the aspects of the motor skill of walking to trunk-AGMs (Figure 1–A2 and D; Section IV), and the applications and future directions of AGMs and motor skill in the clinical space (Figure 1–E1 and E2; Section V)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
