Wearable Sensors for Postural Stability and Fall Risk Analyses: 2nd Edition

Dear Colleagues,

Recent advances in wearable sensor technology have demonstrated the ability to collect objective measurements of postural stability outside the laboratory. Wearable sensors are small, low-cost, and require less time than force-plate or kinematic analysis systems. Previous studies have shown the validity of wearable sensors in quantifying postural stability during dynamic and static postural control tasks, as well as fall risk analysis. In addition to characterizing postural stability, wearable sensors are used for the assessment of training and effective training methods within technology-based approaches, especially in the area of rehabilitation.

In recent years, the rapid proliferation of AI-powered sensors has transformed them from mere data acquisition devices into intelligent decision-making tools. Looking ahead, advancements in sensor technologies, the increasing sophistication of AI-based analytical methods, and the broadening scope of applications are expected to facilitate the development of systems that allow for individuals to assess their posture and balance using AI, thereby effectively mitigating the risk of falls. Accordingly, AI-powered motion analysis systems that not only incorporate wearable sensors, but also non-contact sensing modalities are of particular interest.

The aim of this Special Issue is, therefore, to showcase recent advances, technologies, solutions, applications, and challenges in the field of postural control and motor learning. This Special Issue welcomes research addressing older adults and neurological disorders, as well as healthy subjects and sports athletes. We welcome the submission of original research, reviews, case reports, and short articles, among other paper formats.

Prof. Dr. Tadayoshi Asaka
Dr. Hiroki Mani
Guest Editors

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