A comparison of gait stability between younger and older adults while head turning

Sensor-Based Multifaceted Feature Extraction and Ensemble Elastic Net Approach for Assessing Fall Risk in Community-Dwelling Older Adults

Accurate identification of community-dwelling older adults at high fall risk can facilitate timely intervention and significantly reduce fall incidents. Analyzing gait and balance capabilities via feature extraction and modeling through sensor-based motion data has emerged as a viable approach for fall risk assessment. However, the existing approaches for extracting key features related to fall risk lack inclusiveness, with limited consideration of the non-linear characteristics of sensor signals, such as signal complexity, self-similarity, and local stability. In this study, we developed a multifaceted feature extraction scheme employing diverse feature types, including demographic, descriptive statistical, non-linear, spatiotemporal and spectral features, derived from three-axis accelerometers and gyroscope data. This study is the first attempt to investigate non-linear features related to fall risk in multi-task scenarios from a dynamic system perspective. Based on the extracted multifaceted features, we propose an ensemble elastic net (E-E-N) approach for handling imbalanced data and offering high model interpretability. The E-E-N utilizes bootstrap sampling to construct base classifiers and employs a weighting mechanism to aggregate the base classifiers. We conducted a set of validation experiments using real-world data for comprehensive comparative analysis. The results demonstrate that the E-E-N approach exhibits superior predictive performance on fall risk classification. Our proposed approach offers a cost-effective tool for accurately assessing fall risk and alleviating the burden of continuous health monitoring in the long term.

Effects of age on dynamic balance measures and their correlation during walking across the adult lifespan

In this study, we aimed to discover (1) the effects of age on dynamic balance measures, including the margin of stability (MOS), whole-body angular momentum (H), and misalignment of the desired and measured centers of pressure (dCOP and mCOP, respectively) in the anteroposterior (AP) and mediolateral (ML) directions, (2) the relationship between gait parameters and these balance measures, and (3) the relationships between these balance measures. We used the kinetic and kinematic data of 151 participants aged 20–77 years from a publicly available database. Participants were divided into three groups: young, middle-aged, and old. The step width of the old group was higher than that of the young group. Age-related differences in dynamic measures were found in the ML direction and not in the AP direction: MOS, peak-to-peak range of H, and dCOP–mCOP in the old group were greater than in the young group. ML MOS positively correlated with the frontal peak-to-peak range of H. The ML peak-to-peak range of H positively correlated with ML dCOP–mCOP across the adult lifespan. Our findings provide new insights for understanding the effects of age on dynamic balance and the relationships between the metrics. Older adults walked with a larger step width, resulting in a large stability margin in the ML direction, although with increased moment and momentum around the center of mass in the frontal plane.

Basic Spatiotemporal Gait Variables of Young and Older Healthy Volunteers Walking Along a Novel Figure-of-8 Path

Background: Locomotion along curved trajectories requires fine coordination among body segments. Elderly people may adopt a cautious attitude when steering. A simple, expeditious, patient-friendly walking protocol can be a tool to help clinicians. We evaluated the feasibility of a procedure based upon a newly designed Figure-of-eight (nFo8) path and an easy measurement operation. Methods: Sixty healthy volunteers, aged from 20 to 86 years, walked three times at self-selected speed along a 20 m linear (LIN) and the 20 m nFo8 path. Number of steps, mean speed and walk ratio (step length/cadence) were collected. Data were analysed for the entire cohort and for the groups aged 20-45, 46-65, and >65 years. Results: There was no difference in mean LIN walking speed between the two younger groups but the oldest was slower. During nFo8, all groups were slower (about 16%) than during LIN. Cadence was not different across groups but lower during nFo8 in each group. Step length was about 8% shorter in the two younger groups and 14% shorter in the oldest during nFo8 compared to LIN. Walk ratio was the smallest in the oldest group for both LIN and nFo8. Conclusions: A complex nFo8 walking path, with fast and easy measurement of a simple set of variables, detects significant differences with moderate and large effects in gait variables in people >65 years. This challenging trajectory is more revealing than LIN. Further studies are needed to develop a quick clinical tool for assessment of gait conditions or outcome of rehabilitative treatments.