Modelling locomotion periods and cadence distribution in daily life: how many days are required?

Soltani, Abolfazl; Dejnabadi, H.; Fasel, Benedikt; Ionescu, Anisoara; Gubelmann, Cédric; Marques‐Vidal, Pedro; Vollenweider, Péter; Aminian, Kamiar

doi:10.1016/j.gaitpost.2017.08.030

Cited by 1 publication

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“…From the 2809 subjects, ~ 98% had at least eight valid days, thus including both weekdays and weekend day(s). This number was large enough for the estimation of preferred gait speed and related metrics 35 , 36 . The characteristics of the participants included and excluded are reported in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

Real-world gait speed estimation, frailty and handgrip strength: a cohort-based study

Soltani

Abolhassani

Marques‐Vidal

et al. 2021

Sci Rep

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Gait speed is a reliable outcome measure across multiple diagnoses, recognized as the 6th vital sign. The focus of the present study was on assessment of gait speed in long-term real-life settings with the aim to: (1) demonstrate feasibility in large cohort studies, using data recorded with a wrist-worn accelerometer device; (2) investigate whether the walking speed assessed in the real-world is consistent with expected trends, and associated with clinical scores such as frailty/handgrip strength. This cross-sectional study included n = 2809 participants (1508 women, 1301 men, [45–75] years old), monitored with a wrist-worn device for 13 consecutive days. Validated algorithms were used to detect the gait bouts and estimate speed. A set of metrics were derived from the statistical distribution of speed of gait bouts categorized by duration (short, medium, long). The estimated usual gait speed (1–1.6 m/s) appears consistent with normative values and expected trends with age, gender, BMI and physical activity levels. Speed metrics significantly improved detection of frailty: AUC increase from 0.763 (no speed metrics) to 0.798, 0.800 and 0.793 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Similarly, speed metrics also improved the prediction of handgrip strength: AUC increase from 0.669 (no speed metrics) to 0.696, 0.696 and 0.691 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Forward stepwise regression showed that the 95th percentile speed of gait bouts with medium duration (30–120 s) to be the best predictor for both conditions. The study provides evidence that real-world gait speed can be estimated using a wrist-worn wearable system, and can be used as reliable indicator of age-related functional decline.

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Section: Resultsmentioning

confidence: 99%