Institute for Data Science and AI, University of Exeter, Exeter EX4 4QJ, UK.
Sports and Health Sciences, University of Exeter, Exeter EX1 2LU, UK.
Sensors (Basel). 2023 May 27;23(11):5122. doi: 10.3390/s23115122.
Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83-0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53-0.68 and 0.55, 95% CI 0.46-0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32-0.74). We have validated a digital susceptibility/risk biomarker-pfSTEP-that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.
步幅和步频的测量是可穿戴设备（如加速度计）常见的输出结果。有人提出，生物医学技术，包括加速度计及其算法，应该经过严格的验证以及分析和临床验证，以证明其符合特定目的。本研究旨在使用 V3 框架评估由 GENEActiv 加速度计和 GENEAcount 计步算法组成的手腕佩戴式步幅和步频测量系统的分析和临床有效性。分析有效性通过测量手腕佩戴系统与大腿佩戴系统（activPAL，参考测量）之间的一致性水平来评估。临床有效性通过建立步幅和步频变化与身体功能（SPPB 评分）变化之间的前瞻性关联来评估。大腿佩戴参考系统和手腕佩戴系统在总日步数方面的一致性非常好（CCC = 0.88，95%CI 0.83-0.91），在行走步数和快节奏行走步数方面的一致性为中度（CCC = 0.61，95%CI 0.53-0.68 和 0.55，95%CI 0.46-0.64，分别）。总步数和快节奏行走步数越多，与身体功能越好相关。在 24 个月后，每天增加 1000 步快节奏行走与身体功能的临床显著改善相关（0.53 SPPB 评分，95%CI 0.32-0.74）。我们使用手腕佩戴加速度计及其配套的开源计步算法验证了一种数字易感性/风险生物标志物-pfSTEP-可以识别社区居住的老年人身体功能低下的相关风险。
