Luckhurst Jim, Hughes Cara, Shelley Benjamin
School of Medicine, University of Glasgow, Glasgow, UK.
Clinical Research Fellow, Academic Unit of Anaesthesia, Critical Care and Peri-operative Medicine, University of Glasgow, Glasgow, UK.
BMC Sports Sci Med Rehabil. 2024 Oct 10;16(1):212. doi: 10.1186/s13102-024-00991-6.
The development of readily available wearable accelerometers has enabled clinicians to objectively monitor physical activity (PA) remotely in the community, a superior alternative to patient self-reporting measures. Critical to the value of these monitors is the ability to reliably detect when patients are undergoing ambulatory activity. Previous studies have highlighted the strength of using mean amplitude deviation (MAD) as a universal measure for analysing raw accelerometery data and defining cut-points between sedentary and ambulatory activities. Currently however there is little evidence surrounding the use of chest-worn accelerometers which can provide simultaneous monitoring of other physiological parameters such as heart rate (HR), RR intervals, and Respiratory Rate alongside accelerometery data. We aimed to calibrate the accelerometery function within the VivaLink ECG patch to determine the cut-point MAD value for differentiating sedentary and ambulatory activities.
We recruited healthy volunteers to undergo a randomised series of 9 activities that simulate typical free-living behaviours, while wearing a VivaLink ECG Patch (Campbell, California). MAD values were applied to a Generalised Linear Mixed Model to determine cut-points between sedentary and ambulatory activities. We constructed a Receiver Operating Characteristic (ROC) curve to analyse the sensitivity and specificity of the cut-off MAD value.
Eighteen healthy adults volunteered to the study and mean MAD values were collected for each activity. The optimal MAD cut-point between sedentary and ambulatory activities was 47.73mG. ROC curve analysis revealed an area under the curve of 0.99 (p < 0.001) for this value with a sensitivity and specificity of 98% and 100% respectively.
In conclusion, the MAD cut-point determined in our study is very effective at categorising sedentary and ambulatory activities among healthy adults and may be of use in monitoring PA in the community with minimal burden. It will also be useful for future studies aiming to simultaneously monitor PA with other physiological parameters via chest worn accelerometers.
便捷的可穿戴式加速度计的发展使临床医生能够在社区中客观地远程监测身体活动（PA），这是一种优于患者自我报告测量的方法。这些监测器的价值关键在于能够可靠地检测患者何时进行动态活动。先前的研究强调了使用平均幅度偏差（MAD）作为分析原始加速度计数据以及定义久坐和动态活动之间切点的通用指标的优势。然而，目前关于使用可同时监测其他生理参数（如心率（HR）、RR间期和呼吸频率）以及加速度计数据的胸部佩戴式加速度计的证据很少。我们旨在校准VivaLink心电图贴片内的加速度计功能，以确定区分久坐和动态活动的切点MAD值。
我们招募了健康志愿者，让他们在佩戴VivaLink心电图贴片（加利福尼亚州坎贝尔）的同时，随机进行一系列9种模拟典型自由生活行为的活动。将MAD值应用于广义线性混合模型，以确定久坐和动态活动之间的切点。我们构建了受试者工作特征（ROC）曲线，以分析截断MAD值的敏感性和特异性。
18名健康成年人自愿参与该研究，并收集了每项活动的平均MAD值。久坐和动态活动之间的最佳MAD切点为47.73mG。ROC曲线分析显示，该值的曲线下面积为0.99（p < 0.001），敏感性和特异性分别为98%和100%。
总之，我们研究中确定的MAD切点在对健康成年人的久坐和动态活动进行分类方面非常有效，并且可能有助于在社区中以最小的负担监测身体活动。它对于未来旨在通过胸部佩戴式加速度计同时监测身体活动和其他生理参数的研究也将是有用的。
