Bakrania Kishan, Yates Thomas, Rowlands Alex V, Esliger Dale W, Bunnewell Sarah, Sanders James, Davies Melanie, Khunti Kamlesh, Edwardson Charlotte L
Department of Health Sciences, University of Leicester, Leicester General Hospital, Leicester, Leicestershire, United Kingdom.
Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, Leicestershire, United Kingdom.
PLoS One. 2016 Oct 5;11(10):e0164045. doi: 10.1371/journal.pone.0164045. eCollection 2016.
(1) To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and (2) to compare and evaluate the performances between the ENMO and MAD metrics.
Thirty-three adults [mean age (standard deviation (SD)) = 27.4 (5.9) years; mean BMI (SD) = 23.9 (3.7) kg/m2; 20 females (60.6%)] wore four accelerometers; an ActiGraph GT3X+ and a GENEActiv on the right hip; and an ActiGraph GT3X+ and a GENEActiv on the non-dominant wrist. Under laboratory-conditions, participants performed 16 different activities (11 sedentary behaviours and 5 light-intensity physical activities) for 5 minutes each. ENMO and MAD were computed from the raw acceleration data, and logistic regression and receiver-operating-characteristic (ROC) analyses were implemented to derive thresholds for activity discrimination. Areas under ROC curves (AUROC) were calculated to summarise performances and thresholds were assessed via executing leave-one-out-cross-validations.
For both hip and wrist monitor placements, in comparison to the ActiGraph GT3X+ monitors, the ENMO and MAD values derived from the GENEActiv devices were observed to be slightly higher, particularly for the lower-intensity activities. Monitor-specific hip and wrist ENMO and MAD thresholds showed excellent ability for separating sedentary behaviours from motion-based light-intensity physical activities (in general, AUROCs >0.95), with validation indicating robustness. However, poor classification was experienced when attempting to isolate standing still from sedentary behaviours (in general, AUROCs <0.65). The ENMO and MAD metrics tended to perform similarly across activities and accelerometer brands.
Researchers can utilise these robust monitor-specific hip and wrist ENMO and MAD thresholds, in order to accurately separate sedentary behaviours from common motion-based light-intensity physical activities. However, caution should be taken if isolating sedentary behaviours from standing is of particular interest.
(1)利用从髋部和腕部佩戴的三轴加速度计收集的原始加速度数据,制定并进行内部验证欧几里得范数减一(ENMO)和平均幅度偏差(MAD)阈值,以区分久坐行为和常见的低强度身体活动;(2)比较和评估ENMO和MAD指标的性能。
33名成年人[平均年龄(标准差)=27.4(5.9)岁;平均体重指数(标准差)=23.9(3.7)kg/m²;20名女性(60.6%)]佩戴四个加速度计;右髋部佩戴一个ActiGraph GT3X+和一个GENEActiv;非优势手腕佩戴一个ActiGraph GT3X+和一个GENEActiv。在实验室条件下,参与者进行16种不同的活动(11种久坐行为和5种低强度身体活动),每种活动持续5分钟。从原始加速度数据计算ENMO和MAD,并进行逻辑回归和受试者工作特征(ROC)分析,以得出活动区分阈值。计算ROC曲线下面积(AUROC)以总结性能,并通过执行留一法交叉验证评估阈值。
对于髋部和腕部监测器的放置,与ActiGraph GT3X+监测器相比,观察到从GENEActiv设备得出的ENMO和MAD值略高,特别是对于较低强度的活动。特定监测器的髋部和腕部ENMO和MAD阈值显示出将久坐行为与基于运动的低强度身体活动区分开来的卓越能力(一般来说,AUROC>0.95),验证表明其稳健性。然而,在试图将静止站立与久坐行为区分开时,分类效果较差(一般来说,AUROC<0.65)。ENMO和MAD指标在不同活动和加速度计品牌中的表现往往相似。
研究人员可以利用这些针对特定监测器的稳健的髋部和腕部ENMO和MAD阈值,以便准确地将久坐行为与常见的基于运动的低强度身体活动区分开来。然而,如果特别关注将久坐行为与站立区分开,则应谨慎。