Examination of wrist and hip actigraphy using a novel sleep estimation procedure

Abstract

ObjectiveImproving and validating sleep scoring algorithms for actigraphs enhances their usefulness in clinical and research applications. The MTI® device (ActiGraph, Pensacola, FL) had not been previously validated for sleep. The aims were to (1) compare the accuracy of sleep metrics obtained via wrist- and hip-mounted MTI® actigraphs with polysomnographic (PSG) recordings in a sample that included both normal sleepers and individuals with presumed sleep disorders; and (2) develop a novel sleep scoring algorithm using spline regression to improve the correspondence between the actigraphs and PSG.MethodsOriginal actigraphy data were amplified and their pattern was estimated using a penalized spline. The magnitude of amplification and the spline were estimated by minimizing the difference in sleep efficiency between wrist- (hip-) actigraphs and PSG recordings. Sleep measures using both the original and spline-modified actigraphy data were compared to PSG using the following: mean sleep summary measures; Spearman rank-order correlations of summary measures; percent of minute-by-minute agreement; sensitivity and specificity; and Bland–Altman plots.ResultsThe original wrist actigraphy data showed modest correspondence with PSG, and much less correspondence was found between hip actigraphy and PSG. The spline-modified wrist actigraphy produced better approximations of interclass correlations, sensitivity, and mean sleep summary measures relative to PSG than the original wrist actigraphy data. The spline-modified hip actigraphy provided improved correspondence, but sleep measures were still not representative of PSG.DiscussionThe results indicate that with some refinement, the spline regression method has the potential to improve sleep estimates obtained using wrist actigraphy.

Use of Tablet Devices in the Management of Agitation Among Inpatients with Dementia: An Open-Label Study

“…It also demonstrates that use of such technology can add a dimension to clinical diagnostics that was not previously readily available. While there are limitations to using commercially available wristworn devices for monitoring motion and sleep in older adults, including the fact these may not be as accurate as polysomnography (28,29), and that information on the steps taken still needs validation and context based on observational data, this case report provides context for how these devices may add a dimension to clinical care, as a result of maturation of the technology involved and availability of immediately visible processed data.…”

Comparison of Accelerometry Methods for Estimating Physical Activity

“…Compliance may be higher with wrist placement, but some wrist-based algorithms appear to be less accurate in classifying activity (7). Another reason to consider the wrist placement for 24 hour activity monitoring is because it has been shown to provide a better approximation of patterns of polysomnography-defined sleep than the hip location (21), although few studies have attempted to use the hip location for sleep assessment or improve sleep estimates based on hip wear (16). …”

Pediatric Videosomnography: Can Signal/Video Processing Distinguish Sleep and Wake States?

“…For example, Mantua et al ( 35 ) assessed agreement between PSG and several actigraphy devices and reported high correlations for many of their comparisons; however, as the current study demonstrates, high correlations do not equate high agreement. Finally, the placement of our actigraph device (ankle band) may have influenced our results because at least one previous study documented the highest agreement between actigraphy and PSG with a wrist placement ( 36 ). However, clinical recommendations for actigraphy placement in young children include the ankle ( 23 ).…”