2007
DOI: 10.1111/j.1365-2869.2007.00588.x
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Validation of actigraphy for determining sleep and wake in children with sleep disordered breathing

Abstract: SUMMAR Y There have been limited studies of the validation of actigraphy for the determination of sleep and wake in children and in this study we aimed to compare wrist actigraphy with polysomnography (PSG). We studied 45 children (29 M ⁄ 16 F), aged between 1 and 12 years (5.8 ± 2.7 years, mean ± SD). Actigraphic data were collected during standard overnight PSG. Data from the actiwatch were analysed over four separate activity threshold settings (low, medium, high, auto). Actigraphic data were compared epoch… Show more

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Cited by 137 publications
(127 citation statements)
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“…However, ACT80 and AlgoSmooth decreased the ability of actigraphy to detect wakefulness compared to ACT40. The low specificity (about 60% of PSG wakefulness is scored as wakefulness by actigraphy) observed in our data is similar to that found in previous studies that compared different brands of actigraphy with PSG in infants 14,20 and children, 17,21 highlighting the difficulty of correctly identifying wake with actigraphy. Nevertheless, when the actigraphs scored wake, AlgoSmooth showed higher agreement with PSG (NPV = 76.6%) than the other two algorithms (42.8% and 52.7%), suggesting that AlgoSmooth is better suited for this purpose.…”
Section: Discussionsupporting
confidence: 74%
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“…However, ACT80 and AlgoSmooth decreased the ability of actigraphy to detect wakefulness compared to ACT40. The low specificity (about 60% of PSG wakefulness is scored as wakefulness by actigraphy) observed in our data is similar to that found in previous studies that compared different brands of actigraphy with PSG in infants 14,20 and children, 17,21 highlighting the difficulty of correctly identifying wake with actigraphy. Nevertheless, when the actigraphs scored wake, AlgoSmooth showed higher agreement with PSG (NPV = 76.6%) than the other two algorithms (42.8% and 52.7%), suggesting that AlgoSmooth is better suited for this purpose.…”
Section: Discussionsupporting
confidence: 74%
“…Sitnick et al 19 showed that an algorithm commonly used with adults is too sensitive with a population of young children, resulting in high false negative rates (i.e., actigraphy detects wakefulness when the child is probably sleeping). In fact, although several studies with infants and children have reported that various actigraphy devices are highly correlated (> 80%) with PSG or videosomnography, 14,[16][17][18][19][20][21][22][23] most of these studies have shown very low ability to correctly identify wakefulness 14,17,19,22 and hence, sleep fragmentation. 24 Nevertheless, the American Academy of Sleep Medicine (AASM) states that the use of actigraphy in normal children and special pediatric populations is indicated for the assessment of sleep patterns and response to treatment.…”
mentioning
confidence: 99%
“…The opposite was found when PSG was compared to Fitbit in the sensitive mode. While most actigraphy validation studies discuss an overestimation of WASO in infants and children, 15,16,27 the direction of error in other pediatric 14 and adult studies is not as consistent. [28][29][30] It may be that as children age, the level of movement during sleep not associated with an awakening decreases.…”
Section: Discussionmentioning
confidence: 95%
“…13 Validation studies in infants, children and adolescents have shown that actigraphy is sensitive in assessing actual sleep, however over-or underestimates wake after sleep onset, providing a poor estimate of sleep disruption when compared to PSG. [14][15][16][17] While actigraphy is less expensive, labor-intensive, and more reflective of natural sleep patterns than PSG, it still requires specialized software and expertise to analyze and interpret. 16 A number of commercial devices that claim to assess sleep duration and quality are now available.…”
Section: Introductionmentioning
confidence: 99%
“…Actigraphy is a validated wristwatch-like device that distinguishes sleep from wakefulness based on accelerometer measured movement. 18,19 Caregivers simultaneously completed a daily sleep diary which was used to identify bedtime and wake time, as well as to identify when the device was removed. Data were analyzed and interpreted centrally by a single technologist and a single pediatric sleep medicine specialist, respectively.…”
Section: Actigraphymentioning
confidence: 99%