Further Validation of Actigraphy for Sleep Studies

Souza, Luciane de; Benedito‐Silva, Ana Amélia; Pires, Maria Laura Nogueira; Poyares, Dalva; Tufik, Sérgio; Calil, Helena Maria

doi:10.1093/sleep/26.1.81

Cited by 508 publications

(421 citation statements)

References 9 publications

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“…As discussed in Introduction, the agreement rate (or ÔaccuracyÕ) alone may not fully capture the quality of an actigraphy algorithm, and in fact could result in unrealistically good but misleading outcomes (de Souza et al, 2003). Additional parameters, such as the ones defined above, provide a more comprehensive evaluation of the performance and trade-offs inherent in actigraphy algorithms.…”

Section: Metrics For Evaluation Of Actigraphy Algorithmsmentioning

confidence: 99%

“…Many studies use the agreement rate (defined as ÔaccuracyÕ in the next section) to compare the quality of an actigraphy algorithm against the reference PSG. However, as discussed in de Souza et al (2003), accuracy alone may provide misleading conclusions. For example, in studies with healthy subjects who have normal night sleep, even if the whole night of actigraphy recording is scored as sleep without detecting any wake epoch, one can get accuracy as high as 92% as pointed out in Sadeh et al (1989).…”

Section: Introductionmentioning

confidence: 99%

“…For example, in studies with healthy subjects who have normal night sleep, even if the whole night of actigraphy recording is scored as sleep without detecting any wake epoch, one can get accuracy as high as 92% as pointed out in Sadeh et al (1989). Thus evaluation parameters beyond agreement rate, such as sensitivity and specificity (de Souza et al, 2003), must be considered to fully understand the performance of a scoring algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Algorithms for sleep–wake identification using actigraphy: a comparative study and new results

Tilmanne

Urbain

Kothare

et al. 2009

Journal of Sleep Research

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SUMMAR Y The aim of this study was to investigate two new scoring algorithms employing artificial neural networks and decision trees for distinguishing sleep and wake states in infants using actigraphy and to validate and compare the performance of the proposed algorithms with known actigraphy scoring algorithms. The study employed previously recorded longitudinal physiological infant data set from the Collaborative Home Infant Monitoring Evaluation (CHIME) study conducted between 1994 and 1998 [http:// dccwww.bumc.bu.edu/ChimeNisp/Main_Chime.asp; Sleep 26 (1997) 553] at five clinical sites around the USA. The original CHIME data set contains recordings of 1079 infants <1 year old. In our study, we used the overnight polysomnography scored data and ankle actimeter (Alice 3) raw data for 354 infants from this data set. The participants were heterogeneous and grouped into four categories: healthy term, preterm, siblings of SIDS and infants with apparent life-threatening events (apnea of infancy). The selection of the most discriminant actigraphy features was carried out using FisherÕs discriminant analysis. Approximately 80% of all the epochs were used to train the artificial neural network and decision tree models. The models were then validated on the remaining 20% of the epochs. The use of artificial neural networks and decision trees was able to capture potentially nonlinear classification characteristics, when compared to the previously reported linear combination methods and hence showed improved performance. The quality of sleep-wake scoring was further improved by including more wake epochs in the training phase and by employing rescoring rules to remove artifacts. The large size of the database (approximately 337 000 epochs for 354 patients) provided a solid basis for determining the efficacy of actigraphy in sleep scoring. The study also suggested that artificial neural networks and decision trees could be much more routinely utilized in the context of clinical sleep search.

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Section: Metrics For Evaluation Of Actigraphy Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Algorithms for sleep–wake identification using actigraphy: a comparative study and new results

Tilmanne

Urbain

Kothare

et al. 2009

Journal of Sleep Research

View full text Add to dashboard Cite

show abstract

“…Subjects could not have worked regular or rotating shift work within the past 2 years, and they could not have traveled across time zones in the 3 months prior to the experiment. They were required to be in bed for approximately 8 h daily during the week preceding the study, as verified by wrist actigraphy [10] combined with daily diary reports and time-stamped phone records for time to bed and time awake. The Institutional Review Board of the University of Pennsylvania reviewed and approved the study, and each subject gave written informed consent.…”

Section: Study Design and Participantsmentioning

confidence: 99%

Response surface mapping of neurobehavioral performance: Testing the feasibility of split sleep schedules for space operations

et al. 2008

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The demands of sustaining high levels of neurobehavioral performance during space operations necessitate precise scheduling of sleep opportunities in order to best preserve optimal performance. We report here the results of the first split-sleep, dose-response experiment involving a range of sleep/wake scenarios with chronically reduced nocturnal sleep, augmented with a diurnal nap. To characterize performance over all combinations of split sleep in the range studied, we used response surface mapping methodology. Waking neurobehavioral performance was studied in N=90 subjects each assigned to one of 18 sleep regimens consisting of a restricted nocturnal anchor sleep period and a diurnal nap. Psychomotor vigilance task performance and subjective assessments of sleepiness were found to be primarily a function of total time in bed per 24 h regardless of how sleep was divided among nocturnal anchor sleep and diurnal nap periods. Digit symbol substitution task performance was also found to be primarily a function of total time in bed per 24 h; however, accounting for nocturnal sleep duration and nap duration separately provided a small but significant enhancement in the variance explained. The results suggest that reductions in total daily sleep result in a near-linear accumulation of impairment regardless of whether sleep is scheduled as a consolidated nocturnal sleep period or split into a nocturnal anchor sleep period and a diurnal nap. Thus, split sleep schedules are feasible and can be used to enhance the flexibility of sleep/work schedules for space operations involving restricted nocturnal sleep due to mission-critical task scheduling. These results are generally applicable to any continuous industrial operation that involves sleep restriction, night operations, and shift work.

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“…In the past decade, a relatively high performance of sleep/wake detection using actigraphy has been achieved for healthy subjects without sleep disturbances [11], [12], [13], [14]. However, this is not yet the case for subjects with insomnia who have difficulty of falling or maintaining sleep [6], causing increased wake periods and more 'active' sleep epochs.…”

Section: Introductionmentioning

confidence: 99%