Skip to main content

Advertisement

Log in

The convergent validity of Actiwatch 2 and ActiGraph Link accelerometers in measuring total sleeping period, wake after sleep onset, and sleep efficiency in free-living condition

  • Epidemiology • Original Article
  • Published:
Sleep and Breathing Aims and scope Submit manuscript

Abstract

Purpose

Physical activity (PA) and sleep are important to health; thus, it is important for researchers to have valid tools to measure them. Accelerometers have been proven valid for measuring PA and sleep, but only one device does this simultaneously: the ActiGraph Link (ActiGraph, LLC); however, the sleep-monitoring function has not been validated. This study aimed to evaluate the predictive power of ActiGraph Link sleep parameters against a validated accelerometer (Actiwatch 2, Phillips Respironics Mini-Mitter).

Methods

A total of 49 Hong Kong adults aged 18–64 provided valid data on both accelerometers on their non-dominant wrist for seven consecutive days. Epochs from both accelerometers were classified as either sleep or awake using seven established algorithms (Cole-Kripke, Sadeh, Sazonov, high sensitivity threshold, medium sensitivity threshold, low sensitivity threshold, and neural network model), and these data were transformed to total sleeping period, wake after sleep onset, and sleep efficiency.

Results

The non-zero count data for both accelerometers (331,103 observations) were strongly correlated with a Spearman correlation of 0.83 (p < 0.001). The total sleeping period was highly correlated (Spearman correlation ranged from 0.74 to 0.90) regardless of the algorithms used. All algorithms yielded insignificant difference in total sleep time measured by the two accelerometers (p > 0.05) with a negligible effect size of d < 0.2. The agreement of sleep/wake status was high for all algorithms, with accuracy ranging from 93.05 % (Sadeh’s algorithm) to 96.13 % (Cole-Kripke’s algorithm).

Conclusions

Results showed that the sleep function of the ActiGraph Link performs similar to a validated accelerometer (Actiwatch 2) and provides an opportunity to measure both sleep and PA simultaneously.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Cappuccio FP, Taggart FM, Kandala NB, Currie A, Peile E, Saverio S, Miller MA (2008) Meta-analysis of short sleep duration and obesity in children and adults. Sleep Biol Rhythms 31:610–626

    Google Scholar 

  2. Knutson KL, Spiegel K, Penev P, Van Cauter E (2007) The metabolic consequences of sleep deprivation. Sleep Med Rev 11(3):163–178

    Article  PubMed  PubMed Central  Google Scholar 

  3. Pedersen BK, Saltin B (2006) Evidence for prescribing exercise as therapy in chronic disease. Scand J Med Sci Sports 16(1 (Suppl)):3–63

    Article  PubMed  Google Scholar 

  4. Roberts CK, Barnard RJ (2005) Effects of exercise and diet on chronic disease. J Appl Physiol 98:3–30

    Article  PubMed  Google Scholar 

  5. Colley RC, Wong SL, Garriguet D, Janssen I, Gorber SC, Tremblay MS (2012) Physical activity, sedentary behavior and sleep in Canadian children: parent-report versus direct measures and relative associations with health risk. Health Rep 45-52(2)

  6. Harrington SA (2013) Relationship of objectively measured physical activity and sleep with BMI and academic outcomes in 8-year-old children. Appl Nurs Res 26:63–70

    Article  PubMed  Google Scholar 

  7. Schutz Y, Weinsier RL, Hunter GR (2006) Assessment of free-living physical activity in humans: an overview of currently available and proposed new measures. Obes Res 9:368–379

    Article  Google Scholar 

  8. Van de Water AT, Holmes A, Hurley DA (2011) Objective measurements of sleep for non-laboratory settings as alternatives to polysomnography—a systematic review. J Sleep Res 20:183–200

    Article  PubMed  Google Scholar 

  9. Pfitzner R, Gorzelniak L, Heinrich J, Von Berg A, Klumper C, Bauer CP, Koletzko S, Berdel D, Horsch A, Schulz H, GINIPlus Study Group (2013) Physical activity in German adolescents measured by accelerometry and activity diary: introducing a comprehensive approach for data management and preliminary results. PLoS One 8(6):e65192

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Meltzer LJ, Walsh CM, Traylor J, Westin AML (2012) Direct comparison of two new actigraphs and polysomnography in children and adolescents. Sleep 35(1):159–166

    PubMed  PubMed Central  Google Scholar 

  11. Stone MR, Stevens D, Faulkner GEJ (2013) Maintaining recommended sleep throughout the week is associated with increased physical activity in children. Prev Med 56:112–117

    Article  PubMed  Google Scholar 

  12. Lambiase MJ, Pettee Gabriel K, Kuller LH, Matthews KA (2013) Temporal relationships between physical activity and sleep in older women. Med Sci Sports Exerc 45(12):2362–2368

    Article  PubMed  Google Scholar 

  13. Hjorth MF, Chaput J-P, Damsgaard CT, Dalskov S-M, Michaelsen KF, Tetens I, Sjodin A (2012) Measure of sleep and physical activity by a single accelerometer: can a waist-worn actigraph adequately measure sleep in children? Sleep Biol Rhythms 10:328–335

    Article  Google Scholar 

  14. Soric M, Turkalj M, Kucic D, Marusic I, Plavec D, Misigoj-Durakovic M (2013) Validation of a multi-sensor activity monitor for assessing sleep in children and adolescents. Sleep Med 14:201–205

    Article  PubMed  Google Scholar 

  15. Colbert LH, Matthews CE, Havighurst TC, Kim K, Schoeller DA (2011) Comparative validity of physical activity measures in older adults. Med Sci Sports Exerc 43(5):867–876

    Article  PubMed  PubMed Central  Google Scholar 

  16. Macfarlane DJ, Lee CCY, Ho EYK, Chan KL, Chan D (2006) Convergent validity of six methods to assess physical activity in daily life. J Appl Physiol 101(1328–1334)

  17. Ridgers ND, Salmon J, Ridley K, O’Connell E, Arundell L, Timperio A (2012) Agreement between activPAL and ActiGraph for assessing children’s sedentary time. Int J Behav Nutr Phys Act 9:15

    Article  PubMed  PubMed Central  Google Scholar 

  18. Sasaki JE, John D, Freedson PS (2011) Validation and comparison of ActiGraph activity monitors. J Sci Med Sport 14(5):411–416

    Article  PubMed  Google Scholar 

  19. Dillman DA, Smyth J, Christian L (2009) Internet, mail, and mixed-mode surveys: the tailored design method, 3rd edn. John Wiley & Sons, Inc, Hoboken, NJ

    Google Scholar 

  20. Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC (1992) Automatic sleep/wake identification from wrist activity. Sleep 15:461–469

    CAS  PubMed  Google Scholar 

  21. Sadeh A, Sharkey KM, Carskadon MA (1994) Activity-based sleep-wake identification: an empirical test of methodological issues. Sleep 17:201–207

    CAS  PubMed  Google Scholar 

  22. Sazonov ES, Sazonova NS, Schuckers SAC, Neuman M, CHIME Study Group (2004) Activity-based sleepwake identification in infants. Physiol Meas 25:1291–1304

    Article  PubMed  Google Scholar 

  23. Tilmanne J, Urbain J, Kothare MV, Wouwer AV, Kothare SV (2009) Algorithms for sleep-wake identification using actigraphy: a comparative study and new results. J Sleep Res 18:85–98

    Article  PubMed  Google Scholar 

  24. Kinder JR, Lee KA, Thompson H, Hicks K, Topp K, Madsen KA (2012) Validation of a hip-worn accelerometer in measuring sleep time in children. J Pediatr Nurs 27:127–133

    Article  PubMed  Google Scholar 

  25. Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, Hillsdale

    Google Scholar 

  26. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  CAS  PubMed  Google Scholar 

  27. Roane BM, Van Reen E, Hart CN, Wing R, Carskadon MA (2015) Estimating sleep from multisensory armband measurements: validity and reliability in teens. J Sleep Res 24(6):714–721

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lee PH, Macfarlane DJ, Lam TH, Stewart SM (2011) Validity of International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act 8:115

    Article  PubMed  PubMed Central  Google Scholar 

  29. Grandner MA, Kripke DF, Yoon IY, Youngstedt SD (2006) Criterion validity of the Pittsburgh Sleep Quality Index: investigation in a non-clinical sample. Sleep Biol Rhythms 4(2):129–139

    Article  PubMed  PubMed Central  Google Scholar 

  30. Cellini N, McDevitt EA, Mednick SC, Buman MP (2016) Free-living cross-comparison of two wearable monitors for sleep and physical activity in healthy young adults. Physiol Behav 157:79–86

    Article  CAS  PubMed  Google Scholar 

  31. Meltzer LJ, Hiruma LS, Avis K, Montgomery-Downs H, Valentin J (2015) Comparison of a commercial accelerometer with polysomnography and actigraphy in children and adolescents. Sleep 38(8):1323–1330

    PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paul H. Lee.

Ethics declarations

Funding

The Food and Health Bureau of the Hong Kong Special Administrative Region, China, provided financial support in the form of Health and Medical Research Fund (Ref 12131741). The sponsor had no role in the design or conduct of this research.

Conflict of interest

The authors declare that they have no competing interests.

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Additional information

Comments:

Obstructive sleep apnoea is both underdiagnosed and undertreated. In regard to the process of diagnosis full overnight sleep studies are costly and require the use of expensive equipment, whereas the home-based studies are more convenient though less accurate. The use of a device such as the ActiGraph Link (ActiGraph, LLC), accelerometer has an advantage both for the provider and patient as it has been demonstrated that this single device is capable of monitoring both the normal levels of daily activity and sleep pattern. Physical inactivity is a major risk factor for people with OSA so having accurate recordings of physical activity will help the health professional to provide an appropriate exercise prescription. If the same device can continue to be worn at night then a 24-h profile of the individual will be possible and trends in improvement in sleep plus physical activity levels monitored with minimal burden on the patient.

Margot Skinner

Dunedin, New Zealand

Electronic supplementary material

Fig S1

(DOC 82 kb)

Fig S2

(DOC 82 kb)

Fig S3

(DOC 82 kb)

Fig S4

(DOC 84 kb)

Fig S5

(DOC 82 kb)

Fig S6

(DOC 82 kb)

Fig S7

(DOC 82 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, P.H., Suen, L.K.P. The convergent validity of Actiwatch 2 and ActiGraph Link accelerometers in measuring total sleeping period, wake after sleep onset, and sleep efficiency in free-living condition. Sleep Breath 21, 209–215 (2017). https://doi.org/10.1007/s11325-016-1406-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11325-016-1406-0

Keywords

Navigation