Predicting free-living energy expenditure using a miniaturized ear-worn sensor: An evaluation against doubly labeled water

IEEE Transactions on Biomedical Engineering

Volumn 61, Issue 2, 2014, Pages 566-575

  Bouarfa, Loubna ^a   Atallah, Louis ^a   Kwasnicki, Richard Mark ^a   Pettitt, Claire ^a   Frost, Gary ^a   Yang, Guang Zhong ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Energy expenditure (EE); free living environment; multiclass feature selection; nearest neighbor (NN) regression; physical activity assessment; wearable sensing device

Indexed keywords

ENERGY EXPENDITURE; FREE-LIVING ENVIRONMENT; NEAREST NEIGHBORS; PHYSICAL ACTIVITY ASSESSMENTS; WEARABLE SENSING;

ESTIMATION; FORECASTING; MATHEMATICAL MODELS;

SENSORS;

ACCELERATION; ACCELEROMETER; ADULT; ARTICLE; BASAL METABOLIC RATE; BODY MASS; EAR WORN ACCELEROMETER; ENERGY EXPENDITURE; EVALUATION STUDY; FEMALE; HUMAN; MALE; METABOLIC EQUIVALENT; NORMAL HUMAN; PATTERN RECOGNITION; PERFORMANCE; PHYSICAL ACTIVITY; PREDICTION; TRAINING;

ADULT; ENERGY METABOLISM; FEMALE; HUMANS; MALE; METABOLIC EQUIVALENT; MINIATURIZATION; MODELS, STATISTICAL; MONITORING, AMBULATORY; MOTOR ACTIVITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84893269475     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2013.2284069     Document Type: Article

References (38)

1. S. A. McNaughton, D. Crawford, K. Ball, and J. Salmon, "Understanding determinants of nutrition, physical activity and quality of life among older adults: The wellbeing, eating and exercise for a long life (well) study, " Health Qual. Life Outcomes, vol. 10, no. 1, pp. 109-116, 2012.
2. S. N. Blair, E. Horton, A. S. Leon, I. Lee, B. L. Drinkwater, R. Dishman, M. Mackey, M. L. Kienholz et al., "Physical activity, nutrition, and chronic disease, " Med. Sci. Sports Exerc., vol. 28, no. 3, pp. 335-349, 1996. (Pubitemid 26082554)
3. Working for health (2013, Feb. 14). [online]. Available: http://www.who.int
4. R. A. Tanhoffer, A. I. P. Tanhoffer, J. Raymond, A. P. Hills, and G. M. Davis, "Comparison of methods to assess energy expenditure and physical activity in people with spinal cord injury, " J. Spinal Cord Med., vol. 35, no. 1, pp. 35-45, 2012.
5. L. Atallah, J. J. Leong, B. Lo, and G. Z. Yang, "Energy expenditure prediction using a miniaturized ear-worn sensor." Med. Sci. Sports Exerc., vol. 43, no. 7, pp. 1369-1377, 2011.
6. T. Preston, W. Baltzer, and S. Trost, "Accelerometer validity and placement for detection of changes in physical activity in dogs under controlled conditions on a treadmill, " Res. Veterin. Sci., vol. 93, no. 1, pp. 412-416, 2012.
7. Y. Kurihara, K. Watanabe, and M. Yoneyama, "Estimation of walking exercise intensity using 3-d acceleration sensor, " IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 42, no. 4, pp. 495-500, 2012.
8. G. E. Duncan, J. L., S. Migotsky, J. Goh, L. Higgins, and G. Borriello, "Accuracy of a novel multi-sensor board for measuring physical activity and energy expenditure, " Eur. J. Appl. Physiol., vol. 111, no. 9, pp. 2025-2032, 2011.
9. S. Liu, R. X. Gao, D. John, J. Staudenmayer, and P. S. Freedson, "Svm-based multi-sensor fusion for free-living physical activity assessment, " in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2011, pp. 3188-3191.
10. S. Heiermann, K. H. K., M. J. Müller, and M. Dittmar, "Accuracy of a portable multisensor body monitor for predicting resting energy expenditure in older people: A comparison with indirect calorimetry, " Gerontology, vol. 57, no. 5, pp. 473-479, 2011.
11. C. Raffaelli, C. Galvani, M. Lanza, and P. Zamparo, "Different methods for monitoring intensity during water-based aerobic exercises, " Eur. J. Appl. Physiol., vol. 112, no. 1, pp. 125-134, 2012.
12. A. S. Brazeau, A. D. Karelis, D. Mignault, M. J. Lacroix, D. Prud'homme, and R. Rabasa-Lhoret, "Accuracy of the SenseWear armband during er-gocycling, " Int. J. Sports Med., vol. 32, no. 10, pp. 761-764, Oct. 2011. [online]. Available: http://europepmc.org/abstract/MED/21913157
13. M. Soric, P. Mikulic, M. Misigoj-Durakovic, L. Ruzic, and G. Markovic, "Validation of the sensewear armband during recreational in-line skating, " Eur. J. Appl. Physiol., vol. 112, no. 3, pp. 1183-1188, 2012.
14. D. Mungúia-Izquierdo, A. Santalla, and A. Legaz-Arrese, "Evaluation of a wearable body monitoring device during treadmill walking and jogging in patients with fibromyalgia syndrome, " Arch. Phys. Med. Rehabil., vol. 93, no. 1, pp. 115-122, 2012.
15. S. I. de Vries, M. Engels, and F. G. Garre, "Identification of childrens activity type with accelerometer-based neural networks, " Med. Sci. Sports Exerc., vol. 43, no. 10, pp. 1994-1999, 2011.
16. R. Capanna and M. Basilico, "Energy cost in children: Validation of sensewear/armband-swa compared to indirect calorimetry, " in Proc. Hormone Res. Paediatr. Conf.: 50th Annu. Meet. Eur. Soc. Paediatr. En-docrinol., 2011, pp. 76-77.
17. D. Arvidsson, M. Fitch, M. L. Hudes, C. Tudor-Locke, and S. E. Fleming, "Accelerometer response to physical activity intensity in normal-weight versus overweight African American children, " J. Phys. Activity Health, vol. 8, no. 5, pp. 682-693, 2011.
18. S. E. Crouter, M. Horton, and D. R. Bassett, "Use of a two-regression model for estimating energy expenditure in children, " Med. Sci. Sports Exerc., vol. 44, no. 6, pp. 1177-1185, 2012.
19. S. Härtel, J. P. Gnam, S. Löffler, and K. Bös, "Estimation of energy expenditure using accelerometers and activity-based energy models-Validation of a new device, " Eur. Rev. Aging Phys. Activity, vol. 8, no. 2, pp. 1-6, 2010.
20. S. V. Hiremath and D. Ding, "Evaluation of activity monitors in manual wheelchair users with paraplegia, " J. Spinal Cord Med., vol. 34, no. 1, pp. 110-117, 2011.
21. S. A. Moore, K. Hallsworth, L. J. C. Bluck, G. A. Ford, L. Rochester, and M. I. Trenell, "Measuring energy expenditure after stroke validation of a portable device, " Stroke, vol. 43, no. 6, pp. 1660-1662, 2012.
22. T. Wyss and U. Mader, "Energy expenditure estimation during daily military routine with body-fixed sensors, " Military Med., vol. 176, no. 5, pp. 494-499, 2011.
23. O. R. Pearson, M. E. Busse, R. W. M. Van Deursen, and C. M. Wiles, "Quantification of walking mobility in neurological disorders, " Q. J. Med., vol. 97, no. 8, pp. 463-475, 2004. (Pubitemid 39144594)
24. F. K. Assah, U. Ekelund, S. Brage, A. Wright, J. C. Mbanya, and N. J. Wareham, "Accuracy and validity of a combined heart rate and motion sensor for the measurement of free-living physical activity energy expenditure in adults in Cameroon, " Int. J. Epidemiol., vol. 40, no. 1, pp. 112-120, 2011.
25. C. E. Rodes, S. N. Chillrud, W. L. Haskell, S. S. Intille, F. Albinali, and M. Rosenberger, "Predicting adult pulmonary ventilation volume and wearing compliance by on-board accelerometry during personal level exposure assessments, " Atmos. Environ., vol. 57, pp. 126-137, 2012.
26. L. Atallah, B. Lo, R. King, and G. Z. Yang, "Sensor positioning for activity recognition using wearable accelerometers, " IEEE Trans. Biomed. Circuits Syst., vol. 5, no. 4, pp. 320-329, Aug. 2011.
27. H. Vathsangam, A. Emken, E. T. Schroeder, D. Spruijt-Metz, and G. S. Sukhatme, "Determining energy expenditure from treadmill walking using hip-worn inertial sensors: An experimental study, " IEEE Trans. Biomed. Eng., vol. 58, no. 10, pp. 2804-2815, Oct. 2011.
28. S. Liu, R. X. Gao, D. John, J. W. Staudenmayer, and P. S. Freedson, "Multisensor data fusion for physical activity assessment, " IEEE Trans. Biomed. Eng., vol. 59, no. 3, pp. 687-696, Mar. 2012.
29. P. S. Freedson, K. Lyden, S. Kozey-Keadle, andJ.Staudenmayer, "Evaluation of artificial neural network algorithms for predicting mets and activity type from accelerometer data: Validation on an independent sample, " J. Appl. Physiol., vol. 111, no. 6, pp. 1804-1812, 2011.
30. U. Ekelund, S. Brage, and N. J. Wareham, "Physical activity in young children, " Lancet, vol. 363, no. 9415, pp. 1163-1164, 2004.
31. B. Lo, G. Z. Yang, and J. Pansiot, "Bayesian analysis of sub-plantar ground reaction force with BSN, " in Proc. IEEE 6th Int. Workshop Wearable Implant. Body Sens. Netw., 2009, pp. 133-137.
32. D. A. Schoeller and C. R. Fjeld, "Human energy metabolism: What have we learned from the doubly labeled water method?" Annu. Rev. Nutrit., vol. 11, no. 1, pp. 355-373, 1991. (Pubitemid 21903834)
33. R. P. W. Duin, P. Juszczak, P. Paclik, E. Pekalska, D. de Ridder, D. M. J. Tax, S. Verzakov, "PRTools4.1, A Matlab Toolbox for Pattern Recognition, " Delft University of Technology, 2007.
34. K. Van Laerhoven and H. W. Gellersen, "Spine versus porcupine: A study in distributed wearable activity recognition, " in Proc. 8th Int. Symp. Wearable Comput., 2004, vol. 1, pp. 142-149. (Pubitemid 40701063)
35. U. Maurer, A. Smailagic, D. Siewiorek, and M. Deisher, "Activity recognition and monitoring using multiple sensors on different body positions, " in Proc. Int. Workshop Wearable Implantable Body Sens. Netw., 2006, pp. 4-116.
36. N. Kern, B. Schiele, and A. Schmidt, "Multi-sensor activity context detection for wearable computing, " in Ambient Intelligence. New York, NY, USA: Springer-Verlag, 2003, pp. 220-232. (Pubitemid 137631976)
37. Y. Guo, W. He, and C. Gao, "Human activity recognition byfusing multiple sensor nodes in the wearable sensor systems, " J. Mech. Med. Biol., vol. 12, no. 5, 2012.
38. P. Zappi, C. Lombriser, T. Stiefmeier, E. Farella, D. Roggen, L. Benini, and G. Tröster, "Activity recognition from on-body sensors: Accuracy-power trade-off by dynamic sensor selection, " in Wireless Sensor Networks. New York, NY, USA: Springer-Verlag, 2008, pp. 17-33.