A review of accelerometer-based physical activity measurement

Lecture Notes in Electrical Engineering

Volumn 120 LNEE, Issue , 2012, Pages 223-237

  Meng, Yao ^a   Kim, Hee Cheol ^a  

^a Inje University   (South Korea)

Author keywords

Accelerometer; Activity detection; Energy expenditure; Healthcare; Physical activity

Indexed keywords

ACTIVITY DETECTION; ENERGY EXPENDITURE; PHYSICAL ACTIVITY;

DATA HANDLING; HEALTH CARE;

ACCELEROMETERS;

EID: 84255177433     PISSN: 18761100     EISSN: 18761119     Source Type: Book Series    
DOI: 10.1007/978-94-007-2911-7_20     Document Type: Conference Paper

References (89)

1. Caspersen CJ, Powell KE, Christenson GM (1985) Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep 100(2):126-131
2. Bouchard C, Blair SN, Haskell W (2007) Physical activity and health, Human kinetics
3. Davis MG, Fox KR (2007) Physical activity patterns assessed by accelerometry in older people. Eur J Appl Physiol 100(5):581-589
4. Schoeller DA (1988) Measurement of energy expenditure in free living humans by using doubly labeled water. J Nutr 118(11):1278-1289
5. Sirard JR, Pate RR (2001) Physical activity assessment in children and adolescents. Sports Med 31(6):439-454
6. Vanhees L et al (2005) How to assess physical activity? How to assess physical fitness. Eur. J. Cardiovasc Prev Rehabil 12(2):102-114
7. Haskell WL, Kiernan M (2000) Methodologic issues in measuring physical activity and physical fitness when evaluating the role of dietary supplements for physically active people. Am J Clin Nutr 72(2):541-550
8. Yang CC, Hsu YL (2010) A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 10(8):7772-7788
9. Plasqui G, Westerterp KR (2007) Physical activity assessment with accelerometers: an evaluation against doubly labeled water. Obesity 15(10):2371-2379
10. Murphy SL (2009) Review of physical activity measurement using accelerometers in older adults: consideration for research design and conduct. Prev Med 48(2):108-114
11. Mathie MJ, Coster AC, Lovell NH, Celler BG (2004) Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol Meas 25(2):R1-R20
12. Chen KY, Bassett DR (2005) The technology of accelerometry-based activity monitors: current and future. Med Sci Sports Exerc 37(11):S490-S500
13. Welk GJ (2005) Principles of design and analysis for the calibration of accelerometry-based activity monitors. Med Sci Sports Exerc 37(11):S501-S511
14. Actigraph LEM (2008) ActiLife users manual. Pensacola, FL
15. Sunnd M, Hill JO (1993) A method for measuring mechanical work and work efficiency during human activities. J Biomech 26(3):229-241
16. Bouten CV et al (1997) A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity. IEEE Trans Biomed Eng 44(3):136-147
17. Oppenheim AV et al (1983) Signals and systems. Prentice Hall, Englewood Cliffs
18. Bouten CV et al (1997) Effects of placement and orientation of body-fixed accelerometers on the assessment of energy expenditure during walking. Med Biol Eng Comput 35(1):50-56
19. Mathie MJ, Basilakis J (2001) A system for monitoring posture and physical activity using accelerometers, Proceedings 23rd International Conference of the IEEE, 25 Oct 2001
20. Foerster F, Fahrenberg J (2000) Motion pattern and posture: correctly assessed by calibrated accelerometers. Behav Res Methods 32(3):450-457
21. Chang M (2006) Review of clinical applications with human accelerometry, ISSN: 0107-8283
22. Mathie MJ et al. (2002) Determining Activity using a Triaxial Accelerometer, Second Joint EMBS/BMES Conference, 23-26 Oct 2002
23. Bouten CV et al (1994) Assessment of energy expenditure for physical activity using a triaxial accelerometer. Med Sci Sports Exerc 26(12):1516-1523
24. Lyden K et al (2011) A comprehensive evaluation of commonly used accelerometer energy expenditure and met prediction equations. Eur J Appl Physiol 111(2):187-201
25. Rothney MP et al (2008) Validity of physical activity intensity predictions by actigraph, actical, and RT3 accelerometers. Obesity 16(8):1946-1952
26. Freedson PS, Melanson E, Sirard J (1998) Calibration of the computer science and applications, Inc. Accelerometer. Med Sci Sports Exerc 30(5):777-781
27. Hendelman D et al (2000) Validity of accelerometry for the assessment of moderate intensity physical activity in the field. Med Sci Sports Exerc 32(9):S442-S449
28. Leenders NY, Nelson TE, Sherman WM (2003) Ability of different physical activity monitors to detect movement during treadmill walking. Int J Sports Med 24(1):43-50
29. Brooks AG et al (2005) Predicting walking mets and energy expenditure from speed or accelerometry. Med Sci Sports Exerc 37(7):1216-1223
30. Swartz AM et al (2000) Estimation of energy expenditure using CSA accelerometers at hip and wrist sites. Med Sci Sports Exerc 32(9):S450-S456
31. Heil DP (2006) Predicting activity energy expenditure using the actical activity monitor. Res Q Exerc Sport 77(1):64-80
32. Klippel NJ, Heil DP (2003) Validation of energy expenditure prediction algorithms in adults using the actical electronic activity monitor. Med Sci Sports Exerc 35(5):S284
33. Crouter SE, Clowers KG, Bassett DR Jr (2006) A novel method for using accelerometer data to predict energy expenditure. J Appl Physiol 100(4):1324-1331
34. Crouter SE, Bassett DR Jr (2008) A new two-regression model for the actical accelerometer. Br J Sports Med 42(3):217-224
35. Crouter SE et al (2010) Refined two-regression model for the actical accelerometer. Med Sci Sports Exerc 42(5):1029-1037
36. Brage S et al (2004) Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure. J Appl Physiol 96(1):343-351
37. Zakeri I et al (2008) Application of cross-sectional time series modeling for the prediction of energy expenditure from heart rate and accelerometry. J Appl Physiol 104(6):1665-1673
38. Staudenmayer J et al (2009) An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer. J Appl Physiol 107(4):1300-1307
39. Bonomi AG et al (2009) Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer. J Appl Physiol 107(3):655-661
40. van Hees VT, Ekelund U (2009) Novel daily energy expenditure estimation by using objective activity type classification: Where do we go from here? J Appl Physiol 107(3):639-640
41. Lester J et al. (2005) A hybrid discriminative/generative approach for modeling human activities, Proceedings 19th International joint Conference on Artificial Intelligence, pp 766-772, Jul 30-Aug 5
42. Parkka J et al (2006) Activity classification using realistic data from wearable sensors. IEEE Trans Inf Technol Biomed 10(1):119-128
43. Ermes M et al (2008) Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions. IEEE Trans Inf Technol Biomed 12(1):20-26
44. Foerster F, Smeja M, Fahrenberg J (1999) Detection of posture and motion by accelerometry: a validation study in ambulatory monitoring. Comput Human Behav 15(5):571-583
45. Bao L, Intille SS (2004) Activity recognition from user-annotated acceleration data, Proceedings Pervasive, LNCS 3001, pp 1-17
46. Pober DM et al (2006) Development of novel techniques to classify physical activity mode using accelerometers. Med Sci Sports Exerc 38(9):1626-1634
47. Mathie MJ et al (2004) Classification of basic daily movements using a triaxial accelerometer. Med Biol Eng Comput 42(5):679-687
48. Karantonis DM et al (2006) Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring. IEEE Trans Inf Technol Biomed 10(1):156-167
49. Veltink PH et al (1996) Detection of static and dynamic activities using uniaxial accelerometers. IEEE Trans Rehabil Eng 4(4):375-385
50. Nishkam R et al. (2005) Activity recognition from accelerometer data," Proceedings 17th conference on IAAI, 3:1541-1546
51. Long X, Yin B, Aarts RM (2009) Single-accelerometer-based daily physical activity classification, Proceedings 31st annual International Conference of the IEEE EMBS, pp 6107-6110
52. Lee M et al. (2009) Physical activity recognition using a single tri-axis accelerometer, Proceedings world congress on Engineering and Computer Science
53. Bonomi AG et al (2009) Detection of type, duration and intensity of physical activity using an accelerometer. Med Sci Sports Exerc 41(9):1770-1777
54. Khan AM et al (2010) A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer. IEEE Trans Inf Technol Biomed 14(5):1166-1172
55. Minnen D et al. (2005) Recognizing and discovering human actions from on-body sensor data, Proceedings IEEE International Conference on Multimedia Expo., pp 1545-1548
56. Mantyjarvi J, Himberg J and Seppanen T, (2001) Recognizing human motion with multiple acceleration sensors, Proceedings IEEE International Conference on System, Man, and Cybernetics, 2: 747-752
57. Allen F et al (2006) Classification of a known sequence of motions and postures from accelerometry data using adapted gaussian mixture models. Physiol Meas 27(10):935-951
58. Sant'Anna A, Wickstrom N (2009) Developing a motion language: gait analysis from accelerometer sensor systems, Proceedings 3rd International Conference on Pervasive Computing Technologies for Healthcare, pp 1-8
59. Zijlstra W (2004) Assessment of spatio-temporal parameters during unconstrained walking. Eur J Appl Physiol 92(1-2):39-44
60. Moe-Nilssen R, Helbostad JL (2004) Estimation of gait cycle characteristics by trunk accelerometry. J. Biomechanics 37(1):121-126
61. Lee SW, Mase K, Kogure K (2005) Detection of spatio-temporal gait parameters by using wearable motion sensors, Proceedings 27th annual International Conference of IEEE EMBS 7: 6836-6839
62. Brandes M et al (2006) Accelerometry based assessment of gait parameters in children. Gait Posture 24(4):482-486
63. Lee JA et al. (2007) Wearable accelerometer system for measuring the temporal parameters of gait, Proceedings 29th annual International Conference of IEEE EMBS, pp 483-486
64. Tura A et al (2010) Gait symmetry and regularity in transfemoral amputees assessed by trunk accelerations. J Neuroeng Rehabil 7:4
65. Bishop E, Li Q (2010) Walking speed estimation using shank-mounted accelerometers, IEEE International Conference on Robotics and Automation, pp 5096-5101
66. Sekine M et al (2000) Classification of waist-acceleration signals in a continuous walking record. Med Eng Phys 22(4):285-291
67. Sekine M et al. (2000) Classification of walking pattern using acceleration waveform in elderly people, Proceedings 22nd Annual International Conference of IEEE EMBS, 2: 1356-1359
68. Ibrahim RK et al. (2007) Time-frequency based features for classification of walking patterns, Proceedings 15th International Conference on Digital Signal Processing, pp 187-190
69. Giansanti D et al (2003) Is it feasible to reconstruct body segment 3-D position and orientation using accelerometric data? IEEE Trans Biomed Eng 50(4):476-483
70. Liu K et al. (2008) novel approach for lower limb segment orientation in gait analysis using triaxial accelerometers, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp 488-492
71. O'Sullivan M et al (2009) Correlation of accelerometry with clinical balance tests in older fallers and non-fallers. Age Ageing 38(3):308-313
72. Kamen G et al (1998) An accelerometry based system for the assessment of balance and postural sway. Gerontology 44(1):40-45
73. Hahn ME et al (2005) Neural network estimation of balance control during locomotion. J Biomech 38(4):717-724
74. Betker AL, Moussavi ZM, Szturm T (2006) Center of mass approximation and prediction as a function of body acceleration. IEEE Trans Biomed Eng 53(4):686-693
75. Betker AL, Szturm T, Moussavi ZM (2009) Estimation of 2-D center of mass movement during trunk flexion-extension movements using body accelerations. IEEE Trans Neural Syst Rehabil Eng 17(6):553-559
76. Giansanti D (2006) Investigation of fall-risk using a wearable device with accelerometers and rate gyroscopes. Physiol Meas 27(11):1081-1090
77. Giansanti D et al (2008) Assessment of fall-risk by means of a neural network based on parameters assessed by a wearable device during posturography. Med Eng Phys 30(3):367-372
78. Gietzelt M et al (2009) A clinical study to assess fall risk using a single waist accelerometer. Inform Health Soc Care 34(4):181-188
79. Marschollek M et al. (2008) Assessing elderly persons' fall risk using spectral analysis on accelerometric data - a clinical evaluation study, Proceedings 30th annual International Conference of IEEE EMBS, pp 3682-3685
80. Williams G et al. (1998) A smart fall and activity monitor for telecare applications, Proceedings 20th annual International Conference of IEEE EMB 3: 1151-1154
81. Doughty K, Lewis R, McIntosh A (2000) The design of a practical and reliable fall detector for community and institutional telecare. J Telemed Telecare 6(1):S150-S154
82. Degen T et al. (2003) SPEEDY: A fall detector in a wrist watch, Proceedings 17th IEEE Int. Symposium on Wearable Computing, pp 184-187
83. Kangas M et al (2008) Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait Posture 28(2):285-291
84. Meng Y, Kim HC (2011) Heuristics for designing and evaluation wearable healthcare systems from user perspectives, CEIS 2011 (in press)
85. de Vries SI et al (2006) Clinimetric review of motion sensors in children and adolescents. J Clin Epidemiol 59(7):670-680
86. Bonomi AG et al (2010) Estimation of free-living energy expenditure using a novel activity monitor designed to minimize obtrusiveness. Obesity 18(9):1845-1851
87. Lemoyne R et al., (2010) Implementation of an iPhone as a wireless accelerometer for quantifying gait characteristics, Proceedings 32nd annual International Conference of IEEE EMBS, 1: 3847-3851
88. Liu J et al (2008) Local dynamic stability assessment of motion impaired elderly using electronic textile pants. IEEE Trans Autom Sci Eng 5(4):696-702
89. Ni Scanaill C et al (2006) A review of approaches to mobility telemonitoring of the elderly in their living environment. Ann Biomed Eng 34(4):547-563