A comprehensive comparison of simple step counting techniques using wrist- and ankle-mounted accelerometer and gyroscope signals

References

• Coelho CM, Reboredo MM, Valle FM, et al. Effects of an unsupervised pedometer-based physical activity program on daily steps of adults with moderate to severe asthma: a randomized controlled trial. J Sports Sci. 2017;36:1186–1193.
   PubMed Web of Science ®Google Scholar
• Alsubheen SAA, George AM, Baker A, et al. Accuracy of the vivofit activity tracker. J Med Eng Technol. 2016;40:298–306.
   PubMedGoogle Scholar
• Busse ME, Van Deursen RW, Wiles CM. Real-life step and activity measurement: reliability and validity. J Med Eng Technol. 2009;33:33–41.
   PubMedGoogle Scholar
• Dontje ML, de Groot M, Lengton RR, et al. Measuring steps with the Fitbit activity tracker: an inter-device reliability study. J Med Eng Technol. 2015;39:286–290.
   PubMedGoogle Scholar
• Noah JA, Spierer DK, Gu J, et al. Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. J Med Eng Technol. 2013;37:456–462.
   PubMedGoogle Scholar
• Diaz KM, Krupka DJ, Chang MJ, et al. Wrist-based cut-points for moderate-and vigorous-intensity physical activity for the actical accelerometer in adults. J Sports Sci. 2017;36:206–212.
   PubMed Web of Science ®Google Scholar
• Atallah L, Lo B, King R, et al. Sensor positioning for activity recognition using wearable accelerometers. IEEE Trans Biomed Circuits Syst. 2011;5:320–329.
   PubMed Web of Science ®Google Scholar
• Foster RC, Lanningham-Foster LM, Manohar C, et al. Precision and accuracy of an ankle-worn accelerometer-based pedometer in step counting and energy expenditure. Prev Med. 2005;41:778–783.
   PubMed Web of Science ®Google Scholar
• Horvath S, Taylor DG, Marsh JP, et al. The effect of pedometer position and normal gait asymmetry on step count accuracy. Appl Physiol Nutr Metab. 2007;32:409–415.
   PubMed Web of Science ®Google Scholar
• Dobkin BH, Xu X, Batalin M, et al. Reliability and validity of bilateral ankle accelerometer algorithms for activity recognition and walking speed after stroke. Stroke. 2011;42:2246–2250.
   PubMed Web of Science ®Google Scholar
• Fortune E, Lugade V, Morrow M, et al. Validity of using tri-axial accelerometers to measure human movement – part II: step counts at a wide range of gait velocities. Med Eng Phys. 2014;36:659–669.
   PubMed Web of Science ®Google Scholar
• Fortune E, Lugade VA, Amin S, et al. Step detection using multi- versus single tri-axial accelerometer-based systems. Physiol Meas. 2015;36:2519–2535.
   PubMed Web of Science ®Google Scholar
• Trost SG, McIver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sports Exerc. 2005;37:S531–S543.
   PubMed Web of Science ®Google Scholar
• Leong JY, Wong JE. Accuracy of three Android-based pedometer applications in laboratory and free-living settings. J Sports Sci. 2017;35:14–21.
   PubMed Web of Science ®Google Scholar
• Seo J, Chiang Y, Laine TH, et al. Step counting on smartphones using advanced zero-crossing and linear regression. Proceedings of the 9th International Conference on Ubiquitous Information Management and Communcation. 2015;106–112.
   Google Scholar
• Cho Y, Cho H, Kyung C-M. Design and implementation of practical step detection algorithm for wrist-worn devices. IEEE Sens J. 2016;16:7720–7730.
   Web of Science ®Google Scholar
• Brajdic A, Harle R. Walk detection and step counting on unconstrained smartphones. Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 2013;225–234.
   Google Scholar
• Pan M-S, Lin H-W. A step counting algorithm for smartphone users: design and implementation. IEEE Sensors J. 2015;15:2296–2305.
   Web of Science ®Google Scholar
• Ryu U, Ahn K, Kim E, et al. Adaptive step detection algorithm for wireless smart step counter. IEEE International Conference on Information Science and Applications (ICISA). 2013;1–4.
   Google Scholar
• Kang W, Nam S, Han Y, et al. Improved heading estimation for smartphone-based indoor positioning systems. IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). 2012;2449–2453.
   Google Scholar
• Kim JW, Jang HJ, Hwang D-H, et al. A step, stride and heading determination for the pedestrian navigation system. J Glob Posi Syst. 2004;3:273–279.
   Google Scholar
• Lim YP, Brown IT, Khoo JCT. An accurate and robust gyroscope-gased pedometer. 30th Annual International IEEE EMBS Conference. 2008;4587–4590.
   Google Scholar
• Jayalath S, Abhayasinghe N, Murray I. A gyroscope based accurate pedometer algorithm. International Conference on Indoor Positioning and Indoor Navigation. 2013;28.
   Google Scholar
• Thorstensson A, Roberthson H. Adaptations to changing speed in human locomotion: speed of transition between walking and running. Acta Physiol Scand. 1987;131:211–214.
   PubMedGoogle Scholar
• Duong HT, Suh YS. Walking parameters estimation based on a wrist-mounted inertial sensor for a walker user. IEEE Sensors J. 2016;17:2100–2108.
   Web of Science ®Google Scholar
• Barth J, Oberndorfer C, Kugler P, et al. Subsequence dynamic time warping as a method for robust step segmentation using gyroscope signals of daily life activities. Engineering in Medicine and Biology Society (EMBC) 2013 35th Annual International Conference of the IEEE. 2013;6744–6747.
   Google Scholar
• Palshikar G. Simple algorithms for peak detection in time-series. Proceedings of the 1st International Conference on Advanced Data Analysis, Business Analytics and Intelligence. 2009;1–13.
   Google Scholar
• Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE Trans Biomed Eng. 1985;32:230–236.
   PubMed Web of Science ®Google Scholar
• Ying H, Silex C, Schnitzer A, et al. Automatic step detection in the accelerometer signal. 4th International Workshop on Wearable and Implantable Body Sensor Networks. 2007;80–85.
   Google Scholar
• Marschollek M, Goevercin M, Wolf K-H, et al. A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility impaired persons. 30th Annual International IEEE EMBS Conference. 2008;1319–1322.
   Google Scholar
• Liu Y, Collins RT, Tsin Y. A computational model for periodic pattern perception based on frieze and wallpaper groups. IEEE Trans Patt Anal Mach Intellig. 2004;26:354–371.
   PubMed Web of Science ®Google Scholar
• Modi YR. Wrist pedometer step detection. United States Patent Application 13/608,214. 2012.
   Google Scholar
• Bland JM, Altman D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327:307–310.
   Web of Science ®Google Scholar
• Bartko JJ. The intraclass correlation coefficient as a measure of reliability. Psychol Rep. 1966;19:3–11.
   PubMed Web of Science ®Google Scholar
• Wong CK, Mentis HM, Kuber R. The bit doesn’t fit: evaluation of a commercial activity-tracker at slower walking speeds. Gait Post. 2017;59:177–181.
   PubMed Web of Science ®Google Scholar
• Del Din S, Godfrey A, Rochester L. Validation of an accelerometer to quantify a comprehensive battery of gait characteristics in healthy older adults and Parkinson’s disease: toward clinical and at home use. IEEE J Biomed Health Inform. 2016;20:838–847.
   PubMed Web of Science ®Google Scholar