© The Institution of Engineering and Technology
This study explores wavelet decomposition based skewness analysis for walking speed assessment. This has been achieved by using four force sensing resistors attached beneath the foot and one flex sensor attached on ankle. Experimentation is carried out on walking pattern of able individuals and data are collected using data acquiescing set-up and de-noised using Savitzky–Golay filter. De-noised data are then decomposed at different discrete wavelet transform (DWT) levels from where skewness values of approximate coefficient are assessed. Variation of skewness with respect to walking speed has been observed which shows that skewness values are having definite relations with walking speeds at certain DWT levels. Based on these, an algorithm is proposed for walking speed assessment. Experimentation is again carried out to validate the proposed algorithm. Satisfactory result is achieved indicating that assessment of wavelet decomposition based skewness of approximate coefficients may be very useful for walking speed measurement.
References
-
-
1)
-
17. Chattopadhyay, S., Chattopadhyaya, A., Sengupta, S.: ‘Measurement of harmonic distortion and skewness of stator current of induction motor at crawling in Clarke plane’, IET Sci. Meas. Technol., 2014, 8, (6), pp. 528–536 (doi: 10.1049/iet-smt.2013.0082).
-
2)
-
5. Verdini, F., Leo, T., Fioretti, S., et al: ‘Analysis of ground reaction forces by means of wavelet transform’, Clin. Biomech. (Bristol, Avon), 2000, 15, (8), pp. 607–610 (doi: 10.1016/S0268-0033(00)00019-X).
-
3)
-
14. Liu, T., Inoue, Y., Shibata, K., et al: ‘A mobile force plate and three-dimensional motion analysis system for three-dimensional gait assessment’, IEEE Sens. J., 2012, 12, (5), pp. 1461–1467 (doi: 10.1109/JSEN.2011.2173763).
-
4)
-
10. Hagler, S., Austin, D., Hayes, T.L., et al: ‘Unobtrusive and ubiquitous in-home monitoring: a methodology for continuous assessment of gait velocity in elders’, IEEE Trans. Biomed. Eng., 2010, 57, (4), pp. 813–820 (doi: 10.1109/TBME.2009.2036732).
-
5)
-
4. Sloboda, W., Zatsiorsky, V.M.: ‘Wavelet representation of the ground reaction force data’. Proc. of the ASME Dynamics Systems and Control Division, vol. 58, 1996, pp. 917–926.
-
6)
-
12. Maranesi, E., Barone, V., Fioretti, S.: ‘Assessment of walking speed by a goniometer-based method’. 36th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBC), 2014, 2014, pp. 1202–1205, .
-
7)
-
9. Wahid, F., Begg, R.K., Hass, C.J., et al: ‘Classification of Parkinson's disease gait using spatial–temporal gait features’, IEEE J. Biomed. Health Inf., 2015, 19, (6), pp. 1794–1802 (doi: 10.1109/JBHI.2015.2450232).
-
8)
-
15. Qi, Y., Soh, C.B., Gunawan, E., et al: ‘Ambulatory measurement of three-dimensional foot displacement during treadmill walking using wearable wireless ultrasonic sensor network’, IEEE J. Biomed. Health Inf., 2015, 19, (2), pp. 446–452 (doi: 10.1109/JBHI.2014.2316998).
-
9)
-
13. Juen, J., Cheng, Q., Schatz, B.: ‘A natural walking monitor for pulmonary patients using mobile phones’, IEEE J. Biomed. Health Inf., 2015, 19, (4), pp. 1399–1405 (doi: 10.1109/JBHI.2015.2427511).
-
10)
-
11. Sabatini, A.M., Martelloni, C., Scapellato, S., et al: ‘Assessment of walking features from foot inertial sensing’, IEEE Trans. Biomed. Eng., 2005, 52, (3), pp. 486–494 (doi: 10.1109/TBME.2004.840727).
-
11)
-
1. Mathie, M.J., Coster, A.C., Lovell, N.H., et al: ‘Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement’, Physiol. Meas., 2004, 25, (2), p. R1–R20. (doi: 10.1088/0967-3334/25/2/R01).
-
12)
-
20. Masum, H., Bhaumik, S., Dalmia, A., et al: ‘Development of wireless foot pressure sensor for bio-medical application’. Second Int. Conf. on Advances in Mechanical Engineering and its Interdisciplinary Areas (ICAMEI-2015), January 2015, pp. 355–360.
-
13)
-
7. Misiti, M.: ‘Wavelet toolbox user's guide’ (The MathWorks, Inc., 2005).
-
14)
-
18. Chattopadhyay, S., Chattopadhyaya, A., Sengupta, S.: ‘Analysis of stator current of induction motor used in transport system at single phasing by measuring phase angle, symmetrical components, skewness, kurtosis and harmonic distortion in Park plane’, IET Electr. Syst. Transp., 2014, 4, (1), pp. 1–8 (doi: 10.1049/iet-est.2012.0048).
-
15)
-
19. Masum, H., Bhaumik, S., Ray, R.: ‘Conceptual design of a powered ankle–foot prosthesis for walking with inversion and eversion’, Procedia Technol., 2014, 14, pp. 228–235 (doi: 10.1016/j.protcy.2014.08.030).
-
16)
-
8. Sejdic, E., Lowry, K.A., Bellanca, J., et al: ‘Extraction of stride events from gait accelerometry during treadmill walking’, IEEE J. Transl. Eng. Health Med., 2016, 4, , pp. 1–11 (doi: 10.1109/JTEHM.2015.2504961).
-
17)
-
16. Chattopadhyay, S., Mitra, M., Sengupta, S.: ‘Electric power quality’ (Springer, 2011).
-
18)
-
2. Kavanagh, J.J., Menz, H.B.: ‘Accelerometry: a technique for quantifying movement patterns during walking’, Gait Posture, 2008, 28, (1), pp. 1–15 (doi: 10.1016/j.gaitpost.2007.10.010).
-
19)
-
6. Verdini, F., Marcucci, A., Benedetti, M.G., et al: ‘Identification and characterisation of heel strike transient’, Gait Posture, 2006, 24, (1), pp. 77–84 (doi: 10.1016/j.gaitpost.2005.07.008).
-
20)
-
3. Wang, N., Ambikairajah, E., Lovell, N.H., et al: ‘Accelerometry based classification of walking patterns using time–frequency analysis’. Proc. 29th Annual Int. Conf. of the IEEE EMBS, Cité Internationale, Lyon, France, 23–26 August 2007.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-smt.2016.0263
Related content
content/journals/10.1049/iet-smt.2016.0263
pub_keyword,iet_inspecKeyword,pub_concept
6
6