Abstract
This article describes an ambulatory gait event detection method for long-term monitoring of walking. Aminian et al. [2] have developed an automatic gait event detection algorithm based on shank-attached gyroscope signals. However, this algorithm has a drawback in that it is post-processed. We propose a modified algorithm which detects foot initial and end contact timings using the same concept as in [2], but in quasi real-time. The utilization of the knowledge on gait sequence and peak angular acceleration realizes the quasi real-time detection. Furthermore, to be practical, the algorithm has been developed to ensure the robustness of detection (i.e., without missing the gait events in various speed conditions). Validation of the algorithm using footswitches shows that the algorithm detected the end contacts earlier (−8 ms) and the initial contacts later (19 ms) than the footswitch-based method.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aminian K, Rezakhanlou K, De Andres E, Fritsch C, Leyvraz PF, Robert P (1999) Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty. Med Biol Eng Comput 37:686–691
Aminian K, Najafi B, Bula C, Leyvraz P, Robert P (2002) Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. J Biomech 35:689–699
Coley B, Najafi B, Paraschiv-Ionescu A, Aminian K (2005) Stair climbing detection during daily physical activity using a miniature gyroscope. Gait Posture 22:287–294
Cutti AG, Ferrari A, Garofalo P, Raggi M, Cappello A, Ferrari A (2010) ‘Outwalk’: a protocol for clinical gait analysis based on inertial and magnetic sensors. Med Biol Eng Comput 48:17–25
Ferrari A, Cutti AG, Garofalo P, Raggi M, Heijboer M, Cappello A, Davalli A (2010) First in vivo assessment of “Outwalk”: a novel protocol for clinical gait analysis based on inertial and magnetic sensors. Med Biol Eng Comput 48:1–15
Han J, Jeon HS, Yi WJ, Jeon BS, Park KS (2009) Adaptive windowing for gait phase discrimination in Parkinsonian gait using 3-axis acceleration signals. Med Biol Eng Comput 47:1155–1164
Jasiewicz JM, Allum JH, Middleton JW, Barriskill A, Condie P, Purcell B, Li RC (2006) Gait event detection using linear accelerometers or angular velocity transducers in able-bodied and spinal-cord injured individuals. Gait Posture 24:502–509
Lau H-Y, Tong K-Y, Zhu H (2008) Support vector machine for classification of walking conditions using miniature kinematic sensors. Med Biol Eng Comput 46:563–573
Lee J-A, Cho S-H, Lee Y-J, Yang H-K, Lee J-W (2009) Portable activity monitoring system for temporal parameters of gait cycles. J Med Syst 34:959–966
Monaghan CC, van Riel WJBM, Veltink PH (2009) Control of triceps surae stimulation based on shank orientation using a uniaxial gyroscope during gait. Med Biol Eng Comput 47:1181–1188
Pappas IP, Popovic MR, Keller T, Dietz V, Morari M (2001) A reliable gait phase detection system. IEEE Trans Neural Syst Rehabil Eng 9:113–125
Sabatini AM, Martelloni C, Scapellato S, Cavallo F (2005) Assessment of walking features from foot inertial sensing. IEEE Trans Biomed Eng 52:486–494
Selles RW, Formanoy MA, Bussmann JB, Janssens PJ, Stam HJ (2005) Automated estimation of initial and terminal contact timing using accelerometers; development and validation in transtibial amputees and controls. IEEE Trans Neural Syst Rehabil Eng 13:81–88
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lee, J.K., Park, E.J. Quasi real-time gait event detection using shank-attached gyroscopes. Med Biol Eng Comput 49, 707–712 (2011). https://doi.org/10.1007/s11517-011-0736-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-011-0736-0