SHIMMER: A new tool for temporal gait analysis

Development of a flexible wireless sensor platform for measurement of biomechanical and physiological variables related to functional movement would be a vital step towards effective ambulatory monitoring and early detection of risk factors in the ageing population. The small form factor, wirelessly enabled SHIMMER platform has been developed towards this end. This study is focused assessing the utility of the SHIMMER for use in ambulatory human gait analysis. Temporal gait parameters derived from a tri-axial gyroscope contained in the SHIMMER are compared against those acquired simultaneously using the CODA motion analysis system. Results from a healthy adult male subject show excellent agreement (ICC(2, k) > 0.85) in stride, swing and stance time for 10 walking trials and 4 run trials. The mean differences using the Bland and Altman method for stance, stride and swing times were 0.0087, 0.0044 and -0.0061 seconds respectively. These results suggest that the SHIMMER is a versatile cost effective tool for use in temporal gait analysis.

[1]  Brian Caulfield,et al.  Increasing the number of gait trial recordings maximises intra-rater reliability of the CODA motion analysis system. , 2007, Gait & posture.

[2]  Chitralakshmi K. Balasubramanian,et al.  Variability in spatiotemporal step characteristics and its relationship to walking performance post-stroke. , 2009, Gait & posture.

[3]  Roman Kamnik,et al.  An inertial and magnetic sensor based technique for joint angle measurement. , 2007, Journal of biomechanics.

[4]  Kamiar Aminian,et al.  Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes. , 2002, Journal of biomechanics.

[5]  P. Bonato,et al.  Wearable Wireless Sensor Network to Assess Clinical Status in Patients with Neurological Disorders , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[6]  R N Marshall,et al.  Algorithms to determine event timing during normal walking using kinematic data. , 2000, Journal of biomechanics.

[7]  D. Altman,et al.  Measuring agreement in method comparison studies , 1999, Statistical methods in medical research.

[8]  Jeffrey M. Hausdorff,et al.  Gait variability and fall risk in community-living older adults: a 1-year prospective study. , 2001, Archives of physical medicine and rehabilitation.

[9]  V Maynard,et al.  Intra-rater and inter-rater reliability of gait measurements with CODA mpx30 motion analysis system. , 2003, Gait & posture.

[10]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.