Adrian Burns

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.

SHIMMER™: An extensible platform for physiological signal capture

Wireless sensor networks have become increasingly common in everyday applications due to decreasing technology costs and improved product performance, robustness and extensibility. Wearable physiological monitoring systems have been utilized in a variety of studies, particularly those investigating ECG or EMG during human movement or sleep monitoring. These systems require extensive validation to ensure accurate and repeatable functionality. Here we validate the physiological signals (EMG, ECG and GSR) of the SHIMMER (Sensing Health with Intelligence, Modularity, Mobility and Experimental Reusability) against known commercial systems. Signals recorded by the SHIMMER EMG, ECG and GSR daughter-boards were found to compare well to those obtained by commercial systems.

Adaptive estimation of temporal gait parameters using body-worn gyroscopes

Body-worn kinematic sensors have been widely proposed for use in portable, low cost, ambulatory monitoring of gait. Such sensor based systems could avoid the need for high-cost laboratory-based methods for measurement of gait. We aimed to evaluate an adaptive gyroscope-based algorithm for automated temporal gait analysis using body-worn wireless gyroscopes. Temporal gait parameters were calculated from initial contact (IC) and terminal contact (TC) points derived from gyroscopes, contained in wireless sensors on the left and right shanks, using a newly developed adaptive algorithm. Gyroscope data from nine healthy adult subjects performing four walks at three different speeds were then compared against data acquired simultaneously using two force-plates. Results show that the mean true error between the adaptive gyroscope algorithm and force-plate was −5.5±7.3 ms and 40.6±19.2 ms for IC and TC points respectively; the latter representing a consistent, systematic error of this magnitude that may be intrinsic to shank-mounted gyroscopes. These results suggest that the algorithm reported here could form the basis of a robust, portable, low-cost system for ambulatory monitoring of gait.

Development and validation of a clinic based balance assessment technology

Falls in the elderly are a major problem worldwide, with enormous associated societal costs. Deficits in balance and postural control have long been associated with falls risk in elderly adults. The gold standard for quantitative assessment of human balance in a clinical setting is the force plate which is highly expensive, non-portable and requires specialized personnel to operate. The present study aims to evaluate the validity and reliability of a portable quantitative balance measurement technology compared to the forceplate. Two participants (1 male, 1 female) performed sixteen balance trials each (eight eyes open and eight eyes closed). Simultaneous data were recorded from a portable pressure sensor platform and a laboratory grade force platform. Standard centre of pressure (COP) metrics from both modalities were compared and high levels of agreement in terms of intraclass correlation coefficient (ICC), mean absolute error (MAE) and mean percentage error (MPE) were found.