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Annual International Conference of the IEEE Engineering in Medicine and Biology Society.; 09/2012
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 09/2012
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ABSTRACT: Falls are a major problem in older adults worldwide with an estimated 30% of elderly adults over 65 years of age falling each year. The direct and indirect societal costs associated with falls are enormous. A system that could provide an accurate automated assessment of falls risk prior to falling would allow timely intervention and ease the burden on overstretched healthcare systems worldwide. An objective method for assessing falls risk using body-worn kinematic sensors is reported. The gait and balance of 349 community-dwelling elderly adults was assessed using body-worn sensors while each patient performed the “timed up and go” (TUG) test. Patients were also evaluated using the Berg balance scale (BBS). Of the 44 reported parameters derived from body-worn kinematic sensors, 29 provided significant discrimination between patients with a history of falls and those without. Cross-validated estimates of retrospective falls prediction performance using logistic regression models yielded a mean sensitivity of 77.3% and a mean specificity of 75.9%. This compares favorably to the cross-validated performance of logistic regression models based on the time taken to complete the TUG test (manually timed TUG) and the Berg balance score. These models yielded mean sensitivities of 58.0% and 57.8%, respectively, and mean specificities of 64.8% and 64.2%, respectively. Results suggest that this method offers an improvement over two standard falls risk assessments (TUG and BBS) and may have potential for use in supervised assessment of falls risk as part of a longitudinal monitoring protocol.
IEEE Transactions on Biomedical Engineering 01/2011; · 2.28 Impact Factor
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ABSTRACT: Inertial sensors have become increasingly popular in gait analysis, due to their highly portable, low cost, and potentially wireless nature. However, accurate spatial gait analysis using few sensors remains a challenge. A gyroscope-based algorithm for spatial gait analysis is presented. This novel algorithm (SGA) uses data from a single gyroscope attached to each shank. The performance of the SGA was compared to that of an electronic walkway, GAITRite<sup>®</sup>. The two systems compared favorably, with a mean error in stride length of 0.09 ± 0.07 m, and a mean error in stride velocity of 0.11 ± 0.10 m/s. The error between the SGA and GAITRite was also similar to that reported by previous inertial sensor based algorithms. The relationship between stride length and stride velocity, as well as that of subject height and stride length was also examined. This new method provides an inexpensive, portable system for spatial or spatio-temporal gait analysis, which has potential for use in any location.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: 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.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: 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.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: Applying new sensing technology to healthcare maybe part of a solution to the financial and demographic crisis facing global healthcare systems. Researchers applying new approaches to noninvasive patient monitoring and diagnostics are assisted by the features of Sensing Health with Intelligence, Modularity, Mobility and Experimental Reusability (SHIMMER™), a flexible sensing platform. Integrated peripherals, open software, modular expansion, specific power management hardware, and a library of applications supported with platform validation provide SHIMMER with advantages over many other medical research platforms.
IEEE Sensors Journal 10/2010; · 1.52 Impact Factor
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ABSTRACT: 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.
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE; 10/2009
