Quantitative Falls Risk Assessment Using the Timed Up and Go Test

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.

Early identification of declining balance in higher functioning older adults, an inertial sensor based method

“…The BBS was delivered and scored as per the protocol outlined by Berg et al [16]. The TUG was conducted as per the protocol described by Greene et al [11]. Wireless inertial sensors (SHIMMER Research, Dublin, Ireland) were used to capture kinematic data during the TUG (Fig.…”

“…Quantitative TUG parameters were calculated from the raw sensor data, these are described in detail elsewhere [11,12]. In summary temporal, spatio-temporal, turn and tri-axial angular velocity parameters were extracted for further analyses.…”

“…The TUG is quick, easy to administer and has been shown to have some predictive power for falls and mobility impairment [9,10]. Additionally, the application of wireless inertial sensors to the lower limbs during the TUG allows measurements such as cadence, stance phase duration and angular velocity to be recorded [11,12]. These objective measures have been combined statistically to improve the accuracy of falls risk assessment as compared to TUG time [11,12].…”

“…Additionally, the application of wireless inertial sensors to the lower limbs during the TUG allows measurements such as cadence, stance phase duration and angular velocity to be recorded [11,12]. These objective measures have been combined statistically to improve the accuracy of falls risk assessment as compared to TUG time [11,12]. As altered balance is associated with falls risk these inertial sensor based measures may have utility in identifying early changes in balance for higher functioning groups [4].…”

A New Application of Smart Walker for Quantitative Analysis of Human Walking

“…These studies examined the usual gait parameters such as used time [42], gait speed, stride length, cadence, double-limb support duration during the turning [43]. Other methods assess accelerometer-derived parameters [44], [26] and gyroscope-derived parameters [45]. Our objective is to find new quality index during turning phase by using the walker instrumented with an accelerometer/gyrometer, which may help doctors to evaluate the fall risk of the elderly.…”