High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents

Abstract

The Timed Up and Go test (TUG) is commonly used to estimate the fall risk in the elderly. Several ways to improve the predictive accuracy of TUG (cameras, multiple sensors, other clinical tests) have already been proposed. Here, we added a single wearable inertial measurement unit (IMU) to capture the residents’ body center-of-mass kinematics in view of improving TUG’s predictive accuracy. The aim is to find out which kinematic variables and residents’ characteristics are relevant for distinguishing faller from non-faller patients. Data were collected in 73 nursing home residents with the IMU placed on the lower back. Acceleration and angular velocity time series were analyzed during different subtasks of the TUG. Multiple logistic regressions showed that total time required, maximum angular velocity at the first half-turn, gender, and use of a walking aid were the parameters leading to the best predictive abilities of fall risk. The predictive accuracy of the proposed new test, called i + TUG, reached a value of 74.0%, with a specificity of 95.9% and a sensitivity of 29.2%. By adding a single wearable IMU to TUG, an accurate and highly specific test is therefore obtained. This method is quick, easy to perform and inexpensive. We recommend to integrate it into daily clinical practice in nursing homes.

Evaluation of Lower-Limb Kinematics during Timed Up and Go (TUG) Test in Subjects with Locomotive Syndrome (LS) Using Wearable Gait Sensors (H-Gait System)

“…Although an optical motion analysis system using a camera has been generally used to analyze lower-limb kinematics during the TUG test, it imposes limitations on the time and location of the measurement [ 16 ]. In recent years, due to technological advances, motion analysis using acceleration and gyro sensors has been verified and clinically applied to gait analysis during the TUG test [ 17 , 18 , 19 , 20 , 21 ]. The H-Gait system can also make it possible to evaluate lower-limb kinematics during the TUG test.…”

Wearable technology use in long-term care facilities for older adults: a scoping review protocol

“…This review will seek to identify the available literature on the use of WT in LTCFs for older adults, including type of device design, body placement, functions, data gathered, and the range of health conditions or diseases associated with WT usage. Studies, policies, or opinion papers will be included if they pertain to wearable devices that perform activity or movement tracking, location monitoring, vital signs monitoring, sleep assessment, or other functions specifically used to improve the care provided in LTCF settings 14–17 . This review will also seek to understand whether aspects related to acceptability of WT by older adults have been considered in LTCF settings 17–19 .…”

“…WT can enhance older adults' safety, tracking their movements and sending alerts if they wander or leave the facility, reducing the risk of falls, or mitigating other negative outcomes. 15,16 The motion-tracking function can, at the same time, highlight low levels of activity, promoting the implementation of programs to counter the alarming level of sedentary living in LTCFs for older adults. 17 The use of WT in settings characterized by physical and cognitive frailty raises questions of acceptability, which is the extent to which people are willing to adopt and regularly use WT in their daily lives.…”

“…WT is playing an increasing role in caring for older adults living in LTCFs by monitoring frailty and age-related issues in the aged population 14–17 . WT can help assess the level of frailty, provide real-time monitoring of vital signs or sleep patterns and allow staff to quickly respond to changes in older residents’ conditions 14 .…”

Wearable Sensors Applied in Movement Analysis

“…Optimal agreement (98.4%) with the therapist’s scoring can be achieved using a one-dimensional convolutional neural network and a gated recurrent unit in a population of 53 hospitalized patients with brain diseases aged 50 to 80 years. Finally, it was shown in [ 13 ] that additional information from a single IMU, placed on the lower back of 73 care institute residents who performed a Timed-Up and Go (TUG) test considerably improved fall risk prediction. Kinematic observations and TUG time were included in a multiple logistic regression.…”