Why is FallSkip based on a modified version of the Timed up and Go Test for assessing fall risk?

The methodology followed by FallSkip is based on the application of an adapted version of the “Timed up and Go” Test (TUG), which has been cited in multiple clinical trials [11, 15] as a reliable and cost-effective method for assessing general functional state. Besides, these studies have demonstrated the efficiency of this test for obtaining some parameters related with human gait, balance, motor control or muscle strength. In fact, according to Herman and cols. [3], the TUG test is a widespread tool that allows researchers to obtain reproducible results in older adults, with an ICC=0.99.

What is the contribution of the TUG in terms of fall risk assessment?

Despite its clinical usefulness, there are a significant number of scientific proofs, which claim that collecting how long the TUG test lasts, as a unique objective factor, is an inconsistent way to classify between people with and without fall risk. This is why researchers complement this data with other biomechanical variables, which are globally accepted due to their discriminatory capability between fallers and non-fallers [16, 17, 18].

For this reason, in an effort to improve the practical applicability of the test as a method of evaluation for older adults´ fall risk, researchers have been recently using new wearable measurement instruments based on inertial movement units (IMU) [4]. These sensors allow professionals to evaluate different biomechanical variables throughout the test´s milestones, providing quantitative data like temporal, kinetic and kinematic parameters.

How is IMU technology being applied in clinical context?

There are multiple evidences about the applicability of IMU sensors for getting TUG´s quantitative parameters [17, 21]. Higashi and cols. [4] published some examples in the evaluation of hemiplegic patients with gait impairments. Similarly, Weiss and cols. [21] used this technology to define an instrumented version of TUG test in patients with Parkinson. Other evidence is found in the studies carried out by Martinez-Ramirez [10], which describe a satisfactory method to assess balance alterations.

How can biomechanical analysis contribute to obtain an objective measurement of fall risk?

Regarding the biomechanical variables used by FallSkip it is important to remark the great number of papers that justify their high statistical correlation with fall risk. In that way, Hausdorff and cols. [2] conclude that there is a significant correlation between biomechanical parameters, which describe gait variability, and fall risk. Indeed, the specialized literature demonstrates that the more step variability the higher the risk of falling. Following this approach, there are other studies, like those published by Mancini or Topper and cols. [9, 20], that prove the tighten relationship between the biomechanical parameters related with balance functionality and fall risk; the larger centre of masses oscillation the higher danger of falling.

Similarly to the aforementioned studies, the results presented by Perry and cols. [14] support the need for identifying those biomechanical parameters closely related with lower limb strength; the reason lies in the high correlation between those variables and older adults´ fall risk. In that sense, McCarthy, Yuan-Yang and cols. [12, 22] remark the usefulness of the sit-to-stand protocol to evaluate clinically the functionality level of lower limbs in terms of muscle strength and power.

Finally, Mirelman, in his study published in 2012 [13], discusses about the influence of a diminished reaction time over the fall risk. In the same direction, the studies carried out by Laessoe and Lord [5, 6] reach the same conclusion (the longer muscular activation time, the higher fall risk).

What is the reliability of Fallskip in comparison to the current standards of fall risk evaluation?

The Physiological Profile Assessment (PPA) QuickScreen© is considered the current gold standard [7]. This method, which consists of 5 different independent tests, presents an ICC, depending on the tests, between 0.55 and 0.85 [7], with a predictive precision between 70 and 75% [8].

In that sense, a study was undertaken by the Institute of Biomechanics (IBV) among a sample of 65 older adults, who were evaluated, by three independent observers, using PPA and Fallskip methodology. The correlation obtained between these two methods is -0.65 (p<0.01 bilateral).

In the same experiment, a reliability study of Fallskip methodology was also conducted, getting a value of the Cronbach’s Alpha statistic of 0.97, with an ICC between 0.88 and 0.95. These results prove the high reliability of the protocol and biomechanical model implemented in Fallskip.

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