Performing gait analysis within the timed up &amp; go assessment test: comparison of aTUG to a marker-based tracking system

Frenken, Thomas; Lohmann, Okko; Frenken, Melina; Steen, Enno-Edzard; Hein, Andreas

doi:10.3109/17538157.2014.931850

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…Other researchers used video to analyze a specific component of the test. For example, Wang et al [ 20 ] focused on the turn phase, whereas Frenken et al [ 21 ] studied the walking phase. Lohmann et al [ 22 ] used a Kinect camera with skeleton tracking to automate the test.…”

Section: Introductionmentioning

confidence: 99%

Automating the Timed Up and Go Test Using a Depth Camera

Dubois

Bihl

Bresciani

2017

Sensors

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Fall prevention is a human, economic and social issue. The Timed Up and Go (TUG) test is widely used to identify individuals with a high fall risk. However, this test has been criticized because its “diagnostic” is too dependent on the conditions in which it is performed and on the healthcare professionals running it. We used the Microsoft Kinect ambient sensor to automate this test in order to reduce the subjectivity of outcome measures and to provide additional information about patient performance. Each phase of the TUG test was automatically identified from the depth images of the Kinect. Our algorithms accurately measured and assessed the elements usually measured by healthcare professionals. Specifically, average TUG test durations provided by our system differed by only 0.001 s from those measured by clinicians. In addition, our system automatically extracted several additional parameters that allowed us to accurately discriminate low and high fall risk individuals. These additional parameters notably related to the gait and turn pattern, the sitting position and the duration of each phase. Coupling our algorithms to the Kinect ambient sensor can therefore reliably be used to automate the TUG test and perform a more objective, robust and detailed assessment of fall risk.

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Section: Introductionmentioning

confidence: 99%

Automating the Timed Up and Go Test Using a Depth Camera

Dubois

Bihl

Bresciani

2017

Sensors

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“…38 The SIMI motion system is a very reliable and valid tool used in gait analysis worldwide. A study by Frenken et al 39 used the SIMI motion system as the gold standard for validating Timed Up and Go assesment in gait analysis. Although markerless techniques have gained popularity in the biomechanics in the past decade, their application in the clinical setting is a matter of debate.…”

Section: Instrumentation and Setupmentioning

confidence: 99%

Foot Kinetic and Kinematic Profile in Type 2 Diabetes Mellitus with Peripheral Neuropathy

Hazari

Maiya

Shivashankara

2019

Journal of the American Podiatric Medical Association

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The mean age, height, weight, body mass index, duration of diabetes was 57±14 year, 164±11cm, 61±18kg, 24± 3, 12±7 year respectively. There were significant changes in overall biomechanical profile along with clinical manifestations of diabetes peripheral neuropathy.The regression analysis showed statistical significance for dynamic maximum plantar pressure at forefoot with age, weight, height, duration of diabetes, body mass index, knee & ankle joint angle at toe-off phase of gait cycle,pinprick sensation and ankle reflex (R=.71,R =.55, F (12, 108)=521.9 kPa, p=.002) Conclusions: From the present study, we conclude that people with type 2 diabetes mellitus and peripheral neuropathy have significant changes in their foot kinetics and kinematicsparameters. Therefore, they could be at higher risk of foot ulceration with underlying neuropathy and biomechanically associated problems.

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“…The aTUG’s validity to measure step length and step duration was initially confirmed within a trial with 7 participants [ 44 ]. In addition, the aTUG’s validity to measure total TUG duration via light barriers with a root mean squared error (RMSE) of 0.83 s and force sensors of 0.90 s was confirmed [ 45 ] in a clinical trial with 100 older adults with a mean age of 74 years.…”

Section: Introductionmentioning

confidence: 99%

Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair

Fudickar

Kiselev

Stolle

et al. 2021

Sensors

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This article covers the suitability to measure gait-parameters via a Laser Range Scanner (LRS) that was placed below a chair during the walking phase of the Timed Up&Go Test in a cohort of 92 older adults (mean age 73.5). The results of our study demonstrated a high concordance of gait measurements using a LRS in comparison to the reference GAITRite walkway. Most of aTUG’s gait parameters demonstrate a strong correlation coefficient with the GAITRite,indicating high measurement accuracy for the spatial gait parameters. Measurements of velocity had a correlation coefficient of 99%, which can be interpreted as an excellent measurement accuracy. Cadence showed a slightly lower correlation coefficient of 96%, which is still an exceptionally good result, while step length demonstrated a correlation coefficient of 98% per leg and stride length with an accuracy of 99% per leg. In addition to confirming the technical validation of the aTUG regarding its ability to measure gait parameters, we compared results from the GAITRite and the aTUG for several parameters (cadence, velocity, and step length) with results from the Berg Balance Scale (BBS) and the Activities-Specific Balance Confidence-(ABC)-Scale assessments. With confidence coefficients for BBS and velocity, cadence and step length ranging from 0.595 to 0.798 and for ABC ranging from 0.395 to 0.541, both scales demonstrated only a medium-sized correlation. Thus, we found an association of better walking ability (represented by the measured gait parameters) with better balance (BBC) and balance confidence (ABC) overall scores via linear regression. This results from the fact that the BBS incorporates both static and dynamic balance measures and thus, only partly reflects functional requirements for walking. For the ABC score, this effect was even more pronounced. As this is to our best knowledge the first evaluation of the association between gait parameters and these balance scores, we will further investigate this phenomenon and aim to integrate further measures into the aTUG to achieve an increased sensitivity for balance ability.

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Performing gait analysis within the timed up & go assessment test: comparison of aTUG to a marker-based tracking system

Cited by 8 publications

References 9 publications

Automating the Timed Up and Go Test Using a Depth Camera

Automating the Timed Up and Go Test Using a Depth Camera

Foot Kinetic and Kinematic Profile in Type 2 Diabetes Mellitus with Peripheral Neuropathy

Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair

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