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Review
. 2015:8:64-77.
doi: 10.1109/RBME.2015.2390646. Epub 2015 Jan 12.

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Gina Sprint, Diane J Cook, Douglas L Weeks
Review

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Gina Sprint et al. IEEE Rev Biomed Eng. 2015.

Abstract

Older adults often suffer from functional impairments that affect their ability to perform everyday tasks. To detect the onset and changes in abilities, healthcare professionals administer standardized assessments. Recently, technology has been utilized to complement these clinical assessments to gain a more objective and detailed view of functionality. In the clinic and at home, technology is able to provide more information about patient performance and reduce subjectivity in outcome measures. The timed up and go (TUG) test is one such assessment recently instrumented with technology in several studies, yielding promising results toward the future of automating clinical assessments. Potential benefits of technological TUG implementations include additional performance parameters, generated reports, and the ability to be self-administered in the home. In this paper, we provide an overview of the TUG test and technologies utilized for TUG instrumentation. We then critically review the technological advancements and follow up with an evaluation of the benefits and limitations of each approach. Finally, we analyze the gaps in the implementations and discuss challenges for future research toward automated self-administered assessment in the home.

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Figures

Fig. 1
Fig. 1
Experimental setup for instrumenting the timed up and go with inertial sensors and cameras (left). The red cross on the floor denotes the turnaround point. Shimmer inertial sensor (5.4 cm × 1.9 cm × 3.2 cm) with coordinate axes (right). Greene and Kenny (2012) [74].
Fig. 2
Fig. 2
The Skeleton TUG. The dashed and dotted areas are the view and detection area of Kinect one and two respectively. Labels Ms – Me correspond to component detected events. Labels al – a12 are TUG actions. Lohmann et al. (2012) [56].
Fig. 3
Fig. 3
Diagram of how inertial sensors were used for the iTUG analysis algorithms. Acceleration is represented by α and angular velocity by ω. Salarian et al. (2010) [41].
Fig. 4
Fig. 4
Smartphone TUG application displaying the TUG parameters computed. Milosevic et al. (2013) [86].
See this image and copyright information in PMC

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