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Research Papers

Dynamic Balanced Reach: A Temporal and Spectral Analysis Across Increasing Performance Demands

[+] Author and Article Information
Joseph E. Barton

Research and Development Service,
VA Maryland Health Care Center,
Baltimore VA Medical Center,
Baltimore, MD 21201;
Department of Neurology,
University of Maryland School of Medicine,
Baltimore, MD 21201;
Department of Physical Therapy & Rehabilitation Science,
University of Maryland School of Medicine,
Baltimore, MD 21201
e-mail: mailto:jbarton@som.umaryland.edu

Valentina Graci

Research and Development Service,
VA Maryland Health Care Center,
Baltimore VA Medical Center,
Baltimore, MD 21201;
Department of Neurology,
University of Maryland School of Medicine,
Baltimore, MD 21201
e-mail: vgraci@som.umaryland.edu

Charlene Hafer-Macko

Geriatric Research Education and Clinical Center,
VA Maryland Health Care Center,
Baltimore VA Medical Center,
Baltimore, MD 21201;
Department of Neurology,
University of Maryland School of Medicine,
Baltimore, MD 21201
e-mail: cmacko@grecc.umaryland.edu

John D. Sorkin

Geriatric Research Education and Clinical Center,
VA Maryland Health Care Center,
Baltimore VA Medical Center,
Baltimore, MD 21201;
Division of Gerontology and Geriatric Medicine,
Department of Medicine,
University of Maryland School of Medicine,
Baltimore, MD 21201
e-mail: jsorkin@grecc.umaryland.edu

Richard F. Macko

Geriatric Research Education and Clinical Center,
VA Maryland Health Care Center,
Baltimore VA Medical Center,
Baltimore, MD 21201;
Department of Neurology,
University of Maryland School of Medicine,
Baltimore, MD 21201
e-mail: rmacko@grecc.umaryland.edu

1Corresponding author.

Manuscript received February 18, 2016; final manuscript received August 18, 2016; published online November 3, 2016. Assoc. Editor: Zong-Ming Li.This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J Biomech Eng 138(12), 121009 (Nov 03, 2016) (13 pages) Paper No: BIO-16-1066; doi: 10.1115/1.4034506 History: Received February 18, 2016; Revised August 18, 2016

Standing balanced reach is a fundamental task involved in many activities of daily living that has not been well analyzed quantitatively to assess and characterize the multisegmental nature of the body's movements. We developed a dynamic balanced reach test (BRT) to analyze performance in this activity; in which a standing subject is required to maintain balance while reaching and pointing to a target disk moving across a large projection screen according to a sum-of-sines function. This tracking and balance task is made progressively more difficult by increasing the disk's overall excursion amplitude. Using kinematic and ground reaction force data from 32 young healthy subjects, we investigated how the motions of the tracking finger and whole-body center of mass (CoM) varied in response to the motion of the disk across five overall disk excursion amplitudes. Group representative performance statistics for the cohort revealed a monotonically increasing root mean squared (RMS) tracking error (RMSE) and RMS deviation (RMSD) between whole-body CoM (projected onto the ground plane) and the center of the base of support (BoS) with increasing amplitude (p < 0.03). Tracking and CoM response delays remained constant, however, at 0.5 s and 1.0 s, respectively. We also performed detailed spectral analyses of group-representative response data for each of the five overall excursion amplitudes. We derived empirical and analytical transfer functions between the motion of the disk and that of the tracking finger and CoM, computed tracking and CoM responses to a step input, and RMSE and RMSD as functions of disk frequency. We found that for frequencies less than 1.0 Hz, RMSE generally decreased, while RMSE normalized to disk motion amplitude generally increased. RMSD, on the other hand, decreased monotonically. These findings quantitatively characterize the amplitude- and frequency-dependent nature of young healthy tracking and balance in this task. The BRT is not subject to floor or ceiling effects, overcoming an important deficiency associated with most research and clinical instruments used to assess balance. This makes a comprehensive quantification of young healthy balance performance possible. The results of such analyses could be used in work space design and in fall-prevention instructional materials, for both the home and work place. Young healthy performance represents “exemplar” performance and can also be used as a reference against which to compare the performance of aging and other clinical populations at risk for falling.

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References

Figures

Grahic Jump Location
Fig. 1

During the balanced reach test, subjects stand on force platforms, fix gaze and point to the projected disk as it moves around the screen. The locations of two landmarks on each foot are used to compute the perimeter of the BoS at each sampling instant. This computation is robust enough to accurately represent the perimeter should the subject shift their stance or momentarily raise up on the ball of one foot (as shown in the figure).

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Fig. 2

Group-average RMSEs, RMSDs, and response delays for 32 young healthy subject

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Fig. 3

Temporal trajectories (a) and frequency spectra (b) of the disk (gray), tip of the tracking finger (black, top two panels) and CoM–BoS deviation (black, bottom two panels). Dotted lines indicate 95% confidence intervals. Tracking fingertip and CoM–BoS deviation ordinates are along the left hand side of the plots, disk ordinates are along the right-hand side. All trajectories have been shifted along their respective ordinate axes so that the overall excursion amplitude of each can be read directly (e.g., 54.5 cm for the tracking fingertip in the x-direction, 47.6 cm in the y-direction). Movements in the positive x-direction are to the subject's left, those in the positive y-direction are up, and movements in the positive z-direction are forward with respect to the subject (see global coordinate axis orientation in Fig. 1). Due to the scale, tracking finger confidence intervals are barely discernable, so their mean “width” is indicated. This shows that all confidence intervals are approximately the same. The reduced ranges of the AP CoM–BoS deviation in the plot “magnifies” this trajectory, making it appear “noisier” than the other trajectories. 1.1250 arm lengths overall excursion amplitude.

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Fig. 4

Gain/phase diagram of ML(y) and SI (z) components of tracking finger motion and ML CoM-BoS deviation. Dots denote the empirical transfer function gain computed at each disk motion frequency. Solid lines denote the analytical transfer functions fit to the empirical data (upper three rows in Table 4). Dotted lines denote the fitted transfer functions' 95% confidence intervals. Dashed lines denote the minimum phase transfer functions (lower three rows in Table 4). Because minimum phase transfer functions have identical gain characteristics as fitted transfer functions only their phase relationships are visible in the figure. 1.1250 arm lengths overall excursion amplitude. Bode diagrams for other amplitudes are shown in Appendix C, which is available under the “Supplemental Materials” tab for this paper on the ASME Digital Collection.

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Fig. 5

Gain/phase diagrams of ML(y) and SI (z) components of tracking finger motion and ML CoM–BoS deviation for all five disk excursion amplitudes. The individual characteristics are nearly the same across amplitude, indicating that these systems respond linearly under these conditions.

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Fig. 6

Step responses of ML(y) and SI (z) components of tracking finger motion and ML CoM-BoS deviation. Thick lines represent fitted transfer function step responses (upper three rows in Table 4), while thin lines represent minimum phase transfer function responses (lower three rows in Table 4). Dots indicate time to settle to within 5% of response final value. 1.1250 arm lengths overall excursion amplitude.

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Fig. 7

RMS (solid lines) and NRMS (dashed lines) finger tracking errors and CoM–BoS deviations (solid lines) with 95% confidence intervals (dotted lines). For tracking errors (Figs. 7(a) and 7(b)), dots (RMS error) and stars (NRMS error) correspond to errors computed from the ETF gains and phase lags (dots in Figs. 4(a) and 4(b)), while the solid and dashed lines correspond to those computed by the fitted analytical transfer function gains and phase lags (solid lines in Figs. 4(a) and 4(b)). For CoM–BoS deviations (panels C and D), dots correspond to deviations computed from the ETF gains and phase lags (dots in Figs. 4(c) and 4(d)), and solid lines represent fitted equations of the form k1 fik2+k3. The lower 95% confidence bound for AP CoM–BoS deviation is zero. 1.1250 arm lengths overall excursion amplitude.

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