July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Optimizing the accuracy of activity monitors in visually-impaired older populations
Author Affiliations & Notes
  • Rohan P Bajaj
    Dana Center for Preventative Ophthalmology, Johns Hopkins Wilmer Eye Institute, Baltimore, Maryland, United States
  • Lisa Dillon
    The George Institute for Global Health, UNSW, Sydney, New South Wales, Australia
  • Pradeep Y Ramulu
    Dana Center for Preventative Ophthalmology, Johns Hopkins Wilmer Eye Institute, Baltimore, Maryland, United States
  • Anne Tiedemann
    Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia
  • Kirsten Jakobsen
    The George Institute for Global Health, UNSW, Sydney, New South Wales, Australia
  • Kris Rogers
    The George Institute for Global Health, UNSW, Sydney, New South Wales, Australia
  • Lisa J Keay
    The George Institute for Global Health, UNSW, Sydney, New South Wales, Australia
  • Footnotes
    Commercial Relationships   Rohan Bajaj, None; Lisa Dillon, None; Pradeep Ramulu, None; Anne Tiedemann, None; Kirsten Jakobsen, None; Kris Rogers, None; Lisa Keay, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 5184. doi:
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    • Get Citation

      Rohan P Bajaj, Lisa Dillon, Pradeep Y Ramulu, Anne Tiedemann, Kirsten Jakobsen, Kris Rogers, Lisa J Keay; Optimizing the accuracy of activity monitors in visually-impaired older populations. Invest. Ophthalmol. Vis. Sci. 2018;59(9):5184.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Activity monitors have been used to objectively measure physical activity and its association with visual impairment in low vision populations. However, there is limited understanding of the accuracy of activity monitors in this population. This study investigated the accuracy of activity monitors compared with manual step counting and sought to find the most accurate placement for the device.

Methods : 32 individuals with low vision were recruited: 20 (63%) were female, median visual acuity was 1.48 logMAR, average age was 74 years ± 2 (standard deviation, SD), average BMI was 29.8 ± 6.8 (SD), and 44% of participants used an assistive device. ActiGraph activity monitors were secured bilaterally on the wrists, ankles, and hips of each participant, who then walked a flat, linear course in their home at a comfortable pace for 4 minutes, using any necessary assistive device such as a long cane, support cane, or guide dog. Steps were counted using a hand-held tally counter. Step data from the 4-minute period were downloaded using the standard and low frequency filters at 1 epoch/second through the 'Actilife' ActiGraph software.

Results : Average distance for the test course was 10.9 ± 3.4 meters and participants completed an average of 368 ± 68 (SD) steps during the 4 minutes. The mean number of steps recorded by the two bilaterally-worn devices was taken at each location. On average, ankle, hip, and wrist activity monitors detected 85% (interquartile range (IQR): 76-94%), 56% (IQR: 39-85%), and 56% (IQR: 43-69%) of the actual, directly observed steps when using the standard ActiGraph filter. Detected steps more closely matched directly observed steps for all placement sites when the low-frequency ActiGraph filter was applied: 101.4% (IQR: 98.7-104.3%) at the ankle, 94.0% (IQR: 84.9-100.9%) at the hip, and 83.8% (IQR: 72.1-93.7%) at the wrist.

Bland-Altman plots showed greater levels of agreement between ActiGraph-recorded and observed steps at faster walking speeds.

Conclusions : Our results demonstrate that the most accurate location of activity monitor placement is the ankle and that if the low-frequency filter is used, then the level of agreement becomes more acceptable on the wrist and hip. Further work is needed to ensure that accurate data are being obtained, particularly on individuals with severe visual impairment and those with slow walking speeds.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

Bland-Altman plots with low-frequency ActiGraph filter

Bland-Altman plots with low-frequency ActiGraph filter

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