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Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons with Multiple Sclerosis
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  • Brett Meyer ,
  • Jenna Cohen ,
  • Nicole Donahue ,
  • Sam Fox ,
  • Aisling O'Leary ,
  • Anna Jane Brown ,
  • Tyler VanDyk ,
  • Paolo DePetrillo ,
  • Melissa Ceruolo ,
  • Nick Cheney ,
  • Andrew Solomon ,
  • Ryan McGinnis
Brett Meyer
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Jenna Cohen
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Nicole Donahue
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Aisling O'Leary
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Anna Jane Brown
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Tyler VanDyk
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Paolo DePetrillo
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Melissa Ceruolo
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Nick Cheney
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Andrew Solomon
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Ryan McGinnis
University of Vermont

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Typical assessments of balance impairment are subjective or require data from cumbersome and expensive force platforms. Researchers have utilized lower back (sacrum) accelerometers to enable more accessible, objective measurement of postural sway for use in balance assessment. However, new sensor patches are broadly being deployed on the chest for cardiac monitoring, opening a need to determine if measurements from these devices can similarly inform balance assessment. Our aim in this work is to validate postural sway measurements from a chest accelerometer. To establish concurrent validity, we considered data from 16 persons with multiple sclerosis (PwMS) asked to stand on a force platform while also wearing sensor patches on the sacrum and chest. We found five (five) of 15 postural sway features derived from chest (sacrum) were significantly correlated with force platform-derived features, which is in line with prior sacrum-derived findings. Clinical significance was established using a sample of 39 PwMS who performed eyes-open, eyes-closed, and tandem standing tasks. This cohort was stratified by fall status and completed several patient-reported measures (PRM) of balance and mobility impairment. We also compared sway features derived from a single 30-second period to those derived from a one-minute period with a sliding window to create subject-specific distributions of each postural sway feature (SSD method). We find traditional computation of sway features from the chest is sensitive to changes in PRMs and task differences. Distribution characteristics from the SSD method establish additional relationships with PRMs, detect differences in more tasks, and distinguish between fall status groups. Overall, the chest was found to be a valid location to monitor postural sway and we recommend utilizing the SSD method over single-observation analyses.
2023Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering volume 31 on pages 2132-2139. 10.1109/TNSRE.2023.3267807