Introduction: Novel implementation of a force sensor during a sit-to-stand measure of dynamic cerebral autoregulation (dCA) has been shown to measure the exact moment an individual stands up from a chair, called arise-and-off (AO). Traditional measures estimate time delay (TD) before the onset of the dCA response from the verbal command to stand. We hypothesized that using a force sensor to measure AO would significantly improve the accuracy of the TD measure compared to estimating from verbal command. Methods: Middle cerebral artery blood velocity (MCAv) and mean arterial pressure (MAP) were measured simultaneously during three sit-to-stand measures of dCA. Participants were seated for 60 seconds, then performed a sit-to-stand and the force sensor detected AO. TD was calculated as the time from AO until an increase in cerebrovascular conductance (CVC = MCAv/MAP). TD was also calculated from verbal command to stand. Results: Sixty-five participants completed the study: twenty-five young adults (age 25±2 years), twenty older adults (age 61±13 years), and twenty individuals with stroke (age 60±13 years). There was a significant difference in TD when using AO compared to estimating (F-value=49.9, p<0.001). Estimated TD introduced ≈17% measurement error. Average TD measurement error was not related to age (r =-0.04, p=0.76) or history of stroke (r=0.01, p=0.96). Discussion: The addition of a force sensor to detect AO during a sit-to-stand procedure showed a significant difference in the TD dCA measurement. Our data support the implementation of a force sensor during sit-to-stand dCA measures in healthy adults across all ages and after stroke.

The authors have declared no competing interest.

NCT04673994

https://physoc.onlinelibrary.wiley.com/doi/10.14814/phy2.15244

AW was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health (T32HD057850) and the American Heart Association Predoctoral Fellowship Grant (898190). EV and SB were supported in part by the National Institute on Aging for the KU Alzheimers Disease Research Center (P30 AG072973). REDCap at University of Kansas Medical Center is supported by Clinical and Translational Science Awards (CTSA) Award # ULTR000001 from National Center for Research Resources (NCRR). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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