The journal of spinal cord medicine · 2024
Validation of a data logger for measuring standing time and seat angles for community-based standing devices.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wacek Amber, Truty Timothy, Jaramillo Jeffrey, Goldish Gary, Sauerbrey Matthew, Mattson Michelle, Looft John M, Olney Christine, Kiratli B Jenny, Hansen Andrew
Аннотация
CONTEXT: Little is understood about community-based standing device use and the impact of standing on health outcomes (e.g. pressure injury) in those living with spinal cord injury (SCI). This project reports on the accuracy of a commercially available data logger for measuring standing time and seat angle.
METHODS: A standing frame and a standing manual wheelchair were each instrumented with a commercially available data logger and each was tested by an non-disabled participant. Standing time in the standing frame was calculated from the data logger and compared to a user-recorded standing log over a two-month period in a laboratory environment. The standing wheelchair's seat angle was calculated using motion capture and compared to the calculated seat angle from the data logger. Average seat interface pressures were also captured during the testing of the standing wheelchair.
RESULTS: The data logger demonstrated high accuracy (99.99999%) in classifying sitting and standing in the standing frame when compared to a user-recorded standing log. The wheelchair seat angle calculated from the data logger demonstrated a high level of agreement with the motion lab calculations of seat angle (ICC = 0.96 (0.95, 0.97)). The data logger seat angle results also demonstrated strong relationships to average seat pressure and rear dispersion index, measures relevant to pressure injuries.
CONCLUSIONS: The data logger appears to be an appropriate tool for determining standing time and seat angle in standing devices, which may aid clinicians and researchers to better understand the use and impact of standing technologies on health outcomes.
METHODS: A standing frame and a standing manual wheelchair were each instrumented with a commercially available data logger and each was tested by an non-disabled participant. Standing time in the standing frame was calculated from the data logger and compared to a user-recorded standing log over a two-month period in a laboratory environment. The standing wheelchair's seat angle was calculated using motion capture and compared to the calculated seat angle from the data logger. Average seat interface pressures were also captured during the testing of the standing wheelchair.
RESULTS: The data logger demonstrated high accuracy (99.99999%) in classifying sitting and standing in the standing frame when compared to a user-recorded standing log. The wheelchair seat angle calculated from the data logger demonstrated a high level of agreement with the motion lab calculations of seat angle (ICC = 0.96 (0.95, 0.97)). The data logger seat angle results also demonstrated strong relationships to average seat pressure and rear dispersion index, measures relevant to pressure injuries.
CONCLUSIONS: The data logger appears to be an appropriate tool for determining standing time and seat angle in standing devices, which may aid clinicians and researchers to better understand the use and impact of standing technologies on health outcomes.