At a glance
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Changes in User Satisfaction and Quality of Life Following 4 Weeks of Instrumented Standing Frame Intervention in Children With Disabilities - a Feasibility Intervention Study
In Brief
A clinical study evaluating PONDUS® for Functional Disability. Completed, enrolled 20 participants across 1 site.
Detailed Summary
Standing frames have existed for a long time and are well-established medical devices used to allow weight bearing in standing for persons who are unable to stand independently. Documenting the effectiveness of interventions using standing frames is complex. The current evidence base for their use is limited due to studies of low to moderate quality and small effects documented. Providing real-time feed-back on force and position and thus continuous tracking of the intensity allows for informed decision making about the support provided by the standing frame in clinical settings, thereby making it possible to document the potential setup for optimal support and potential association between the intensity and positive effects of the standing frames. The objective of the study is to document potential short-term benefits on a) patient satisfaction and health-related quality of life and b) changes in prescription from the prescribing therapist of the use of standing frames in children with standing disabilities when PONDUS®, a digital product used to assess the force applied during standing in a R82 standing frame is applied opposed to current practice. The study is a one-arm feasibility intervention study using participants as their own controls. The study will include 15 children with functional disabilities who currently uses a standing frame.
Study Details
Timeline
Interventions
PONDUS® is a CE-marked medical device to support the positioning of the user in a R82 standing frame. PONDUS® is designed as a pair of instrumented foot plates and an app as an external display. PONDUS® gives individual readings from the right and the left plate telling how much force is applied to each plate by combining high frequency data from three pressure sensors in each plate. The data is displayed in the app as a time series graph and can also be exported.