Advisor Information
Brian Knarr
Location
Dr. C.C. and Mabel L. Criss Library
Presentation Type
Poster
Start Date
3-3-2017 2:15 PM
End Date
3-3-2017 3:30 PM
Abstract
Balance disorders impact millions of people causing substantial impact on quality of life due to psychological and physical hardships associated with poor balance. However, a clinically relevant, low cost, self-service system in detecting such disorders does not exist. Previous research has shown the built in accelerometer and gyroscope sensors of a smart phone to be valid tools in detecting standing balance performance using traditional linear analysis, however, such a system has yet to be proven useful in detecting dynamic postural variability. Indeed, more quantitative methods than are typically used in clinical settings are necessary for early detection of poor postural variability. Therefore, the purpose of this study is to determine if a low cost, self-service mobile sensor system is reliable in detecting balance performance during standing and walking tasks. This study will use non-linear analysis, through the calculation of sample entropy during static standing, and maximum Lyapunov exponent’s during dynamic walking. A smart phone application will be developed to create a simple user interface and implement the objectives of this study. Participants in this study will perform the six stances of the Balance Error Scoring System (BESS) test for a standing balance examination, and then will proceed to a two-minute walking trial for dynamic data collection. We hypothesize that through the collection of continuous mobile sensor data, dynamic postural variability can be assessed and will provide a low cost alternative to current balance testing.
Quantifying Static and Dynamic Stability Using Mobile Sensors
Dr. C.C. and Mabel L. Criss Library
Balance disorders impact millions of people causing substantial impact on quality of life due to psychological and physical hardships associated with poor balance. However, a clinically relevant, low cost, self-service system in detecting such disorders does not exist. Previous research has shown the built in accelerometer and gyroscope sensors of a smart phone to be valid tools in detecting standing balance performance using traditional linear analysis, however, such a system has yet to be proven useful in detecting dynamic postural variability. Indeed, more quantitative methods than are typically used in clinical settings are necessary for early detection of poor postural variability. Therefore, the purpose of this study is to determine if a low cost, self-service mobile sensor system is reliable in detecting balance performance during standing and walking tasks. This study will use non-linear analysis, through the calculation of sample entropy during static standing, and maximum Lyapunov exponent’s during dynamic walking. A smart phone application will be developed to create a simple user interface and implement the objectives of this study. Participants in this study will perform the six stances of the Balance Error Scoring System (BESS) test for a standing balance examination, and then will proceed to a two-minute walking trial for dynamic data collection. We hypothesize that through the collection of continuous mobile sensor data, dynamic postural variability can be assessed and will provide a low cost alternative to current balance testing.