SeeSway – A free web-based system for analysing and exploring standing balance data. (June 2018)

• Record Type: Journal Article
• Authors: Clark, Ross A.; Pua, Yong-Hao
• Is Part Of: Computer methods and programs in biomedicine. Volume 159(2018)
• Page Start: 31
• Page End: 36
• Publication Date: 2018-06
• Subjects: Posturography -- Balance -- Force platform -- Center of pressure -- Falls; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2018.02.019
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: SeeSway is a free website for analysing instrumented balance tests. Filtering: Wavelet, Butterworth and averaging filters. Standard Analysis: Techniques such as path length and range. Other analysis: Entropy, detrended fluctuation and wavelet. The program focuses on simple yet powerful data analysis. Abstract: Background and objectives: Computerised posturography can be used to assess standing balance, and can predict poor functional outcomes in many clinical populations. A key limitation is the disparate signal filtering and analysis techniques, with many methods requiring custom computer programs. This paper discusses the creation of a freely available web-based software program, SeeSway (www.rehabtools.org/seesway ), which was designed to provide powerful tools for pre-processing, analysing and visualising standing balance data in an easy to use and platform independent website. Methods: SeeSway links an interactive web platform with file upload capability to software systems including LabVIEW, Matlab, Python and R to perform the data filtering, analysis and visualisation of standing balance data. Input data can consist of any signal that comprises an anterior-posterior and medial-lateral coordinate trace such as center of pressure or mass displacement. This allows it to be used with systems including criterion reference commercial force platforms and three dimensional motion analysis, smartphones, accelerometers and low-cost technology such as Nintendo Wii Balance Board and Microsoft Kinect. Filtering options include Butterworth, weighted and unweighted moving average, and discrete wavelet transforms. Analysis methods include standard techniques such as path length, amplitude, and root mean square in addition to less common but potentially promising methods such as sample entropy, detrended fluctuation analysis and multiresolution wavelet analysis. These data are visualised using scalograms, which chart the change in frequency content over time, scatterplots and standard line charts. This provides the user with a detailed understanding of their results, and how their different pre-processing and analysis method selections affect their findings. Results: An example of the data analysis techniques is provided in the paper, with graphical representation of how advanced analysis methods can better discriminate between someone with neurological impairment and a healthy control. Conclusions: The goal of SeeSway is to provide a simple yet powerful educational and research tool to explore how standing balance is affected in aging and clinical populations.