Building on SPM1D technology with statistical parametric mapping

We are contributing to the existing SPM1D technology for our movement analysis platform by developing a colour mapping system and user interface that sits on top of SPM1D’s validated time-varying analysis tool.

One of the largest benefits of the SPM1D software is the ease of performing continuum statistical analyses of complex, time-varying biomechanical data. With our enhancements, users are provided a complete waveform analysis informing them of the direction of statistically significant differences between two sets of time series data as well as the magnitude (colour map software).  This provides an added layer of objectivity and inter-tester agreement in the analysis of time-varying clinical gait data.

The potential benefits:

1. Users do not need to deliberate over which 0D (i.e., discreet mean, max, min, etc.) variables to analyse when performing time-varying analysis.

2. Users are able to analyse movement data in a cascading manner, from the 3-component joint to the 1-component joint level (e.g. flex-ion/extension) and back with relative ease.

3. Users are able to identify, in order, which statistical differences are the most meaningful (via the colour map). This provides them with a compass for potential interventions.

The benefit of SPM1D is that it protects a clinician or researcher from making both type 1 and type 2 errors - identifying something that is not there, or missing something that is there. The colour mapping system and user interface allows clinicians with minimal statistical and computation experience to use this software with relative ease.

We have received 100% positive feedback from clinicians to date. With continued funding, we see this becoming a staple to clinical gait analysis for years to come.

Significantly reducing clinical timeframes from 30 hours to 15 minutes

We are also building upon OpenSim’s Residual Reduction Algorithm in concert with direct collocation (OpenSim Moco). The residual reduction algorithm enables the manipulation of the laws of physics to optimise an individual’s movement patterns (joint angles and velocities) to reduce the forces known to lead to joint or musculoskeletal and prostheses breakdown. This is relevant for, but is not limited to, osteoarthritis, arthroplasty, amputee, sport injury, cerebral palsy and stroke patients.

With our direct collocation optimisation algorithm, we have accelerated this process to fit within a clinically relevant timeframe, which is now approximately 10 to 15 minutes. Without direct collocation, the timeline would be 20-30 hours.

Figure 1: Phase one (left) identifies the movement pathology. Phase 2 (Right) provides a physics-based simulation to optimise the movement strategy so as to manage or eliminate the movement’s pathology.

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