OpenBalance ⚖️🔓
An Open-Platform, Multi-Cell Framework for Unconstrained Posturography and Balance Assessment
OpenBalance is an open-source, hardware-agnostic framework designed to democratize advanced biomechanical balance assessment. By breaking the vendor lock-in of proprietary, high-cost medical devices, OpenBalance enables research laboratories, sports facilities, and clinical institutions to implement a highly precise, flexible posturography system using customizable distributed force cells.
Unlike conventional monolithic force plates or rigid four-quadrant systems (such as Tetrax), OpenBalance introduces a novel methodological approach using a multi-cell array (e.g., 4x4 matrix). This architecture allows for unconstrained foot placement, ensuring subjects can adopt their natural, anthropometrically comfortable stance—which is particularly crucial in orthopedic rehabilitation (e.g., post-operative hip and knee arthroplasty).
🚀 Key Features
- Open Architecture & No Vendor Lock-In: Pure open-source software (Python/NumPy) and flexible hardware principles. No encrypted data structures, no hidden subscription walls.
- Unconstrained Stance & Variable Geometry: Supports custom-positioned, mechanically decoupled sub-platforms. The software dynamically handles coordinate transformation via geometric offsets.
- Cascading Mathematical Framework: Implements a rigorous two-stage Center of Pressure (COP) calculation (localized sub-segment COPs fused into a global COP) based on established biomechanical models (Winter, 2009).
- Decoupled Clinical Metrics: Independently quantifies static postural alignment/deficits via the Weight Distribution Index (WDI) and dynamic equilibrium stability (Postural Sway).
- High Dynamic Precision: Designed for discrete, low-mass load cells to bypass the inertial mass artifacts of heavy force plates and the shear-force limitations of pressure-sensing mats under dynamic perturbations.
📐 Mathematical Principle
OpenBalance handles the spatial data fusion of distributed force cell arrays. The global COP is computed as a force-weighted average of the localized sub-platform coordinates, mapped into a unified global coordinate system:
$$X_{global} = \frac{\sum_{i=1}^{4} \left( (X_{i,local} + X_{off,i}) \cdot F_i \right)}{F_{total}}$$
Where $X_{off,i}$ represents the deterministic geometric offset of the independent sub-platform from the absolute geometric origin $(0,0)$.
🛠️ Repository Contents
This repository contains the core methodological framework and open-source assets:
/data: Testdatasets./docs: Published Paper./hardware_concept: PDF Document for the dimension./src: Python algorithms utilizing NumPy for element-wise, vectorized data processing (localized/global COP calculation, and WDI extraction).
🤝 Contributing & Open Science
This project is a scientific initiative to open up posturography for researchers and sports scientists worldwide. We welcome contributions regarding:
- Signal processing pipelines (e.g., advanced filtering techniques).
- Real-time visualization dashboards (Python/Dash/Streamlit).
- Hardware interface integrations (ADC data streaming, firmware).
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Metadata
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