The work included problem definition, investigation of candidate methods and technologies, system architecture design, sensor design and optimization, the establishment of an embedded system platform for data processing and communication, and finally, the clinical investigation trials, which entailed data collection and analysis, system validation and dissemination and exploitation.
The successful results achieved include the design of intra-socket light-weight, printed, flexible, wearable multi-point pressure and shear/loss of friction sensors for the measurement of dynamic load conditions, and the accomplishment of the prototype system integrating the sensors, sensor electronics, firmware, and application software, as described below.
- On the sensor system development: The final choice for optimal pressure sensor strip and shear/loss of friction sensor design were evaluated by extensive lab testing and performance evaluation. Meanwhile, the electronic system for sensor data acquisition, processing and communication was optimized following pilot tests under real-use conditions. This resulted in a flexible, retrofittable, wearable sensor system that is untethered and capable of global mapping of intra-socket pressures and other relevant data measurements.
- On the data analysis: The data acquisition system was developed to collect QTSS pressure and shear sensor information via Analog-to-Digital Converter as voltage outputs. The work on data analysis emphasized sensor behaviour modelling, characterization and utilizations of data features and identification of models and algorithms for data treatment. The initial design for smart sensor data analysis includes MLP (Multi-Layer Perceptron) and HMM (Hidden Markov Model) for sensor and biomechanical modelling. It creates basic understanding of intra-socket dynamic operational conditions. To allow (re)generating the intra-socket pressure conditions without direct clinical trials, the OpenSim tool was used to capture the overall operational conditions of amputee behaviour. AnsysNSYS was then employed to elicit the pressure distribution inside socket using Finite Element Analysis (FEA) in simulated static and dynamic test conditions. To support the FEA model, the same test conditions and the sensors developed were deployed in a model socket and tested in a Stewart Manipulator.
- On the comfort assessment and socket optimization: A protocol for soft tissue measurement and comparison with a simulation-based method was established in Abaqus to evaluate the interaction between the residual limb and the socket. See Figure 3, below. The work on virtual socket generation was finished. A Decision Support System (DSS) based on a fuzzy-logic inference engine (IE) to support prosthetists in socket rectification decisions was achieved.
- On the overall system integration: A reference scheme for sensor deployment inside prosthetic sockets was developed, allowing the mapping of measurement data in both 2D and 3D representations. The design of a new data management platform for clinicians was also refined. The key features of the SocketSense data management system include a backend for data computation and storage, and a frontend system for the visualization of 3D pressure distributions and data presentation.
On the clinical trial investigation: The clinical investigation was designed, and the protocol to be conducted during the trials was defined. Various other documentation required by the medical devices and health regulatory agencies in the UK and in Spain were also completed. The clinical investigation trials were conducted in the UK and Spain, upon which data analysis and system validation and verification were successfully executed.
Dissemination and exploitation of results was on-going throughout the project. The partners have produced a business plan for the exploitation of the successfully validated TRL5 device, generated numerous publications, attended and presented at a number of conferences and produced significant open access data.
