Industry Talk    AULON545
The Application of Generative Software in the Design of Electroencephalogram (EEG) Headset
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The research, design engineering, and development of a wireless ambulatory Electroencephalogram (EEG ) headset that utilises Brain Computer Interface (BCI) and Functional Electrical Stimulation (FES) presents a wide range of complex requirements. The team responsible for developing this wireless ambulatory EEG headset is focusing on making the device suitable for patient-managed neurorehabilitation within community (at homes or community centres). Unlike existing commercial EEG headsets, this would be the first device created particularly for unassisted (nonprofessional) usage by patients (or their caregivers) with restricted motor function or with chronic pain. These conditions may be the result of spinal cord injury and/or stroke. This approach provides benefits not only to Healthcare providers (such as occupational therapists) in terms of resource allocation, but also to patients and caregivers by providing access to device that can be used in familiar surroundings and at times that suit. The main challenges that benefit from the application of Fusion 360, generative design, and ReCap are: 1) developing form and structures that are adaptable to range of head sizes and geometries; 2) developing a structure that optimises the location and placement of electrodes; 3) reduction of material usage of key headset components; 4) influences the design with the aim of enhancing comfort, functionality, durability, and interaction. The demonstration will show examples of concept development of the device, ranging from digital to physical test beds that test the interaction between a variety of heads, mechanical properties of the headsets and electrodes. Traditional and rapid prototyping processes have been used throughout the development and where appropriate, these have been tested and evaluated using human factors methods and tools. The interaction and placement of the device is critical to the rehabilitation of the patient. Therefore, the device has to intuitive to use and reliable throughout its application. It is also expected that the device would be used by more than one patient, therefore it has to be easily maintained and serviced. The project is aligned with Engineering and Physical Science Research Council's delivery plan in the area of improving prevention and public health. It fits within Healthcare technologies strategic plan for optimising treatment and creating patient-specific predictive models that integrate medical knowledge and knowledge of an i

Key Learnings

  • Disseminate good practice and application of generative and image/form capture tools
  • Apply software tools to a variable human factors specification
  • Benefit from other CAD, data capture applications, and knowledge of generative design expertise
  • Use CAD tools to directly benefit the quality of life for patients and caregivers




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