Applications of AI in the medical design process Paxman Research and Innovation Centre: Exhibition
Barbara Hepworth Building, School of Arts and Humanities. 29 January – 12 February 2024
Jonathan Binder, J.binder@hud.ac.uk, University of Huddersfield, England Riley Irving, u2162750@unimail.hud.ac.uk, University of Huddersfield, England Rilwan Olaosun, R.olaosun@hud.ac.uk, University of Huddersfield, England Ertu Unver, E.unver@hud.ac.uk, University of Huddersfield, England Keywords: AI, Concept generation, Medical design process, design methodology, Scalp cooling.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
Exhibition Narrative: In the Paxman research and Innovation Center, a team of researchers have been exploring the use of AI tools, particularly for concept generation tools within a SMART grant funded project through Innovate UK. Collaborating in this research Center between the University of Huddersfield and Paxman coolers. The aim of this project was to explore a plethora of AI tools, predominantly concept generation tools for the application of conceptualization for streamlining the design process in the medical field. The team has been evaluating Ai art software’s suitability in the medical design process, for developing concepts of Cooling caps and cap covers for Chemotherapy-Induced Alopecia. Other software’s were used, both free and paid (professional). Using the design principles taught at the University of Huddersfield, the team has experimented with the various tools/ functionalities of the free and paid software’s tools in the various stages of the design process. Using a different array of art styles from pen, pencil, computer rendering and photorealism. From the design council, the double diamond process is explored, whereby the various tools are evaluated at the various stages of this method and recommendations are provided to where these tools could be used. Including in the research phase, ideation, development, and delivery stages.
Figure 1: Exhibition space in the BHB Building Background: What is AI? Artificial Intelligence (AI) works as a simulation of human intelligence in machines that are created with the function of thinking and learning like the human mind. AI can be used to assist people in completing lots of different tasks. Machine learning (a subset of AI) allows the AI to improve how they complete certain tasks, so the experience of the user is constantly improving. How does AI Image generation work? AI image generators are AI systems that use deep learning techniques, specifically Generative Adversarial Networks (GANs), to create completely new original images. GANs consist of two neural networks. The first network is the generator which generates the realistic images based on the text or image-based prompt given by the user, and the second is the discriminator which
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
differentiates between real images and those generated by the generator. The generator will keep generating images until the discriminator can’t differentiate between the generated image and real image. This is how the AI learns to develop these images to a realistic quality. How can designers use AI? Product designers can use AI image generation for a wide range of uses to aid the design process: - Generating ideas: combining unique elements that may not have been thought of. - Exploring different style options: can explore new visual aesthetics. - Testing concepts: rapidly test new concepts and re�ne from different options. - Saving time speeds up the beginning of the design process and allows the designer to focus on the finer details. What tools were used?
Figure 2: Various software’s used. Paxman Research and Innovation Center: Co-funded by Paxman and Huddersfield University, the teams are working on several research areas to help cancer patients manage side-effects during Chemotherapy. Some projects are shown below. 01: 3D printed personalized caps 02: Chemotherapy-Induced Peripheral Neuropathy 03: Chemotherapy-Induced Alopecia 04: Sustainable manufacturing 05: New areas of wearable cooling.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
Figure 3: Various research center project images. Supporting Literature: Exploring industry 4.0 applications, AI may have potential uses in reasoning and decision support on engineering and technical challenges [14]. Within Big data in the product lifecycle contains valuable information, such as customer preferences, market demands, product evaluation, and visual display. Using AI alongside big data approaches can inspire designers to quickly generate initial design schemes or even new product images [15]. There is an increasing emphasis on the design of functional products within education, a team of researchers developed a model using AI for undergraduate industrial design students [16]. Many researchers believe that AI can provide substantial improvements in all areas of healthcare from diagnostics to treatment [17]. Combining approaches from big data, industrial design approaches and healthcare appear to promise greater accuracy in diagnosis than the previous generation of automated tools for image analysis, known as computer-aided detection or CAD [18]. The teams at the University of Huddersfield and Paxman research and innovation Centre have been collaborating and working on a plethora of relevant literature that can support this research, where cranial studies, challenges of implementing CAD and software in SMEs, Patented designs and AI papers can be seen [1-13]. School of Arts and Humanities: Barbara Hepworth building. In the University of Huddersfield, there are exhibition spaces in the atrium used for local and international exhibitions where staff, students and industry can showcase ongoing research projects such as this.
Photos of the Barbara Hepworth building and exhibition spaces: Huddersfield, UK.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
Evaluation of AI tools: Several tools were explored, most of which were image generators with explicit usefulness to the ideation processes seen in de�ne and develop, where initial concepts are generated and developed further. For other areas, text tools such as ChatGPT may be useful in coming up with ideas, finding problems or as initial drafts to be re-written. For Leonardo AI, this sketch-based generation tool can be used between the discover and de�ne phases for initial concepts based on sketches. For the development and prototyping phases, Dreamgaussian is useful for simple CAD models, and MurfAI was explored for delivery in dissemination phases for voice overs. Chat GPT - text based for Research: In this section, the team investigates the use of text-based AI tools, such as Chat GPT, for uses in the research phases of a project. Chat GPT is a chatbot developed by OpenAI based on a language model. This use of this tool is for discussions, using knowledge obtained from various resources on the internet, this approach, much like a literature review can be used to process a discussion on research topics. For this approach, we asked AI to tell us: ‘Tell me the AI perspective of why how you think AI can be useful in the medical design process in one Paragraph’. Response: ‘AI offers significant advantages in the medical design process by streamlining and enhancing various stages of development. Through advanced machine learning algorithms, AI can analyze vast amounts of medical data, identify patterns, and predict outcomes, facilitating more informed decision-making. In medical imaging, AI can improve diagnostics by accurately interpreting complex images, aiding in early detection and precise treatment planning. Additionally, AI-driven simulations and modeling contribute to the design and optimization of medical devices and treatment protocols, potentially accelerating the development cycle. By automating repetitive tasks, reducing errors, and leveraging data-driven insights, AI not only enhances the efficiency of the medical design process but also has the potential to improve patient outcomes and advance the overall quality of healthcare solutions. Our perspective: Exploring a plethora of tools, the team agrees there are many applications for AI, including data management, analysis tools and algorithm development, even programming and app development. However, the team is explicitly exploring the generic product design applications in medical design and development. With this, the team believes one of the biggest benefits for Product designers is to use AI concept generation tools during the ideation phase. This could be for ideation mood boards, initial concepts for stakeholder communications, or developing ideas from completely out of the box concepts. The main benefits could be to limit time wasted during the initial ideation phase of a project to help get investors or stakeholders on board, and to explore many ideas in a little time frame, however we don›t believe this should replace the ideation phase for Product designers. More of a collaborative effort.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
After evaluating chat-based tools such as ChatGPT, the team concluded that they could be useful for basic draft writing in projects and web searches with basic arguments for the early phases of a project such as project or bid writing as a starting point. However, this shouldn’t be used to replace academic writing in general. Examples for this rationale include, on occasion, the results presented can provide irrelevant or erroneous information. However, practically for an SME, it can be a useful tool. There are still concerns for its use in academia, where it lacks the critical reviewing of information. Methodology: The Design Council’s Double Diamond [19] clearly conveys a design process to designers and non-designers alike. The two diamonds represent a process of exploring an issue more widely or deeply (divergent thinking) and then taking focused action (convergent thinking). Discover (Research), Define (Ideation) Develop (development) Deliver (deliver a solution). This method is widely used in Product Design. In this research, the team has explored where various tools may �t into the design process. Below visualizes how that might look:
Figure 4: Double Diamond process and AI Tools for medical design.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
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Conclusion: Can AI benefit the wearable medical design process? The integration of Artificial Intelligence (AI) in industrial design has emerged as a transformative force, offering unparalleled opportunities to enhance efficiency, innovation, and overall productivity. AI technologies can revolutionize every stage of the design process, from ideation to prototyping and manufacturing. Through advanced algorithms and machine learning capabilities, AI enables designers to analyse vast amounts of data, identify patterns, and generate valuable insights that contribute to informed decision-making. In essence, the incorporation of Artificial Intelligence in industrial design holds the promise of ushering in a new era of creativity, efficiency, and sustainability. As technology continues to evolve, its positive impact on the design landscape is poised to grow, shaping a future where human ingenuity and AI collaborate harmoniously to push the boundaries of innovation. While the transformative potential of AI in industrial design is evident, it is crucial to navigate ethical considerations, privacy concerns, and the potential displacement of certain job functions. Striking a balance between human creativity and AI-driven efficiency will be essential to maximize the benefits of this technological synergy. However, the designer should not become too dependent on these generation tools as these are not fully realized design concepts and good ideas currently cannot be finalised without human efforts, even with AI, particularly in industrial settings. Recommendations: A hybrid approach of various tools at different stages of the design process I.e. textbased tools in research, concept generation in ideation, CAD based in development and dissemination tools for delivery.
Figure 6: Research project team. References: [1]
[2]
Challenges of Integrating Industrial Product Design CAD Packages in Commercial New Product Development in SME Settings Kopattil, G., Binder, J., Unver, E., Huerta, O. & Bandla, A., 13 Jan 2024, In: CAD Computer Aided Design. 21, 5, p. 759-768 10 p. Investigation of a New Framework for Mass Customization Within Healthcare Orientated Human Head Data Collection for Healthcare Professionals Binder, J., Unver, E., Benincasa-Sharman, C., Yee, YE. & Bandla, A., 1 May 2024, In: Computer-Aided Design and Applications. 21, 3, p. 499-509 11 p.
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
[3]
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[8]
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[11]
[12]
[13]
Medical Design & Development: Paxman coolers Chemotherapy-Induced preventions Jonathan Binder (Organiser), Ertu Unver (Participant), Gayathri Kopattil, Aishwarya Bandla & Richard Paxman Investigation of Mass Customization within Healthcare Orientated Human Head Data Collection for Chemotherapy-Induced Alopecia Prevention Binder, J., Unver, E., Benincasa-Sharman, C., Yee, Y-E. & Bandla, A., 10 Jul 2023, Proceedings of 20th Annual International CAD Conference: CAD'23. CAD Solutions, p. 362-367 6 p. (CAD Proceedings; vol. 2023). Scalp Cooling Cap Design & Development: According to AI, Using Midjourney Binder, J. & Unver, E., 1 Dec 2023, (Unpublished) 50 p. Are traditional head size and shape measurements useful in modern medical design? A literature review Binder, J., Unver, E. & Huerta, O., 18 Aug 2022, In: Journal of Health Design. 7, 2, p. 500-506 7 p. Human head analysis for mass customisation in medical design: A pilot study Binder, J., Unver, E. & Huerta Cardoso, O. I., 18 Aug 2022, In: Journal of Health Design. 7, 2, p. 507-515 9 p. Patent for Wearable cryo-compression device to address an unmet clinical need – Chemotherapy-Induced Peripheral Neuropathy Unver, E., Sundar, R., Bandla, A., Binder, J. & Burke, P., 12 May 2022, IPC No. A61F7/02, Patent No. WO2022098309A1, Priority date 5 Nov 2020, Priority No. SG10202011037WA The challenges of implementing design research within SME based medical product development: Paxman scalp cooling case study Unver, E., Clayton, J., Clear, N., Huerta, O., Binder, J., Paxman, C. & Paxman, R., 1 Jun 2022, In: Design for Health. 6, 1, p. 4-27 24 p. A Parametric Product Design Framework for the Development of Mass Customized Head/Face (Eyewear) Products Bai, X., Huerta Cardoso, O. I., Unver, E., Allen, J. & Clayton, J., 10 Jun 2021, In: Applied Sciences (Switzerland). 11, 12, 20 p., 5382. A Limb Hypothermia Wearable for Chemotherapy-Induced Peripheral Neuropathy: A Mixed-Methods Approach in Medical Product Development Binder, J., Unver, E., Clayton, J., Burke, P., Paxman, R., Sundar, R. & Bandla, A., 15 Dec 2020, In: Frontiers in Digital Health. 2, 14 p., 573234. An Approach of Rapid Tooling for Scalp Cooling Cap Design Unver, E., Binder, J., Kagioglou, M. & Burke, P., 1 Mar 2020, In: Computer-Aided Design and Applications. 17, 2, p. 337-347
Y.P. Tsang, C.K.M. Lee, Artificial intelligence in industrial design: A semiautomated literature survey, Engineering Applications of Artificial Intelligence, Volume 112, 2022, 104884, ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2022.104884 Quan, H.; Li, S.; Zeng, C.; Wei, H.; Hu, J. Big Data and AI-Driven Product Design: A Survey. Appl. Sci. 2023, 13, 9433. https://doi.org/10.3390/app13169433
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on
McCardle, J.R. The Challenge of Integrating AI & Smart Technology in Design, Education. International Journal of Technology and Design Education 12, 59–76 (2002). https://doi.org/10.1023/A:1013089404168
Binder, J. Irving, R. Olaosun, D. Unver, E.
Applica�ons of AI in the medical design process: Exhibi�on