A Methodological Framework for Integrating Artificial Intelligence Agents in Medical Device Design : Integrating AI Agents in Medical Device Design

Tariq  Javid; Muhammad Faris; Mir Farooq  Ali; Muhammad Mansoor  Mughal; Asad  Saleem; Usama  Zahoor

Authors

Tariq Javid Hamdard University, Karachi, Pakistan
Muhammad Faris Hamdard University, Karachi, Pakistan
Mir Farooq Ali Marche, Polytechnic University, Ancona, Italy
Muhammad Mansoor Mughal Hamdard University, Karachi, Pakistan
Asad Saleem Hamdard University, Karachi, Pakistan
Usama Zahoor Hamdard University, Karachi, Pakistan

Keywords:

AI-enabled Healthcare, Artificial Intelligence, Artificial Intelligent Agents, Design Process, Learning, Medical Device

Abstract

An artificial intelligent (AI) agent uses sensors to perceive and actuators to act upon its task environment. The sensor module provides the perception of the task environment. The actuator module facilitates the agent’s performing actions in the task environment. This research extends the function of a medical device by embedding an AI agent in the medical device during the design process. The research methodology utilizes a generic AI agent with fundamental learning capability and an initial knowledge base. The ability to learn enables the generic AI agent to operate in the initially unknown task environment. After sufficient interactions with the task environment, the agent becomes more competent than its initial knowledge base. The clinical applications are demonstrated through the use of the AI-enabled medical device in surgical training and performance evaluation.

DOI: https://doi.org/10.59564/amrj/03.02/0010

Author Biographies

Tariq Javid, Hamdard University, Karachi, Pakistan

Professor and Chair, Department of Biomedical Engineering

Muhammad Faris , Hamdard University, Karachi, Pakistan

Assistant Professor, Department of Biomedical Engineering

Mir Farooq Ali, Marche, Polytechnic University, Ancona, Italy

PhD Scholar, Department of Information Engineering

Muhammad Mansoor Mughal, Hamdard University, Karachi, Pakistan

PhD Scholar/Senior Lecturer, Department of Biomedical Engineering and Electrical and Computer Engineering

Asad Saleem, Hamdard University, Karachi, Pakistan

Senior Lecturer, Department of Biomedical Engineering

Usama Zahoor, Hamdard University, Karachi, Pakistan

Lecturer, Department of Biomedical Engineering

References

Kringos D, Ivanković D, Barbazza E, Klazinga N, Brito Fernandes Ó. Health system performance assessment: embedding resilience through performance intelligence. International Journal for Quality in Health Care. 2024;36(1):mzae010.

DOI: https://doi.org/10.1093/intqhc/mzae010

Food and Drug Administration, Federal Food, Drug, and Cosmetic Act (FD&C Act 21), FDA 2018. https://www.fda.gov/regulatory-information/federal-food-drug-and-cosmetic-act-fdc-act/fdc-act-chapter-v-drugs-and-devices

Russell SJ, Norvig P. Artificial intelligence: A modern approach. Pearson; 2024.

Ogrodnik PJ. Medical device design: innovation from concept to market. Academic Press; 2019.

DOI: https://doi.org/10.1016/C2016-0-05027-1

Schoepen M, Vansteenkiste E, De Gersem W, Detand J. Systems thinking and designerly tools for medical device design in engineering curricula. Health Systems. 2023;12(4):461-71.

DOI: https://doi.org/10.1080/20476965.2022.2072778

Bravo E, Austin-Breneman J. Design for Implementation: A Medical Device Development Design Process. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2023 (Vol. 87349, p. V006T06A013). American Society of Mechanical Engineers.

DOI: https://doi.org/10.1115/DETC2023-114067

Lee JW, Daly SR, Huang-Saad A, Seifert CM. Start with problems or solutions? Medical device design in Industry and Academia. IEEE Access. 2020; 8:208623-42.

DOI: https://doi.org/10.1109/ACCESS.2020.3035966

Soltani N, ElAnsary M, Xu J, Sales Filho J, Genov R. Safety-optimized inductive powering of implantable medical devices: Tutorial and comprehensive design guide. IEEE Transactions on Biomedical Circuits and Systems. 2021;15(6):1354-67.

DOI: https://doi.org/10.1109/TBCAS.2021.3125618

Rivera AE, Gálvez BE, Assad GD, Prieto VL. A New Approach to Learning Basic Medical Device Design Through Challenge-Based and Experiential Learning. Revista Iberoamericana de Tecnologías del Aprendizaje: IEEE-RITA. 2023; 18(4):393-9.

DOI: https://doi.org/10.1109/RITA.2023.3324088

Reynolds P. Designing eco-friendly medical devices. IEEE pulse. 2022; 13(4):24-6.

DOI: https://doi.org/10.1109/MPULS.2022.3191817

Martínez-Sellés M, Marina-Breysse M. Current and future use of artificial intelligence in electrocardiography. Journal of Cardiovascular Development and Disease. 2023; 10(4):175.

DOI: https://doi.org/10.3390/jcdd1004017

Abubaker MB, Babayiğit B. Detection of cardiovascular diseases in ECG images using machine learning and deep learning methods. IEEE Transactions on Artificial Intelligence. 2022; 4(2):373-82.

DOI: https://doi.org/10.1109/TAI.2022.3159505

Tariq J, Muhammad F, Hina I, Tayyaba K, Najam S, Muhammad B, Syeda B. Artificial intelligence based ECG for early detection of dysrhythmia. In 1st International Conference on Emerging Trends in Biomedical Engineering, Science and Technology (ICETBEST) 2024.

Alinsaif S. Unraveling arrhythmias with graph-based analysis: A survey of the MIT-BIH database. Computation. 2024;12(2):21.

DOI: https://doi.org/10.3390/computation12020021

Abdallah M. Design, simulation, and development of a biosensor for viruses detection using FPGA. IEEE Journal of Translational Engineering in Health and Medicine. 2021; 9:1-6.

DOI: https://doi.org/10.1109/JTEHM.2021.3055984

Sarkisian SV, Ishmael MK, Hunt GR, Lenzi T. Design, development, and validation of a self-aligning mechanism for high-torque powered knee exoskeletons. IEEE Transactions on Medical Robotics and Bionics. 2020; 2(2):248-59.

DOI: https://doi.org/10.1109/TMRB.2020.2981951

Nayar NU, Qi R, Desai JP. Toward the design and development of a robotic transcatheter delivery system for mitral valve implant. IEEE Transactions on Medical Robotics and Bionics. 2022; 4(4):922-34.

DOI: https://doi.org/10.1109/TMRB.2022.3215522

Payra S, Mahadevan K. Design, development, and evaluation of a bionic knee-ankle-foot orthosis retrofit for walking gait normalization. IEEE Transactions on Medical Robotics and Bionics. 2021; 3(3):825-37.

DOI: https://doi.org/10.1109/TMRB.2021.3093443

Gesta A, Achiche S, Mohebbi A. Design considerations for the development of lower limb pediatric exoskeletons: A literature review. IEEE Transactions on Medical Robotics and Bionics. 2023.

DOI: https://doi.org/10.1109/TMRB.2023.3310040

Sorriento A, Cafarelli A, Spinnato P, Russo A, Lisignoli G, Rabusseau F, Cabras P, Dumont E, Ricotti L. Design, development and validation of a knee brace to standardize the US imaging evaluation of knee osteoarthritis. IEEE Journal of Translational Engineering in Health and Medicine. 2021; 10:1-8.

DOI: https://doi.org/10.1109/JTEHM.2021.3137628

Faisal M, Sumaiya A, Ayesha H, Tariq J, Muhammad F, Jawad S. Critical thinking and problem solving intelligent agent for high-precision simulated image-guided cardiac interventions. In 1st International Biomedical and Digital Health Conference (IBDC) 2022.

Müller K, Hatvani J, Koller M, Goda MÁ. pyPCG: A Python toolbox specialized for phonocardiography analysis. Physiological Measurement. 2024.

DOI: https://doi.org/10.1088/1361-6579/ad9af7

Joshi G, Jain A, Araveeti SR, Adhikari S, Garg H, Bhandari M. FDA-Approved Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices: An Updated Landscape. Electronics. 2024; 13(3):498. DOI: https://doi.org/10.3390/electronics13030498

Ingvar Å, Oloruntoba A, Sashindranath M, Miller R, Soyer HP, Guitera P, Caccetta T, Shumack S, Abbott L, Arnold C, Lawn C. Minimum labelling requirements for dermatology artificial intelligence‐based Software as Medical Device (SaMD): A consensus statement. Australasian Journal of Dermatology. 2024.

DOI: https://doi.org/10.1111/ajd.14222

Shafik W. Wearable medical electronics in artificial intelligence of medical things. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things. 2024: 21-40.

DOI: https://doi.org/10.1201/9781003370321