Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI's GPT-4 model.

Journal: Biology of sport
Published Date: Dec 13, 2023

Abstract

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI's Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model's ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model's potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition-specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback.

Authors

  • Ismail Dergaa
    Primary Health Care Corporation (PHCC), Doha, Qatar.
  • Helmi Ben Saad
    University of Sousse, Farhat HACHED hospital, Research Laboratory LR12SP09 «Heart Failure», Sousse, Tunisia.
  • Abdelfatteh El Omri
    Surgical Research Section, Department of Surgery, Hamad Medical Corporation, Doha, Qatar.
  • Jordan M Glenn
    Neurotrack Technologies, Redwood City, CA, United States.
  • Cain C T Clark
    College of Life Sciences, Birmingham City University, Birmingham, B15 3TN, UK.
  • Jad Adrian Washif
    Sports Performance Division, National Sports Institute of Malaysia, Kuala Lumpur, Malaysia.
  • Noomen Guelmami
    Department of Health Sciences (DISSAL), Postgraduate School of Public Health, University of Genoa, Genoa, Italy.
  • Omar Hammouda
    Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology: Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France.
  • Ramzi A Al-Horani
    Department of Exercise science, Yarmouk University, Irbid, Jordan.
  • Luis Felipe Reynoso-Sánchez
    Department of Social Sciences and Humanities, Autonomous University of Occident, Los Mochis, Mexico.
  • Mohamed Romdhani
    Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology: Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France.
  • Laisa Liane Paineiras-Domingos
    Departamento de Fisioterapia, Instituto Multidisciplinar de Reabilitação e Saúde, Universidade Federal da Bahia, Brazil.
  • Rodrigo L Vancini
    Centro de Educação Física e Desportos, Universidade Federal do Espírito Santo, Vitória, Espírito Santo, Brazil.
  • Morteza Taheri
    Department of Motor Behavior, Faculty of Sport Sciences, University of Tehran, Tehran, Iran.
  • Leonardo Jose Mataruna-Dos-Santos
    Department of Creative Industries, Faculty of Communication, Arts and Sciences, Canadian University of Dubai, Dubai, United Arab Emirates.
  • Khaled Trabelsi
    Research Laboratory Education, Motricité, Sport et Santé (EM2S) LR19JS01, High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax 3000, Tunisia.
  • Hamdi Chtourou
    Research Laboratory Education, Motricité, Sport et Santé (EM2S) LR19JS01, High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax 3000, Tunisia.
  • Makram Zghibi
    High Institute of Sport and Physical Education of Kef, Jendouba, Kef, Tunisia.
  • Özgür Eken
    Department of Physical Education and Sport Teaching, Inonu University, Malatya 44000, Turkey.
  • Sarya Swed
    Faculty of Medicine, Aleppo University, Aleppo, Syria.
  • Mohamed Ben Aissa
    Postgraduate School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
  • Hossam H Shawki
    Department of Comparative and Experimental Medicine, Nagoya City University Graduate School of Medical Sciences, Nagoya 467-8601, Japan.
  • Hesham R El-Seedi
    Department of Chemistry, Faculty of Science, Islamic University of Madinah, Madinah, 42351, Saudi Arabia.
  • Iñigo Mujika
    Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country, Leioa, Basque Country.
  • Stephen Seiler
    Department of Sport Science and Physical Education, University of Agder, Kristiansand, Norway.
  • Piotr Zmijewski
    Jozef Pilsudski University of Physical Education in Warsaw, 00-809 Warsaw, Poland.
  • David B Pyne
    Research Institute for Sport and Exercise, University of Canberra, Canberra, ACT, Australia.
  • Beat Knechtle
    Institute of Primary Care, University of Zurich, Zurich, Switzerland.
  • Irfan M Asif
    Department of Family and Community Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
  • Jonathan A Drezner
    Center for Sports Cardiology, University of Washington, Seattle, Washington, USA.
  • Øyvind Sandbakk
    Center for Elite Sports Research, Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.
  • Karim Chamari
    Higher institute of Sport and Physical Education, ISSEP Ksar Saïd, Manouba University, Tunisia.

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