Edelle [Edee] Field-Fote’s, PT, PhD, FAPTA, journey to becoming a physical therapy researcher began with a desire to help one patient. Now, as an established expert in spinal cord injury research, she envisions the transformative role that artificial intelligence is poised to play in the future of physical therapy.

Her passion for research was initially sparked by an encounter with one of her first patients, a young man who had recently experienced a spinal cord injury. Reflecting on that pivotal moment, she recalls, “I remember thinking, ‘If there’s anyone in my career that I can help, I hope it will be this person.'” This early experience laid the groundwork for her future research pursuits. As she advanced in her PhD studies at Washington University in St. Louis, she became intrigued by the connection between turtle scratching behavior and the circuits underlying human walking. This behavior in turtles is controlled by spinal cord circuits that are effective even after a complete transection that cuts of information from the brain. Her PhD studies ultimately guided the direction of her research. Today, her work focuses on neuromodulation, using non-invasive stimulation to change the excitability of brain and spinal circuits. When combined with motor training programs, this approach can enhance walking function and hand function in people with spinal cord injury.

As her work continues to evolve, so do the boundaries of physical therapy research. She envisions AI playing a crucial role in advancing patient care. She believes AI’s potential lies in its ability to analyze vast amounts of data from real-world settings, providing insights to physical therapists that were previously out of reach. For instance, AI can enable the tracking and analysis of outcomes in large groups of patients, helping to identify which interventions are most effective for specific patient characteristics. This means AI can both enhance patient treatment approaches and provide insights to inform practice guidelines used by physical therapists.

Edelle notes, “I do think that we have a lot of very effective interventions, but we don’t really know how effective they are and who they’re effective for.” By leveraging AI, the development of more accurate and evidence-based practice guidelines becomes possible. Currently, practice guidelines are “based on relatively small studies, and sometimes not the most well-designed studies, because we just don’t have enough of them.” However, AI can analyze large datasets from real-world physical therapy cases, combining them with existing studies to provide optimized clinical practice guidelines.

As AI advances and contributes to clinical practice guidelines, there is also a need to update DPT curricula accordingly. Edelle emphasizes, “AI will give us the ability to track outcomes in large groups of people who receive interventions, which will, in turn, help us refine our educational approaches to ensure that future physical therapists are equipped with the most effective tools and knowledge.” The integration of AI into physical therapy education holds significant implications for preparing the next generation of practitioners.

Utilizing AI to help generate evidence-based physical therapy practice presents a potentially transformative shift in improving patient care on a large scale. As Edelle aptly puts it, “AI is going to make a tremendous difference— and the future of physical therapy will be all the better for it.”