600: Brad Williams - Using AI for Physical Therapy: What Worked and What Didn’t
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Using AI for Physical Therapy: What Worked and What Didn’t
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In this episode, Brad Williams shares his personal experience using AI as a tool for self-guided physical therapy, highlighting both its potential and its limitations. Drawing from years of dealing with chronic injuries, he focuses on two main issues: a long-term lower back problem and more recent knee pain.
For his back, Brad explains he’s been managing the effects of a herniated disc and multiple surgeries for nearly eight years, getting himself to about “93%” recovery through consistent routines and experimentation. Seeking that final improvement, he turns to AI for new ideas—specifically exploring sleep positioning, which he believes is the biggest trigger for his pain. AI recommends a “zero gravity” sleeping setup to reduce spinal pressure. Instead of investing in an expensive adjustable bed, Brad improvises with affordable wedges and pillows. The result is a noticeable improvement, bringing him close to “98%” recovery, making this a clear success story where AI offered a novel, effective solution he hadn’t tried before.
He then tests AI on a different issue—chronic knee pain. The AI suggests muscle imbalances, particularly involving the VMO (inner quad), and provides exercises targeting strength, stability, and mobility. While some of these recommendations align with his training style and initially help, his progress stalls and one knee worsens. Eventually, Brad consults a physical therapist, who identifies tightness in his IT band and quads as key contributors—something the AI did not emphasize. With targeted treatment like foam rolling and specific strengthening exercises, his knee pain resolves within weeks.
Brad concludes that AI can be a valuable, low-risk tool for exploring ideas, learning, and improving routines—especially for those with experience in fitness. However, it still falls short of replacing hands-on expertise and nuanced diagnosis from professionals. He emphasizes that better input and more detailed feedback to AI could improve its usefulness, but ultimately sees it as a supplement rather than a substitute for qualified care.
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