Use AI to rapidly generate exercise modification libraries for patients with multiple comorbidities or contraindications.
When you have a patient with diabetes, osteoporosis, and shoulder pain who can't do standard exercises, creating safe alternatives eats up precious time between sessions. Instead of manually thinking through every modification scenario, use AI to generate a comprehensive library of safe alternatives all at once. Start by giving AI the complete clinical picture—the diagnosis you're treating plus all contraindications—then ask it to create variations across difficulty levels and equipment options. The real time-saver is doing this in one focused 10-minute session rather than scrambling between patients. You'll build a personalized modification menu you can reference instantly during treatment or when writing HEPs. This works especially well when you have recurring patient profiles (like post-surgical patients with cardiac history) because you create the library once and adapt it repeatedly. Always review each suggested modification against your clinical judgment and current evidence before recommending it to patients.
Try this prompt today
“I'm treating a 68-year-old patient for knee osteoarthritis. They also have uncontrolled hypertension, severe obesity (BMI 42), and bilateral shoulder impingement. I need to strengthen their quadriceps and improve balance. Generate 15 exercise options with modifications, organized by difficulty level (beginner/intermediate/advanced). For each exercise, note what to avoid given their contraindications, what equipment is needed (or bodyweight alternative), and how to progress it safely. Make instructions clear enough that I can quickly adapt them into a home program.”
March 17, 2026
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