Today, many people wear devices like Whoops, Apple Watches, or Fitbits to track their fitness and overall well-being. But what if AI platforms could provide personalized recommendations to enhance our recovery, sleep, and daily health routines? As a former Division I lacrosse player, I’ve experimented with nearly every type of wearable health tracker. However, this often came with the stress of being told I wasn’t recovering or sleeping adequately. With a busy schedule, I struggled to know how to adjust my daily routines without sacrificing my schoolwork or training. I became curious if AI could analyze my Whoop data and help create a tailored schedule with personalized recommendations for living a healthier life every day.
I uploaded my Whoop data (which highlighted my sleep performance and recovery) and uploaded it to Claude 3.5, an AI assistant that is capable of parsing the textual content present within images. While the primary focus of this data is on sleep and recovery, I could also include additional images with detailed information, like muscle breakdown. Along with the data, I provided a detailed prompt requesting specific recommendations and routines to help improve the sleep of a 22-year-old student-athlete.
The output included:
“Based on the Whoop data provided, I understand this 22-year-old female athlete is dealing with low sleep performance and needs to improve her recovery. Here are detailed recommendations to enhance her sleep recovery and overall daily recovery:
By implementing these strategies, the athlete should see improvements in her sleep quality and overall recovery. It’s important to make gradual changes and consistently monitor progress using the Whoop data. If sleep issues persist, consulting with a sleep specialist or sports medicine physician may be beneficial.”
The output highlighted several factors that can influence health, going beyond the obvious advice to exercise regularly and eat well. Some of the suggestions included supplement recommendations, time management techniques, and fostering communication between coaches or mentors. While most of this information was familiar to me prior to using the AI, it served as a helpful reminder of the self-care activities that can be implemented outside of regular training hours. The information gave me a holistic view of my wellness routine and reminded me that part of staying fit also means making time for recovery and things that make my body feel good.
I found that Claude was useful in terms of uploading a document, or in this case an image, and then did a decent job of analyzing the data in the photo. This tool makes the user’s experience much better, compared to having to upload a block of text into the LLM. However, even with these recommendations, we still need human judgment to decide which practices are worth implementing. Perhaps one day this technology will be able to create even more detailed, hourly schedules for people to follow, but we’re not quite there yet.
Lilly Callahan
