肌肉疲勞熱力圖:按肌群劃分的訓練準備度

It is a body map that colors each muscle group by how ready it is to train again. Instead of one whole-body recovery score, it splits the picture by muscle, so chest can read fresh while hamstrings are still fatigued from a heavy session two days ago. The colors come from the workouts you log: how recently you trained each muscle, how many working sets it took, and how hard those sets were. The result is an estimate of training readiness, not a measurement of tissue damage.

It depends on the muscle and how hard you hit it. Larger, eccentric-heavy muscles like hamstrings recover slower, on the order of a few days after a hard session, while small distal muscles like calves, forearms, and the muscles of the core clear fatigue faster. The heat map uses muscle-specific recovery curves rather than a single number, so each group is judged on its own timeline instead of a flat 48 hours for everything.

A common rule of thumb is to train a muscle again once it feels recovered and is no longer sore, which usually lands somewhere between one and three days for most groups. The heat map sharpens that by giving each muscle a readiness state, fresh, recovering, or fatigued, plus a coarse time-to-fresh estimate like tonight, tomorrow, or a couple of days. You still own the call, but you are deciding against your own training history rather than a generic chart.

No. It is an estimate of training readiness derived entirely from the workouts you log, not a measurement of muscle or tissue fatigue, and it is not medical advice. It models how fatigue from your sessions likely decays over time using reasonable training-science priors. Real recovery is also shaped by sleep, nutrition, stress, and individual differences the model cannot see, so treat the colors as a smart starting point and let how you feel have the final word.

No. The heat map is built from logged strength training, the exercises, sets, reps, and loads in your workout history, so it works with no wearable at all. If you log effort with RPE it refines the estimate, and the map reads intensity from your own loading patterns when RPE is absent. When your training history is thin it switches to a low-confidence mode and says so rather than guessing.