BACKGROUND:Existing algorithms do not allow for setting up finely tuned progression or intensity for exercise training in intensive care units (ICUs). AIM:We aimed to assess the feasibility and tolerance of a very early exercise program tailored by using decisional algorithm that integrated both progression and intensity. DESIGN:Open-label pilot study. SETTING:ICU. POPULATION:30 adults hospitalized in ICU. METHODS:Once a day, patients performed manual range of motion, cycloergometry, and functional training exercises. The progression and intensity of training were standardized by using the constructed algorithm. The main outcome, discomfort on a 0-100 visual analog scale, was assessed before and after each exercise session. Secondary outcomes were muscle strength, ICU length of stay and adverse events related to exercise. RESULTS:In total, 125 exercise sessions were performed. Discomfort during exercise sessions decreased significantly by the fifth session (p=0.049). Early exercise sessions were feasible and did not produce major adverse events. CONCLUSIONS:We confirmed the safety and feasibility of very early exercise programs in ICUs. Early exercise tailored by using a decisional algorithm helps relieve the discomfort of ICU patients. CLINICAL REHABILITATION IMPACT:In everyday practice, the use of decisional algorithms should be encouraged to initiate and standardize early exercise in ICUs.