The demand for continuous rehabilitation programs is growing as home-based training expands and in-person resources remain limited, creating a need for controllable hybrid care models. The aim of this work is to substantiate and design an integrative technological framework that links standardized goal setting across functioning domains, hybrid delivery of training, and digital load monitoring. The hypothesis assumes that ICF oriented personalization combined with objective tracking via wearable devices improves dosing accuracy, adherence stability, and outcome reproducibility under explicit safety requirements.

Methods included an analytical review of sources published in 2022–2025, synthesis, and conceptual modeling. A three-loop model is presented: a loop of assessment and goal formulation, a loop of dosing and motor learning, and a loop of digital feedback. It is shown that technology selection is most consistent when performed through a matrix “impairment profile, intervention goal, in-person component, remote module, monitoring metrics, adjustment rule, risk and prevention”. It is established that a minimally sufficient monitoring set may rely on physical activity parameters, exercise execution features, and cardiorespiratory responses, while data interpretation requires clinical context and self-reported symptoms.

Conclusions and practical recommendations are provided for standardizing program design, implementing of load progression and regression rules, and embedding risk management into hybrid support.