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The growing trend of ageing has created many challenges. One of these challenges is the rehabilitation of individuals who take time, resources and manpower. The motivation for this study is to propose an ontology‐based automatic design methodology for use in intelligent rehabilitation systems in the Internet of things (IoTs). For interconnection, all health system resources in a network use IoT technology. In order to provide fast and effective rehabilitation for different patients, IoT is combined with ontology. The experimental results obtained from rehabilitation of the lower limbs show that the IoT‐based rehabilitation system works properly and an ontology‐based approach can help create an effective rehabilitation strategy, configure and quickly deploy all available resources with the requirements given. In this study, three types of biosensors have been selected. These biosensors are used for blood, saliva and breathing tests. The expansion of the growth and maturity of technology based on the Fisher‐Pry model is based on patent and bibliometrics analysis. The analysis of intellectual property rights according to their number indicates that blood vital sensors reached their turning point in 2009, but the vital sensors of saliva and respiration will reach their turning point and maturity with a delay of 8–14 years.
Hamidi et al. (Fri,) studied this question.