Locomotive medical devices that are used for performing non-invasive treatments on patients can achieve positive or negative effects on disease recovery; therefore controlling the monitoring of this equipment becomes the basic objective to achieve a successful physical recovery. This paper first shows how the hardware and software design of a Platform for Human Locomotion Rehabilitation allows for the construction of a compact and reliable machine to rehabilitate people with knee osteoarthritis, and it describes how the "embedded programming" is applied on the platform monitoring system itself. It then expounds on the development of combined Neural Networks and Fuzzy Systems to monitor and control the Rehabilitation Locomotive Platform. We conclude relating variables such as weight-bearing on a patient, the treadmill speed system and the ECG patient's heart rate which must be integrated in the programming process performed by ANFIS and the embedded software using digital processors DSPs.