Hybrid exoskeletons combine robotic orthoses and motor neuroprosthetic devices to compensate for motor disabilities and assist rehabilitation. The basic idea is to take benefits from the strength of each technology, primarily the power of robotic actuators and the clinical advantages of using patient's muscles, while compensating for the respective weaknesses: weight and autonomy for the former, fatigue and stability for the latter. While a wide repertory of solutions have been proposed in literature for the control of robotic orthoses and simple motor neuroprosthesis, the same problem on a complex hybrid architecture, involving a wide number of muscles distributed on multiple articulations, still waits for a practical solution. In this article we present a general algorithm for the control of the neuroprosthesis in the execution of functional coordinated movements. The method extracts muscle synergies as a mean to diagnose residual neuromotor capabilities, and adapts the rehabilitation exercise to patient requirements in a dynamic way. Fatigue effects and unexpected perturbations are compensated by monitoring functional state variables estimated from sensors in the robot. The proposed concept is applied to a case-study scenario, in which a postural balance rehabilitation therapy is presented.