Multimodal Adaptive Interfaces for Upper Limb Robot-aided Neuro-rehabilitation

Nowadays, stroke is one of the leading cause of permanent disability. Several rehabilitation methodologies can be adopted to counteract stroke motor impairments, but the optimal training approach remains unknown. In this perspective, rehabilitation robotics is one of the most active research fields in the neuro-rehabilitation panorama. Robotic devices for upper limb treatment may lead to improvements in motor recovery and neuro-plasticity due to their ability to deliver highly-intensive, repeatable, and accurate movement therapy. In addition, robotic machines provide objective measurements for patient assessment, while guaranteeing patient safety and unloading therapist workload with respect to conventional therapy. This work presents the development of multimodal adaptive interfaces tailored to human's specific needs. Multimodal interfaces represent complex systems characterized by the simultaneous use of multiple human sensory modalities that can support combined input/output modes. They include different subsystems that can operate both as monitoring tools that record various levels of information as well as stimulation techniques (auditive, visual, haptic and neuromodulation). The concept of multimodal interface is then applied to upper limb robot-aided neurorehabilitation with the ambition to maximize the therapeutic effects in post-stroke patients. Bio-cooperative systems and non-invasive neuromodulation techniques may represent a general extended vision of multimodal interfaces. In particular, bio-cooperative systems include several subsystems that communicate through a customized multimodal interface. They represent the new generation of robotic platforms that collocate the patient in the control loop, by employing his/her physiological, neurological, psychological and biomechanical measures, and automatically adapts the control strategy on the basis of the acquired patient states. The proposed work consists of two main research areas that include the concept of multimodal interface: i) design criteria of bio-cooperative robotic systems for upper limb rehabilitation, ii) application of multimodal interfaces for investigating effects of robotic therapy combined with non-invasive neuromodulation techniques. Regarding the first area, a novel taxonomy of bio-cooperative systems is proposed. In addition, the application of bio-cooperative system has been applied to two case studies grounded on end-effector machines (Kuka robotic arm and CBM-Motus). However, the approach can be easily extended to wearable robotic devices as shown in Chapter 5. A special attention has been paid to the design and development of an arm gravity support system integrated in a bio-cooperative upper limb robot-aided rehabilitation system. The bio-cooperative approach and an adaptive control strategy have been then applied to a robotic tele-rehabilitation system. Furthermore, a modular system aimed to control an upper arm robotic exoskeleton for assistive tasks has been presented and discussed. Finally, the development of a mechanical interfacing system for hand rehabilitation devices and upper arm exoskeletons is reported. As regards the second area, the concept of multimodal interface has been applied for quantitative assessment of the outcomes related to clinical studies involving stroke patients. These studies have been designed for investigating the effects of neuromodulation techniques paired with upper limb planar robotic therapy. The outcomes of two clinical studies combining Transcranial Magnetic Stimulation (TMS) and transcranial Direct Current Stimulation (tDCS) with upper limb robotic therapy are reported and discussed.