Development of innovative protocols and methods for functional assessment of movement and neuromotor rehabilitation

Over the years, the role of bioengineering in medical sciences has been significantly rising, thanks to the capabilities of cutting-edge techniques and technologies, which are nowadays more widely available in terms of cost and complexity. The functional assessment of movement and the treatment of neuromotor disorders may be significantly impacted by new systems for the measurement of human movements and the visualisation of virtual environments. These systems provide sophisticated data acquisition and data analysis capabilities to study complex movements at a negligible cost. Such technologies can be applied to the study of human movement both in the context of basic science, to understand fundamental aspects of motor control, and for medical applications, to develop novel neuromotor assessment and rehabilitation protocols. Virtual reality (VR) systems allow to create immersive virtual environments, include sophisticated instruments for recording kinematic data, and provide feedback to participants during the performance of motor tasks and rehabilitation training exercises. VR system may therefore allow for quantitative assessments of visuomotor function and for novel neuromotor rehabilitation approaches. Assessing motor function often requires characterizing the patterns of muscle activation which underlie movement generation. In recent years, several approaches have been developed to study the relation between electromyography (EMG) and kinematics or force generation, and to use EMG signals in rehabilitation protocols for restoring specific components of the motor commands affected by the impairment. However, myoelectric interfaces are typically not very reliable and decoding participant’s intention through EMG signals is still challenging. Thanks to the advancements in machine learning techniques, it is now possible to reliably decode EMG signals in a reasonable time for real time applications. Using myoelectric interfaces in a rehabilitation context may promote usages of residual myoelectric activity to assist patients in generating voluntary movements. This thesis presents five research projects conducted in collaboration with national and international research centres. The common thread among these projects is the development of bioengineering methods, exploiting the capability of new technologies, to perform functional assessments of motor function and the application of these methods to investigate motor skills and for neuromotor rehabilitation of patients with neurological pathologies. The first two projects explore the use of technologies and methods to understand fundamental aspects of motor control while the other three projects involve novel neuromotor assessments and rehabilitation protocols. The first project (chapter 2) concerns the analysis of kinematic data for the characterization of individual performance and strategies during complex tasks such as the interception of virtual balls. The second project (chapter 3) is focused on the development and validation of a system to study complex motor tasks such as unconstrained ball throwing. The third and the fourth project (chapters 4 and 5), concerns the design and validation of an upper limb rehabilitation system using VR and myoelectric control for stroke survivors as well as the testing of the feasibility of a refinement of this system through the integration of a more sophisticated electromyographic measurement device. Finally, the fifth project (chapter 6) presents the design, development, and validation on healthy subjects of a low-cost maximum bite force measurement system to be used on patients with temporomandibular joint diseases. The setups, protocols, and methods developed in this thesis will allow to perform quantitative evaluations of the physiological parameters, in some cases also during activities of daily life, in conditions that are generally more complex than those used in standard clinical practice. Through the study of these parameters, key features of motor control and functional status of the participants can be characterized. The identification of individual strategies may then be useful for the development of personalized rehabilitation protocols. These developments, including the use of low-cost technologies, may also provide the basis for future telemedicine applications to monitor functional parameters and to perform neuromotor rehabilitation protocols in a home environment.