Abstract
BackgroundNeurorehabilitation therapies exploiting the use-dependent plasticity of our neuromuscular system are devised to help patients who suffer from injuries or diseases of this system. These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and thus their functionality. Hence, a sensor-motor treatment where patients makes certain movements will help them (re)learn how to move the affected body parts. But these traditional rehabilitation processes are usually repetitive and lengthy, reducing motivation and adherence to the treatment, and thus limiting the benefits for the patients.ObjectiveOur goal was to create innovative neurorehabilitation therapies based on THERAPIST, a socially assistive robot. THERAPIST is an autonomous robot that is able to find and execute plans and adapt them to new situations in real-time. The software architecture of THERAPIST monitors and determines the course of action, learns from previous experiences, and interacts with people using verbal and non-verbal channels. THERAPIST can increase the adherence of the patient to the sessions using serious games. Data are recorded and can be used to tailor patient sessions.MethodsWe hypothesized that pediatric patients would engage better in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies to improve patient motivation. We propose RoboCog, a novel cognitive architecture. This architecture will enhance the effectiveness and time-of-response of complex multi-degree-of-freedom robots designed to collaborate with humans, combining two core elements: a deep and hybrid representation of the current state, own, and observed; and a set of task-dependent planners, working at different levels of abstraction but connected to this central representation through a common interface. Using RoboCog, THERAPIST engages the human partner in an active interactive process. But RoboCog also endows the robot with abilities for high-level planning, monitoring, and learning. Thus, THERAPIST engages the patient through different games or activities, and adapts the session to each individual.ResultsRoboCog successfully integrates a deliberative planner with a set of modules working at situational or sensorimotor levels. This architecture also allows THERAPIST to deliver responses at a human rate. The synchronization of the multiple interaction modalities results from a unique scene representation or model. THERAPIST is now a socially interactive robot that, instead of reproducing the phrases or gestures that the developers decide, maintains a dialogue and autonomously generate gestures or expressions. THERAPIST is able to play simple games with human partners, which requires humans to perform certain movements, and also to capture the human motion, for later analysis by clinic specialists.ConclusionsThe initial hypothesis was validated by our experimental studies showing that interaction with the robot results in highly attentive and collaborative attitudes in pediatric patients. We also verified that RoboCog allows the robot to interact with patients at human rates. However, there remain many issues to overcome. The development of novel hands-off rehabilitation therapies will require the intersection of multiple challenging directions of research that we are currently exploring.
Highlights
Neuro-rehabilitation therapy pursuits the recovery of dam aged neuronal areas and/or muscles from the repetitive practice of certain motor or cognitive activities
Rehabilitation robotics constitutes an emerging area of research, where the aim is to include robotics technology in the time-consuming and labor-intensive process associated to neuro-rehabilitation therapies
Apart from giving mechanical/physical assistance in rehabil itation, recent studies postulate that robotic technology can motivate and coach patients in the realization of the repetitive efforts that constitute the primary stimulus for recovery
Summary
Abstract-Exploiting the use-dependent plasticity of our neu romuscular system, neuro-rehabilitation therapies are devised to help patients that suffer from injuries or diseases in this system, such as those caused by brain damage before or during birth or in the first years of life (e.g. due to cerebral palsy or obstetric brachial plexus palsy) These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and their functionality. Our starting hypothesis was that patients could get consistently engaged in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies that should improve the patient recovery time and reduce the overall socio-economic costs. The development of a real socially interactive robot will require the intersection of multiple challenging directions of research that we are currently exploring
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