Efficacious stroke rehabilitation depends not only on patients' medical treatment but also on their motivation and engagement during rehabilitation exercises. Although traditional rehabilitation exercises are often mundane, technology-assisted upper-limb robotic training can provide engaging and task-oriented training in a natural environment. The factors that influence engagement, however, are not fully understood. This paper therefore studies the relationship between engagement and muscle activities as well as the influencing factors of engagement. To this end, an experiment was conducted using a robotic upper limb rehabilitation system with healthy individuals in three training exercises: (a) a traditional exercise, which is typically used for training the grasping function, (b) a tracking exercise, currently used in robot-assisted stroke patient rehabilitation for fine motor movement, and (c) a video game exercise, which is a proliferating approach of robot-assisted rehabilitation enabling high-level active engagement of stroke patients. These exercises differ not only in the characteristics of the motion that they use but also in their method of triggering engagement. To measure the level of engagement, we used facial expressions, motion analysis of the arm movements, and electromyography. The results show that (a) the video game exercise could engage the participants for a longer period than the other two exercises, (b) the engagement level decreased when the participants became too familiar with the exercises, and (c) analysis of normalized root mean square in electromyographic data indicated that muscle activities were more intense when the participants are engaged. This study shows that several sub-factors on engagement, such as versatility of feedback, cognitive tasks, and competitiveness, may influence engagement more than the others. To maintain a high level of engagement, the rehabilitation system needs to be adaptive, providing different exercises to engage the participants.

Enhancing engagement of patients during stroke rehabilitation exercises are in the focus of current research. Various methods and computer supported tools have been developed for this purpose, which try to avoid mundane exercising that is prone to become a routine or even boring for the patients and leads to ineffective training. This paper introduces an engagement enhancing cyber-physical stroke rehabilitation system (CP-SRS) aiming at enhancing the patient's engagement during rehabilitation training exercises. This paper focuses on introducing the implementation and validation of the engagement monitoring subsystem (EMS) in the CP-SRS. The EMS is expected to evaluate the patient's actual engagement levels in motor, perceptive, cognitive and emotional aspects. Experiments in these four aspects were conducted separately, in order to characterize the range and accuracy of the engagement indicators by influencing the subjects into different engaged states. During the experiments, different setups were created to mimic the situations in which the subject was engaged or not engaged. The subjects involved in the experiments were healthy subjects. Results showed that the measurement in motor, perceptive, cognitive, and emotional aspects can represent the corresponding engagement level. More experiments will be conducted in the future to validate the efficiency of the CP-SRS in enhancing the engagement with stroke patients.