OpenFish: Biomimetic design of a soft robotic fish for high speed locomotion.

We present OpenFish: an open source soft robotic fish which is optimized for speed and efficiency. The soft robotic fish uses a combination of an active and passive tail segment to accurately mimic the thunniform swimming mode. Through the implementation of a novel propulsion system that is capable of achieving higher oscillation frequencies with a more sinusoidal waveform, the open source soft robotic fish achieves a top speed of 0.85 m / s . Hereby, it outperforms the previously reported fastest soft robotic fish by 27 % . Besides the propulsion system, the optimization of the fish morphology played a crucial role in achieving this speed. In this work, a detailed description of the design, construction and customization of the soft robotic fish is presented. Hereby, we hope this open source design will accelerate future research and developments in soft robotic fish.

Implementation of System Operation Modes for Health Management and Failure Prognosis in Cyber-Physical Systems.

Cyber-physical systems (CPSs) have sophisticated control mechanisms that help achieve optimal system operations and services. These mechanisms, imply considering multiple signal inputs in parallel, to timely respond to varying working conditions. Despite the advantages that control mechanisms convey, they bring new challenges in terms of failure prevention. The compensatory action the control exerts cause a fault masking effect, hampering fault diagnosis. Likewise, the multiple information inputs CPSs have to process can affect the timely system response to faults. This article proposes a failure prognosis method, which combines time series-based forecasting methods with statistically based classification techniques in order to investigate system degradation and failure forming on system levels. This method utilizes a new approach based on the concept of the system operation mode (SOM) that offers a novel perspective for health management that allows monitoring the system behavior, through the frequency and duration of SOMs. Validation of this method was conducted by systematically injecting faults in a cyber-physical greenhouse testbed. The obtained results demonstrate that the degradation and fault forming process can be monitored by analyzing the changes of the frequency and duration of SOMs. These indicators made possible to estimate the time to failure caused by various failures in the conducted experiments.

Implementation and Validation of Engagement Monitoring in an Engagement Enhancing Rehabilitation System.

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.

Influence of complementing a robotic upper limb rehabilitation system with video games on the engagement of the participants: a study focusing on muscle activities.

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.