Spasticity is one of the muscle diseases in upper limb that is often seen in the patients of stroke and shoulder paralyzed. The disease occur when the patients central nerve is damaged, leading the patients having resistance in the joint when they tries to move it. In the area of orthopedics and rehabilitation, it has become essential to study the characteristics of human joint and muscle diseases. In this paper, an experiment to measure the characteristics of the disease was conducted and the data is used to reproduce the symptoms of spasticity in an upper limb patient simulator. The developed patient simulator is built with the joint and three bones of human arm: humerus, radius and ulna and is evaluated in term of reproducibility of the spasticity stiffness by two experiences physiotherapist.

Conventional ankle rehabilitation exercises can be monotonous and repetitive. The use of robots and games can complement the existing practices, provide an engaging environment for the patient and alleviate the physiotherapist’s workload. This paper presents an ankle rehabilitation robot that uses two nitinol wire actuators and a Pong game to provide foot plantarflexion and dorsiflexion exercises. Nitinol is a type of smart material that has high volumetric mechanical energy density and can produce translational motion. A two-state discrete antagonistic control is proposed to manipulate the actuators. The system was tested on healthy participants and stroke patients. The results showed that the robot was safe and compliant. The robot did not forcefully plantarflex or dorsiflex the foot when the participant exerted opposing force. The actuators worked antagonistically to flex to the foot as intended, in sync with the up and down motions of the player’s bat in the game. These behaviors demonstrated the feasibility of a nitinol-based ankle rehabilitation robot and a simple and yet intuitive game in providing interactive rehabilitation exercise. The robot is expected to enhance the patient’s experience, participation and compliance to the rehabilitation routine and to quantitatively monitor the patient’s recovery progress.

The Modified Ashworth Scale (MAS) is commonly used to assess spasticity in clinics. The qualitative description of MAS has resulted in ambiguity during spasticity assessment. This work supports spasticity assessment by providing measurement data acquired from wireless wearable sensors, i.e., goniometers, myometers, and surface electromyography sensors. Based on in-depth discussions with consultant rehabilitation physicians, eight (8) kinematic, six (6) kinetic, and four (4) physiological features were extracted from the collected clinical data from fifty (50) subjects. These features were used to train and evaluate the conventional machine learning classifiers, including but not limited to Support Vector Machine (SVM) and Random Forest (RF). Subsequently, a spasticity classification approach combining the decision-making logic of the consultant rehabilitation physicians, SVM, and RF was developed. The empirical results on the unknown test set show that the proposed Logical–SVM–RF classifier outperforms each individual classifier, reporting an accuracy of 91% compared to 56–81% achieved by SVM and RF. A data-driven diagnosis decision contributing to interrater reliability is enabled via the availability of quantitative clinical data and a MAS prediction.

Various ankle rehabilitation robots have been developed in the recent decade to improve ankle strength and mobility and to alleviate the burdens on clinicians and physiotherapists. However, existing designs have stiff actuating mechanism, heavy and bulky electromagnetic or pneumatic actuators. This paper introduces ankle rehabilitation robot that utilizes Shape Memory Alloy (SMA) wire actuator to provide foot plantarflexion and dorsiflexion during rehabilitation exercise. SMA wire is a smart material that can contract when it is heated and expand back to its original shape when it is cooled. It also has high power to weight ratio. However, the SMA wire has low cooling rate thus limits its operating frequency. A periodical cooling mechanism is proposed here. Its efficacy is then evaluated against natural cooling and continuous forced convection. The experimental study shows promising results and demonstrates that periodical cooling has both the advantages of natural cooling and forced convection and can improve the cooling rate of SMA wire actuator.

Industry 4.0 is changing design and manufacturing methodologies because future production lines will manufacture customized products for the mass market. As for that, Automated machines and systems in such a production line need to communicate with each other. In this context, data exchange takes place between different kind of systems or platforms. Therefore a system level approach clarifying the interactions between the manufacturing devices in heterogeneous environments addressing highly dynamic and often loosely coupled production processes is required. This paper describes a model-based systems engineering approach of which the system integration of a smart factory is systematically managed right from the conception design phase. During the conception phase, the communication flows between the system elements is specified using CONSENS (Conceptual Design Specification Technique for the Engineering of Complex Systems). Based on the system level design specifications, a working prototype of a mini production line deploying Supervisory Control and Data Acquisition (SCADA) technology has been developed. The SCADA software acts as a human-machine interface and provides a gateway to access data of the production line either locally or through the internet. Multi-role users could access the system locally or remotely for monitoring, controlling, analyzing and ordering using SCADA as the interface.