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E-textiles have shown great potential for development of soft sensors in applications such as rehabilitation and soft robotics. However, existing approaches require the textile sensors to be attached externally onto a substrate or the garment surface. This paper seeks to address the issue by embedding the sensor directly into the wearable using a computer numerical control (CNC) knitting machine. First, we proposed a design of the wearable knee brace. Next, we demonstrated the capability to knit a sensor with the stretchable surrounding fabric. Subsequently, we characterized the sensor and developed a model for the sensor's electromechanical property. Lastly, the fully knitted knee brace with embedded sensor is tested, by performing three different activities: a simple Flexion-extension exercise, walking, and jogging activity with a single test subject. Results show that the knitted knee brace sensor can track the subject's knee motion well, with a Spearman's coefficient (r

Anomaly detection algorithms have vast applications, from fraud detection in business transactions to rare pattern detection in a production line to help prevent machinery failures. The availability of quantitative clinical data makes a compelling case for using anomaly detection algorithms in clinical settings, for instance, to help prevent diagnosis errors. This work evaluates the feasibility of using Isolation Forest algorithm for detection of spikes in surface electromyography (sEMG) of biceps and muscle resistive force in upper limb spasticity datasets. Results show that the anomaly detection in sEMG data is a good predictor for the occurrence of catch. It could be deployed in rehabilitation robotic systems for injury prevention by linking the anomaly detection to the actuation module exerting force in the system.

One of the most frequent cause of limb disabilities worldwide is stroke. In order to achieve high recoverability, stroke patients require repetitive and consistent rehabilitation treatment. However, the increasing number of stroke patients with limited number of therapists and transportation problem among patients from rural places limit the accessibility to have better treatment. Hence, it is important to have a Rehabilitation Robot Devices (RRDs) to minimize the problems. This research is aimed to design an upper limb rehabilitation robot device that is portable and adjustable. In order to ensure that the robot arm design achieve the desired movement, CATIA V5R22 was used to simulate the design with a human builder. Motion analysis in SolidWork 2018 was used to investigate the angular displacement of the robot arm link. The simulation showed that, the robot arm design corresponds with the Malaysian anthropometry dimensions. The motion analysis showed that, the movement pattern of the robot arm achieved the desired angle of movement during rehabilitation process with the wrist extension recorded the highest time cycle which is 16 seconds for 45 degrees of extension.

Plane-to-plane transitioning has been a significant challenge for climbing robots. To accomplish this, additional actuator or robot module is usually required which significantly increases both size and weight of the robot. This paper presents a two-wheg miniature climbing robot with a novel passive vertical tail component which results in robust transitioning capabilities. The design decision was derived from an indepth force analysis of the climbing robot while performing the transition. The theoretical analysis is verified through a working prototype with robust transitioning capabilities whose performance follows closely the analytical prediction. The climbing robot is able to climb any slope angles, 4-way internal transitions, and 4-way external transitions. This work contributes to the understanding and advancement of the transitioning capabilities and the design of a simple climbing robot, which expands the possibilities of scaling down miniature climbing robot further.

This paper presents the design and fabrication of ORION-II for autonomous Intelligence, Surveillance and Reconnaissance (ISR). ORION-II is a miniature climbing robot equipped with all the necessary electronic components to achieve ISR tasks. It consists of a robot chassis (tail) carrying the electronics and two DC motors each driving a wheel-leg (wheg) with four “flaps” equipped with bilayer compliant tapes. Two types of tapes are used for attachment of ORION-II: bilayer PDMS/foam and bilayer micro-suction/foam. The two types of tapes are tested on different climbing surfaces, and the climbing performance is reported. ORION-II could climb rougher surfaces when using the PDMS/foam tape, and perform internal climbing transitions when using the micro-suction/foam tape. The total weight of ORION-II is 153.18 g as compared with 71.5 g of our previous version ORION-I.

This paper describes a system-level design for an upper limb spasticity part-task trainer driven by clinical data stored in a cloud database. The robotic part-task trainer has been developed for pre-clinical training of medical personnel on the evaluation of upper limb spasticity based on the Modified Ashworth Scale. The cloud-based system enables continuous updating of clinical data of upper limb spasticity by rehabilitation physicians. Multiple part-task trainers can be connected to the cloud database via the internet, thus enabling the remote coaching of trainees and instant feedback of professional therapists and clinicians to the trainees. It is expected that the functionality provided by the cloud technology will benefit the pedagogy of medical education in the future.

Smart factories of the era of the fourth industrial revolution or Industry 4.0 that employ a completely new approach to production are beginning to emerge. In this context, information and communication technology driven by the Internet of Things, Data and Services play a vital role. To demystify and showcase how a smart factory works, a reference model consisting of a principle solution and a working prototype for a smart factory has been developed. The principle solution consisting of six key aspects has been specified using the specification technique CONSENS. This paper describes one of the six key aspects, namely, the active structure of a smart factory. The active structure describes a system-level concept for a smart product that records its own product identity and production history from the moment an order is placed right through to outbound logistics. In this context, the key system elements and their interdependencies in terms of information, energy and material flows are described.

Gaming systems have been proven to be able to improve physical and cognitive skills. Several studies have integrated games to be part of rehabilitation program to improve functional ability of human limbs in performing activities of daily living. This paper presents the development of an interactive electromyogram (EMG) based PONG game for foot dorsifexion and plantarflexion exercise. PONG game is selected because it is a classical game that can be easily comprehended and can be played by young and old people. Two surface EMG sensors were used in this work to acquire muscle activity of tibialis anterior muscle and gastrocnemius muscle. An experimental study was carried out to examine the viability of this sensor as input to play the game. The results were satisfactory. This study further strengthens the viability of using muscle activity as an input for gaming system and as a mean to monitor patient rehabilitation progress.

Rehabilitation process for patients with spasticity must go through experienced physicians and therapists to avoid injuries and to maximize the rehabilitation session for the sake of the patients' improvement. To have experience and good skills, therapist trainees need to learn from the experienced clinicians. However, it becomes crucial to transfer the knowledge from the professional clinicians to the therapist trainees. Therefore it is important to be able to visualize the characteristics of spasticity quantitatively in order to support the learning process of therapist trainees. Four patients with varying spasticity levels were involved in this clinical data collection of upper limb spasticity. The clinical procedure involved repeated movements of arm extension and flexion, performed by an experienced clinician. The clinician evaluated the spasticity levels through the conventional manual methods of clinical skills and judgment. The clinical data was also collected via a digital goniometer and manual muscle tester (MMT), connected to a DAQ (product of National Instruments) and recorded using LabVIEW. The data was analyzed to investigate the pattern of each spasticity level according to the Modified Ashworth Scale (MAS). The result of this research will help the therapist trainees to better understand and obtain a clear image of the spasticity stiffness pattern based on the Modified Ashworth Scale (MAS) level.

The aim of this work is to formulate a spasticity symptoms-oriented model, in terms of its capability to consistently emulate unidirectional and velocity-dependent spasticity symptoms, based on a Modified Tardieu Scale (MTS). Spasticity stiffness can be simulated using two dynamic equations expressing 1) muscle tone catch during passive stretching at different velocities and 2) resistance through Range Of Motion (ROM). Muscle tone is proportionate to velocity; where muscle resistance is constant until reaching a certain angular velocity. Following different Modified Ashworth Scale (MAS) levels, muscle resistance can occur at varying degrees through the ROM. The simulated spasticity of MAS 1+, based on the developed model, shows a strong positive linear correlation coefficient with average r = 0.7414 for fast forearm extension. The derived model will be used to develop new principles of variable stiffness actuation in an upper limb part-task trainer that is able to emulate upper limb spasticity symptoms.

Lane detection plays an important role in intelligent vehicle systems. Therefore, this paper presents a robust road lane marker detection algorithm to detect the left and right lane markers. The algorithm consists of optimization of Canny edge detection and Hough Transform. The system captures images from a front viewing vision sensor placed facing the road behind the windscreen as input. Then a series of image processing is applied to generate the road model. Canny edge detection performs features recognition then followed by Hough Transform lane generation. The algorithm detects visible left and right lane markers on the road based on real-time video processing.

Stretching the elbow of patients with upper limb disorder elicits diverse muscle tone responses, for instance, in an increased, uniform or jerky manner. This work addresses the emulation of muscle tone of the symptoms of spasticity, lead-pipe rigidity and cogwheel rigidity in the upper limb. A hybrid actuation strategy capable of emulating dynamic muscle tone has been proposed. In such strategy, a Magneto-Rheological brake is used to produce the resistance for a constant stiffness, and supported by a DC servo motor to assist the time delay of the fluid particle settling rate of the magneto-rheological fluid. The outcome is a consistent replication of the motion characteristics where the resistance torque emulated at the elbow joint is in close resemblance with the simulated data of upper limb spasticity and rigidity.

This paper presents the development of a tactile sensor using single miniature sensing element based on pressure sensitive conductive rubber and outlines the resistance measurements performance. This sensor is specially designed for a robotic hand developed at UiTM Faculty of Mechanical Engineering. Nevertheless, the low cost, low density and flexible material is suitable for most robotics hand designs. It exhibits piezoresistive like behavior whose resistance change with force/pressure enables its applications as tactile sensor. The operating principle and hardware architecture of the sensor is explained. It consists of an array of 16 sensing elements in rows and columns for data acquisition. The test results indicate significant drop of resistance with the increase of applied load.

The development of mechatronic systems starts with conceptual design, followed by design concretization and ends with system integration. The result of the conceptual design phase is the principle solution. It describes the main physical and logical operating characteristics of the system in a domain-spanning way. On the basis of this jointly developed principle solution, further design concretizations will take place in parallel within the domains involved. Finally, during the system integration phase, the outcomes from the individual domains are integrated to form an overall system. We developed a set of semiformal specification techniques to describe the principle solution of mechatronic systems. In collaboration with UNITY AG, we extended the usefulness of the specification technique for the management of development processes and development organization in enterprises.

Self-optimizing systems are technical systems with the ability to learn, communicate with each other, and optimize their behavior autonomously in response to environmental changes. The development of such systems demands new means of communication and cooperation between the specialists from diverse disciplines, especially during the conceptual design phase. The principle solution, as the result of conceptual design, should be formulated in a domain-spanning way and yet supports domain-specific concretization. In this endeavor, this paper addresses the domain-spanning specification technique for describing the principle solution of self-optimizing systems and explains how the domain-specific controller design process can be started in an integrative way. The synergistic impacts enabled by the principle solution are described from the viewpoints of complexity management, performance enhancement, and potential cost reduction along the controller design process.