Cheng Yee Low

The aviation industry is undergoing unprecedented growth, and the rapid expansion places immense pressure on airport operations and demands innovative strategies to enhance efficiency and sustainability. This paper explores the design architecture of passenger boarding bridge (PBB) automation as a key application within the broader field of autonomous airport operations. Autonomous docking could significantly reduce crew workload and aircraft turnaround times, while improving the passenger experience. By harnessing digitalization and Industry 4.0 technologies, the system integrates lean hardware and software components to enable accurate and reliable performance. Particular emphasis is placed on the efficient implementation of inverse kinematics for precise aircraft door detection and bridge navigation. The paper outlines the required technical infrastructure and computational methodology in supporting the automation docking process of a PBB on the airport apron.

Tissue engineering is an area in which new tissues or organs are replicated in a promising way to replace damaged tissues or organs caused by accidents and medi Tissue engineering is an area in which new tissues or organs are replicated in a promising way to replace damaged tissues or organs caused by accidents and medi

The motion analysis of a robotic manipulator is crucial in testing its application scenarios. In this work, the direct geometric model is used for kinematic ana The motion analysis of a robotic manipulator is crucial in testing its application scenarios. In this work, the direct geometric model is used for kinematic ana

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.

Upper limb spasticity (ULS) is a medical condition associated with muscle stiffness and spasms at the upper limb. Modified Ashworth Scale (MAS) is commonly used

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.