Stroke is one of the main causes of disability in the world. Stroke cases happen approximately every 40 seconds. In view of the aging population, the rehabilitation of stroke patients receives a high level of attention in society. A research team led by Prof. Raymond Kai-Yu Tong, Professor and Chairman in the Department of Biomedical Engineering, and Prof. Zheng Li, Assistant Professor in the Department of has developed the 3D-printed soft robotic hand (soft robotic hand) by making use of the latest silicone printing technology. This provides stroke patients a tailor-made, less bulky but comfortable and affordable soft robotic hand for the rehabilitation process and so supports rehabilitation of the hand function. 

Latest silicone 3D-printing technology takes over from bulky traditional rehabilitation devices 

Because of their bulkiness, the traditional rehabilitation mechanical devices for stroke patients are usually found in hospitals. As patients cannot use the devices at home every day, they give a low level of support to them in their daily lives which affects the effectiveness of recovery. Therefore, Prof. Raymond Kai-Yu Tong and his research team developed the ‘Hand of Hope’, a mechanical robotic hand rehabilitation system, a few years ago, which provides training and supports rehabilitation of hand function after stroke. The ‘Hand of Hope’ was also the first Hong Kong-based hand rehabilitation system to receive the Grand Prix Award at the 40^th International Exhibition of Inventions of Geneva in 2012, and currently hospitals in over 15 countries are using it to help rehabilitation of stroke patients after obtaining the US Food and Drug Administration (FDA)’s approval and the Conformité Européene (CE) mark. 

Based on the success of the ‘Hand of Hope’, together with the rapid development of soft robots and silicone 3D-printing technology, the research team has spent nearly two years developing the new soft robotic hand. Compared with the traditional mechanical rehabilitation devices, the silicone actuator  controlling the activities of the fingers of the soft robotic hand is much smaller and lighter and patients can bring the soft robotic hand home to support daily activities. It can be tailor-made for patients, from children to adults, according to the size of their fingers and palms. The soft robotic hand can detect signals from the brain to the muscles, which supports patients in learning hand functions again and in performing complex gestures. This will enable occupational therapists to train patients in different daily tasks. In terms of the price, the cost of the silicone actuator is around one-tenth of the traditional rigid motor, meaning that is affordable to more patients. 

Prof. Raymond Kai-Yu Tong said, “As the ‘Hand of Hope’ made use of the traditional rigid motors, it was hard to further trim down its size and weight. The soft robotic hand is not only lighter and smaller, but we can tailor-make it for every stroke patient according to the hand size. So, some rarely found stroke patients, such as children, can now participate in the rehabilitation training sessions. We have provided training sessions to a stroke child, and we have found significant improvement on his hand function. In the future, we wish to deliver a soft robotic hand to every stroke patient so that they can start the training, even at home, rather than spending lots of time travelling to hospitals for training every day.” 

The soft robotic hand is pneumatically actuated to control patients’ ability in hand opening and closing. To deal with the spasticity presented in stroke patients’ compromised fingers, the research team has modified the design of the silicone actuator to facilitate effective finger flexion and extension, which is important for patients in performing more complex gestures. To enhance the quality of the silicone actuator, the researchers run a simulation to analyse the actuator characteristic before sending the actuator out for 3D-printing. While choosing the suitable 3D-printing service provider, the research team mainly focuses on the durability of the 3D-printed components, e.g. whether rupture would occur on the silicone actuator after a lengthy period of flexion and extension actuation. 

On-going clinical trial to validate the effect of rehabilitation on stroke patients 

When using the soft robotic hand, electrodes will be attached to the hemiplegic side of patients for recording the tiny electric current generated during muscle activity. The tiny electric current from the brain can be treated as an indicator of hand movement. When patients are trying to open the hand, muscle activity will be recorded through the attached electrodes and the soft robotic hand will open patients’ hands following their intention. This enables the patients to learn the correct way again using the brain to control their hand functions. 

This article was originally published on CUHK Communications and Public Relations Office website.

The Faculty of Engineering, together with the Faculty of Education and Faculty of Social Science, is collaborating with the Massachusetts Institute of Technology to explore using cutting-edge technology to improve teaching and learning, especially through understanding best practices for flipped classroom teaching via eLearning technologies. Experiments are ongoing with innovative technologies that enhance educational strategies, measure outcomes and understand the impact of individualised learning trajectories.

This collaborative research project with MIT is sponsored by the Dr. Stanley Ho Medical Development Foundation through the CUHK Stanley Ho Big Data Decision Analytics Research Centre, which is co-directed by Professor Joseph Sung, Mok Hing Yiu Professor of Medicine and Professor Helen Meng, Patrick Huen Wing Ming Professor of Systems Engineering & Engineering. In the recent CUHK-MIT eLearning Workshop, the research findings thus far presented have been based on investigations in eLearning with flipped classroom teaching led by Professor Sidharth Jaggi in an elite freshmen engineering mathematics class at CUHK, as well as a computer architecture class led by Dr. Chris Terman at MIT. 

This research effort involves inter-disciplinary collaboration across three CUHK faculties (the Faculty of Education, the Faculty of Engineering and the Faculty of Social Science) and the faculty at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, to investigate pedagogical efficacies and social dynamics in teaching and learning through data-driven analyses. The aim is to find ways to help students reach high levels of understanding of the subject matter. Flipped classroom is a novel educational paradigm enabled by technology. Basic content delivery/skills acquisition is conducted at home with videos and online exercises. The main activity in the classroom is to deepen skills and mastery with peer-to-peer (P2P) teaching and learning that encourages creativity and personal experience. More interestingly, the research findings illustrate that knowledge can flow from social interactions. 

Dr. Chris Terman, Senior Lecturer and former Co-Director of CSAIL, MIT said, ‘It’s great to have the opportunity for CUHK and MIT to share experiences of how best to use online materials to improve on-campus learning outcomes. There is a slow revolution underway in how best to teach STEM subjects at the university level, one that will benefit both students and faculty. Many thanks to the Dr. Stanley Ho Medical Foundation for sponsoring this workshop and the CUHK-MIT collaboration, which is helping to connect the communities of practice at these two universities.’

In the collaboration, some undergraduate courses in engineering mathematics at CUHK and computer architecture at MIT have adopted the Market-Assisted Teaching Exchange (MATE) System developed by Professor Sidharth Jaggi, Associate Professor, Department of Information Engineering of CUHK. In 2017, Professor Jaggi incorporated the concept of a knowledge exchange market into an interactive teaching and learning model, the MATE system, and applied it in the freshmen engineering mathematics elite course he teaches. Students are requested to study and research before class, advertise their level of understanding of the concepts of the class, use their strengths to help others, and then are given coupons (worth class points) in return.  In the other way around, they can give out coupons to those helping them understand the concepts.  This P2P learning system is warmly welcomed by the students because it can provide a wide variety of personalised help. The learning data analytics indicates that the students’ academic progress with this teaching and learning pedagogy is better than with the traditional teaching and learning mode. Some of the techniques used are indicated in the graphics attached. 

Professor Jaggi said, ‘As technology rapidly integrates into and changes society, our methods of educating current and future generations must also change, not just in terms of what we teach them, but also how we teach it. Integrating interactive e-learning techniques into education can lead to better learning outcomes than traditional teaching does. This project investigates multiple innovative teaching and learning techniques, and helps re-imagine what classrooms of the future can look like.’ 

Professor Helen Meng, Patrick Huen Wing Ming Professor of Systems Engineering & Engineering Management and Co-Director of the Stanley Ho Big Data Decision Analytics Research Centre, CUHK concluded, ‘Our research focuses on the use of data analytics for comparative pedagogical efficacies of online versus classroom teaching and learning, to derive unique and deep insights into individual and group learning processes.’ 

This article was originally published on CUHK Communications and Public Relations Office website.

A team of students has won championship on the PwC HackaDay 2018. It was the second time CUHK students shone in the same hacking competition for two consecutive years. HackaDay is a CTF cybersecurity contest for undergraduate students from universities in Hong Kong, which aimed at increasing the general awareness of the importance of cybersecurity amongst Hong Kong's youth. It also serves as a platform to raise the competency level of new talents to better prepare them for a meaningful career in cybersecurity. A total of nine teams from Hong King universities joined the competition.  

The winning team "g33z" from CUHK was comprised of four undergraduates: Leung Shing Yuet (MIEG), Tong Cham Fei (CS), Zeng Yihui (Math), and Chan Siu Chun (MIEG).