A team led by Dr Billy SO, core member of the Research Institute for Sports Science and Technology (RISports) and Assistant Professor of the Department of Rehabilitation Sciences at The Hong Kong Polytechnic University (PolyU), is committed to enhancing the performance of swimmers by integrating sports technology with biomechanics. By employing advanced wearable sensors and an underwater camera system, the team captures and analyses data on swimmers’ start jump motion and swimming postures, including body movement and muscle activity, thereby assisting coaches in designing training programmes for athletes. The student swimming team of the Diocesan Girls’ School (DGS) is currently adopting these biomechanical training methods into their routine training with the aim of achieving greater effectiveness.
To catalyse joint research in the fields of sports science and technology, PolyU RISports and DGS have entered into a Memorandum of Understanding to establish the “PolyU-DGS AI Swimtech Laboratory”. Under the agreement, DGS will provide swimming facilities, where PolyU researchers will install equipment for data collection and will arrange student swimmers to participate in a research trial. This collaboration aims to strengthen research on enhancing elite athletes’ performance and talent identifications by more fully unleashing their potential, thereby maximising athletic performance at school level and nurturing more outstanding swimmers for the local community in the long run. It also aspires to promote STEM education and foster a culture of innovation and technology on campus.
Prof. Christopher CHAO, PolyU Vice President (Research and Innovation) remarked, “In recent years, Hong Kong’s ‘flying fishes’ continue to shine on the international stage. The integration of technology in athletic training not only more effectively unlocks their potential, but also helps them achieve notable results. PolyU is committed to the translation of research outcomes and so is delighted to collaborate with Diocesan Girls’ School to enhance their student athletes’ competitiveness. We believe that students can gain valuable immersive learning experiences by participating in research work, which helps cultivate their interest in innovation and technology, as well as develops knowledge in mathematics, science and engineering.”
Mrs Stella LAU, Headmistress of DGS stated, “Diocesan Girls’ School, a school with over 160 years of history, has been at the forefront in promoting innovative technology education in recent years. Today, RISports team from PolyU is collaborating with our swimming athletes to put their research achievements in artificial intelligence and biomechanics into practice. Not only will this empower our student athletes to excel in their swimming performance, it will enhance our students’ practical application capabilities in sports science as well as their problem-solving skills using artificial intelligence. This project better equips our students for today’s vast innovation and technology-driven world.”
Each subtle movement can be the key to victory in competitive swimming, especially in short course competition. With this in mind, Dr Billy So aspires to develop systematic biomechanical training and explore its effectiveness in enhancing swimmers’ performance. The key findings of his research are as follow:
(1) Start jump motion analysis
The start jump in swimming demands precise timing, speed and angle of both the jump and entry into the water. The team places patches of a surface electromyography system on athletes’ lower limbs to capture start jump motion. With the use of a reaction time start board and video analytics, the system also provides immediate data on jump reaction, entry angles and speed, to assist swimmers in promptly adjusting their start jump posture. Approximately 30 DGS swimming team students were invited to participate in a six-week training programme, employing this system during 50-metre freestyle swimming practice twice a week for 20 minutes per session. The participants are found to have improved their performance by an average of 0.127 seconds on start jump. By utilising the system to compare and analyse the start jump reaction of participating athletes before and after training, the results show that their average reaction time improved by 0.127 seconds.
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With the use of surface electromyography system, a reaction time start board and video analytics, the system captures start jump motion with a view to assisting athletes in promptly adjusting their posture. | |
(2) Propulsive force analysis
The propulsive force in swimming originates from stroking and kicking, while the stability of core muscles aids in increasing the propulsive force generated from these movements. The team employs an underwater surface electromyography system and a tethered swimming testing system to analyse the propulsive force generated by athletes during swimming. This helps coaches adjust athletes’ techniques and develop suitable training to enhance swimming performance. Approximately 30 student athletes from PolyU and local sports organisations participated in an eight-week muscle training programme focused on core stability. The two systems were then employed to evaluate the athletes’ performance in utilising core muscles during swimming and the propulsive force generated. The results indicate that the average swimming propulsive force generated by the participating athletes increased by about 10%, while their speed in the 50-metre freestyle improved by 0.02 to 0.03 metres per second.
Employing an underwater surface electromyography system and tethered swimming testing system helps the team analyse the propulsive force generated by athletes during swimming. This aids coaches in adjusting athletes’ techniques and developing suitable training to enhance swimming performance.
(3) Muscle activity analysis
The team uses waterproof wearable surface electromyography sensors and an underwater camera system to capture muscle activity of swimmers’ arms, shoulders, legs and trunk during start jumps, strokes and turns in freestyle swimming. The system will be tested in the swimming pool at DGS with the participation of its elite student swimmers.
Looking forward, the team will collaborate with PolyU’s Department of Computing to integrate video motion analysis and wearable motion inertial sensors to leverage the collected data in developing a novel artificial intelligence model, thereby further enhancing the accuracy of the system.
The team has employed waterproof wearable surface electromyography sensors and an underwater camera system to capture muscle activity of swimmers during freestyle swimming. The graphic shows the muscle activity pattern.
