"Accurate to muscle"! Look at the intelligent "personal trainer" of Winter Olympic athletes.

Xinhua news agency, Beijing, October 16 (reporter Xu Zhao)

In a laboratory with many pieces of scientific and technological equipment at Beijing Institute of Technology, two researchers are helping subjects attach electrode sheets to the skin surface of upper limb muscles. After the EMG device was worn, the subjects swung their arms, and the waveform track of the collected electrical signal was displayed on the screen on one side in real time.


Huang Yi, a student at the School of Astronautics of BIT, wears a pressure insole (photographed on October 14). Photographed by Xinhua News Agency reporter Ren Chao.

"This set of EMG equipment is applied to the physical training of Winter Olympic athletes. Electrode pieces are pasted on the skin of athletes at different positions to monitor the degree and order of activation of corresponding muscles during exercise. We can calculate the muscle strength according to this information, and then feed back the data to the physical fitness coaches mobilized, so that they can more specifically guide the athletes to strengthen their exercise "Muscle Groups," said Huo Bo, a professor at the school of Astronautics of BIT.

In response to the needs of preparing for the 2022 Beijing Winter Olympics, Beijing Institute of Technology has undertaken the project of "research and demonstration of key technologies in the construction of national scientific training base" in the special project of "science and technology Winter Olympics" of the Ministry of science and technology. As the project leader, Huo Bo led the team to develop the "intelligent training management system for winter events", which provides personalized, intelligent and "accurate to muscle" training programs for national team athletes in Winter Olympic Events such as ski jumping, freestyle ski jumping, snowmobile sledge and cross-country skiing.


Chen Xue, a student at the School of Astronautics of BIT, adjusted the angle of the calibration frame (photographed on October 14). Photographed by Xinhua News Agency reporter Ren Chao.

Huo Bo introduced that in addition to the EMG equipment used in physical training, the system can also collect the three-dimensional posture parameters of athletes in different events during actual training by installing multiple groups of high-speed cameras in the training field. At the same time, it can collect the ground reaction force and other information of athletes when landing by using the ultra-thin pressure insole equipped with nearly 100 pressure sensors, After the automatic recognition is completed through in-depth learning, the team will analyze and evaluate the athletes' sports ability in combination with aerodynamic analysis, skeletal muscle dynamics analysis, kinematics analysis and other methods.

How to take off more easily? How to reduce wind resistance? What detail factors affect the duration and distance of air gliding? Does the athlete have negative acceleration during sledding With the help of this technology, coaches and athletes can deeply understand the whole process of athletes' sports state in a more intuitive and scientific way, and continuously adjust the sports posture and force mode by comparing the analysis reports obtained each time, so as to help athletes explore the individual "optimal solution" and continuously improve their training results.


Sun Qing (right), a student from the School of Astronautics of BIT, helped subject Huang Yi attach the EMG sensor to the skin surface of the upper limb muscles (photographed on October 14). Photographed by Xinhua News Agency reporter Ren Chao.

"The application of quantitative testing and analysis system in training has a process of acceptance for athletes. In the process of training and communication with athletes and coaches, we translate scientific and technical terms and mechanical vocabulary into sports related languages to better help them familiarize themselves with and make full use of this system. For example, for ski jumpers, after comprehensive analysis , it is suggested that athletes should pedal and extend their knees as much as possible during the take-off process, and appropriately reduce the extension speed of hip joints to reduce the wind resistance of the trunk. In the later stage of training, athletes will always take the initiative to check the report, "said Jiang Liang, a member of the project team and a doctoral student of the school of Astronautics of BIT.

Starting from 2019, Jiang Liang and other members of the team took the system to follow the national teams of Different Winter Olympic events to help athletes train. "The R & D and application of the equipment have experienced a process from scratch. In recent years, the system has also completed many upgrading iterations," Jiang Liang said.


Students from the School of Astronautics of BIT collected data on pressure insoles (photographed on October 14). Photographed by Xinhua News Agency reporter Ren Chao.

"This set of scientific and technological equipment and core technology for Winter Olympic training has been relatively mature. At present, it has been at the cutting-edge level in the same industry. In particular, we have introduced aerodynamic calculation to obtain the air resistance suffered by athletes when taking off in ski jumping events, and applied it to the analysis of skeletal muscle system dynamics. This method has not been reported in the literature." Huo Bo told reporters that after completing the mission of serving the Winter Olympic training, the system will be applied to human rehabilitation training, public health assistance, scientific research and popular science and other scenes.

"It is a great wealth for me to have a complete experience and deeply participate in and serve the Winter Olympics through what I have learned. When the Beijing Winter Olympics is officially held, I especially hope to go to the scene to watch the games and witness the team members who have fought side by side in the ice and snow. I will be very proud and proud," said Jiang Liang.