Researchers have created a new kind of sensor for badminton players that is affordable, flexible, and easy to customize. They used triboelectric sensors to make their monitoring system adaptable for wearable devices. To make sure the sensors wouldn’t interfere with movement, they made a flexible sensor in the shape of an arch that is comfortable to wear and can be personalized for each athlete.
Athletes today are always looking for ways to improve their training. Coaches and trainers use advanced data monitoring tools like videos and wearable sensors to help athletes get better. However, traditional methods often don’t give a complete view of an athlete’s performance.
In APL Materials, by AIP Publishing, researchers from Lyuliang University have created a sensor specifically for badminton players to address these limitations.
Badminton involves many technical movements that require precise speed and accuracy. Monitoring these movements is tricky because of limited camera angles and uncomfortable wearable sensors.
Lead author Yun Yang said: “We combined our knowledge of flexible sensor technology and intelligent systems to analyze badminton techniques quantitatively, providing better guidance for players.”
The team chose triboelectric sensors because they are simple to use in wearable devices. These sensors generate charge when materials rub against each other and don’t need an external power source.
To prevent interference during movement, the team created a 3D-printed flexible sensor in an arch shape covered with a special type of plastic. This design is comfortable, customizable, and suitable for different body parts in motion.
The sensor system consists of three 3D-printed sensors, a data collection card, and advanced algorithms. It offers real-time feedback to athletes and can recognize seven common badminton movements with high accuracy.
Yang added: “Our research suggests solutions for the limitations of current sensors and opens up possibilities for sports monitoring and analysis, which is crucial in the age of big data.”
Future research will focus on using these sensors for health monitoring and medical diagnostics.