(Nanowerk Spotlight) A tennis racket that knows exactly where the ball hits and an elbow pad that tracks every detail of arm movement – these innovations are now helping players improve their game without expensive coaching or complex equipment. Scientists have created these devices using special yarns that generate electricity from motion, enabling the equipment to analyze technique and provide instant feedback through a smartphone app.
Every tennis stroke involves dozens of precise movements. A slight change in elbow position or racket angle can mean the difference between a winning shot and one that sails beyond the baseline. While professional players benefit from sophisticated motion analysis systems and dedicated coaches, most tennis enthusiasts lack access to detailed technical feedback about their form.
Traditional motion tracking systems use high-speed cameras and optical sensors, but their complexity and cost restrict them to elite training facilities. Personal fitness devices offer a simpler alternative, but their rigid construction and dependence on battery power make them impractical for analyzing tennis movements. Players need technology that can track their motions without interfering with their game.
Scientists have attempted to create flexible, wearable sensors for sports training, but these devices typically suffer from three key problems: they break down under repeated impact, produce inconsistent signals, or require frequent battery changes. Creating sensors that combine durability, reliability, and energy independence has remained an unsolved challenge.
A research team from Soochow University has now developed a solution that overcomes these limitations. They created special yarns that generate their own electricity from movement, wove them into fabric, and used them to build a tennis training system that gives players immediate feedback on their technique.
Schematic diagram of the smart tennis training system. (Image: Reprinted with permission by Wiley-VCH Verlag) (click on image to enlarge)
These new yarns work through two different mechanisms to produce electrical signals. They contain tiny piezoelectric fibers that generate electricity when bent or compressed, surrounded by a silicone rubber coating that produces additional power when it contacts other materials. This combination generates more power than either method alone.
The manufacturing process starts with a flexible, conductive core yarn. The researchers coat this core with nanoscale piezoelectric fibers, then add the outer silicone layer. The finished yarn remains as flexible as regular textile thread but can detect even gentle pressure. Laboratory testing demonstrated the yarn’s durability under real-world conditions. It maintained consistent performance after four days of direct sunlight exposure at temperatures above 30 degrees Celsius, showed stable output across humidity levels from 20% to 80%, and survived 30 washing cycles without significant degradation.
The team used these yarns to create two key pieces of equipment. The modified tennis racket contains a grid of nine sensor zones that detect where the ball hits and how hard. The sensors add only 40 grams to the racket’s weight, about the same as four sheets of paper. The elbow pad uses panels of knitted sensor yarn to track arm movement during different tennis strokes.
A sophisticated artificial intelligence system analyzes the electrical signals from both devices. The system uses a type of artificial neural network called a convolutional neural network (CNN), which excels at pattern recognition in complex data. The research team trained the CNN using thousands of recorded tennis movements, enabling it to recognize six basic tennis motions: forehand and backhand volleys, forehand and backhand drives, slice, and serve. More importantly, it can spot common technical flaws like poor racket angles or incorrect elbow positions.
Players see this analysis through a mobile app that shows both written instructions and visual guides. The system divides each tennis stroke into three phases – swing, shot, and finish – and provides specific feedback for each phase. In testing, it correctly identified different tennis motions 95% of the time and spotted incorrect racket angles with 98% accuracy. All this happens without batteries – the system powers itself entirely through the player’s movements and ball impacts.
The smart racket’s sensor grid proved particularly useful for identifying problems with ball placement on the racket face. When players hit the ball too close to the racket’s edge, the system immediately alerts them through the app. This immediate feedback helps players develop better control and consistency in their shots.
Smart tennis racket and the shot monitoring system. a) Photograph of the smart tennis racket. b) The open-circuit voltage and short-circuit current of the smart tennis racket hit by a tennis ball falling from different heights. c) Schematic diagram of tennis trajectory. d) Voltage output signals from the nine channels at different racket surface angles. e) Distribution mapping figure based on the voltage outputs at three different hitting angles. f) The voltage outputs of three volunteers. g) The APP interface of the shot monitoring module. h) Schematic diagram of the edge contact between a tennis ball and the smart racket. i) The voltage outputs from the nine channels with different edge contacts. j) Photograph depicting the integration of two modules in the tennis training system. (Image: Reprinted with permission by Wiley-VCH Verlag) (click on image to enlarge)
Beyond tennis, this technology opens new possibilities for sports training equipment. The combination of self-powered sensors, flexible materials, and artificial intelligence could help athletes in many sports improve their technique while avoiding injuries. The manufacturing methods developed for these sensor yarns could also lead to new types of smart clothing and equipment.
The work marks an important advance toward practical sports monitoring systems that don’t need batteries or complex setups. By making sophisticated motion analysis more accessible, this technology could help players at all skill levels develop better technique and enjoy the game with less risk of injury.
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