By Erick Remedios Muiños

Baseball Smart Coach: machine learning wristband to analyze the swing

Screenless wristband prototype with inertial sensors and a mobile app that analyzes the batter’s swing and compares it with professional players.

Sport Startup $50,000 – $100,000 6 – 12 months

The price includes design, functional prototyping, product testing and optimization.

Baseball Smart Coach wristband without a screen, with baseballs embroidered on the strap and a swing analysis app
Illustrative visualization based on the prototype developed by Let’s Prototype.

Why develop a machine learning wristband for baseball?

1

Quantitative swing analysis

The goal was a novel, low-cost product that quantifies the batter’s swing in different scenarios.

2

Precise sensors

A wristband manages sensors that give precise cues about the path of the mechanical movement.

3

Comparison with professionals

The app shows the similarity between the player’s movement and that of pros with similar physical traits.

4

Multimodal data

The physical data requested by the app and the environmental data from the wearable complete the model.

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First prototype of Baseball Smart Coach

Baseball Smart Coach screenless wristband with the sensor open, showing the electronic board and battery
Illustrative visualization based on the prototype developed by Let’s Prototype.

Screenless wristband

Fabric wristband with a compact sensor, no screen.

Inertial sensors

Capture the path of the swing’s mechanical motion.

IoT wearable

Sends the collected data for analysis.

Machine learning model

Mathematical model calibrated exclusively for this prototype.

Custom mobile app

Speed, number of swings and technical progress, with graphical comparison.

Electronic integration

PCB, inertial sensor and battery integrated into the module.

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Machine learning for sports prototypes

Smart wristbands for racket sports and baseball are trained with machine learning techniques. These are the three main approaches.

1

Supervised

Algorithms trained on input data and correct results.

2

Unsupervised

Algorithms that interpret patterns in the data without labeled results.

3

Reinforcement

Systems that learn through trial-and-error cycles.

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Project lead of Baseball Smart Coach

Iván Bedia, CEO and technical director of Let’s Prototype
Iván Bedia
CEO and Technical Director, Let’s Prototype
LinkedIn
“A screenless wristband looks simple on the outside, but inside, inertial sensors, firmware and the app have to move in step. That is where the real design is. If we could do this, we can surely do your idea.”

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