adidas has been granted a patent for a health and fitness monitoring system that automatically detects cycling workouts. The system uses an electronic device with a GPS receiver, processor, and memory to analyze speed data and patterns to identify when an individual is engaged in cycling activities. GlobalData’s report on adidas gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on adidas, Footwear 3D Printing was a key innovation area identified from patents. adidas's grant share as of January 2024 was 70%. Grant share is based on the ratio of number of grants to total number of patents.
Patent granted for system detecting cycling workouts using gps data
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A recently granted patent (Publication Number: US11878213B2) discloses a health and fitness monitoring system designed to automatically detect cycling workouts of an individual. The system includes an electronic device equipped with a GPS receiver, processor, and memory. The processor processes GPS data into speed segment data streams, organizes them into time-stamped buckets with cycling-specific speed classifications, and detects patterns indicating cycling activity based on speed variations and the array of data.
Furthermore, the system defines cycling-specific speed classifications based on thresholds for different speed ranges, including slower than cycling speed, cycling speed, faster than cycling speed, and too fast to be cycling speed. The processor also determines candidate start density thresholds and minimum time active thresholds to accurately identify the start and end of cycling activities. Additionally, a method for health and fitness monitoring is outlined, involving the processing of GPS data, acceleration data, and the analysis of acceleration patterns to determine cycling activity based on specific criteria such as candidate start density thresholds and maintenance average density thresholds. The method also includes resetting the data array under certain conditions and utilizing an acceleration sensor to enhance pattern detection based on acceleration data.
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