Seiko Epson had 24 patents in artificial intelligence during Q1 2024. The patents filed by Seiko Epson Corp in Q1 2024 include a fatigue detection device using ultrasonic waves, a method for determining positions and attitudes of objects in a scene, an information processing device for evaluating exercise performance, a method for generating image processing sequences, and a display method for projecting images based on user identification and position. GlobalData’s report on Seiko Epson gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Seiko Epson grant share with artificial intelligence as a theme is 62% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Fatigue detection device, support system, and fatigue detection method (Patent ID: US20240081774A1)
The patent filed by Seiko Epson Corp describes a fatigue detection device that utilizes an ultrasonic device to transmit waves into a living body and detect the reflected waves from tissues to determine the fatigue state of the tissue when a load is applied. The device includes a processor that analyzes the received signals to detect changes in the tissue, specifically focusing on the thickness ratio of the tissue when under load. Additionally, the device can utilize machine learning models to process multiple received signals over different times to accurately determine the fatigue state of the tissue.
Furthermore, the patent also describes a support system incorporating the fatigue detection device, a fatigue information processor, and an annunciator to inform users about their health state based on the fatigue information obtained. The system allows for real-time monitoring and feedback to users regarding their fatigue levels and overall health status. Additionally, a fatigue detection method is outlined, detailing the process of detecting tissue fatigue using the ultrasonic device and analyzing the received signals to determine the tissue's fatigue state when subjected to a load. Overall, the patent presents an innovative approach to fatigue detection and monitoring using ultrasonic technology and machine learning algorithms.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
