Company Filing History:
Years Active: 2023
Title: Linean Zou: Innovator in Cycle Recognition Technology
Introduction
Linean Zou is a notable inventor based in San Jose, CA (US). He has made significant contributions to the field of motion sensing and performance monitoring through his innovative patent. His work focuses on enhancing the recognition of cycle durations in repeated activities, which has broad applications across various industries.
Latest Patents
Linean Zou holds a patent titled "Methods and system for cycle recognition in repeated activities by identifying stable and repeatable features." This patent describes a system and method for monitoring the performance of repeated activities. The system comprises a motion sensing system and a processing system. The motion sensing system includes sensors configured to measure or track motions corresponding to a repeated activity. The processing system processes motion data received from the motion sensing system to recognize and measure cycle durations in the repeated activity. Unlike conventional systems, which may only work for standardized repeated activities, Zou's system can recognize and monitor cycle durations even when significant abnormal motions are present. This innovation allows for a much broader set of applications compared to traditional methods.
Career Highlights
Linean Zou is currently employed at Robert Bosch GmbH, where he continues to develop and refine technologies related to motion sensing and cycle recognition. His expertise in this area has positioned him as a valuable asset to his team and the company.
Collaborations
Linean collaborates with talented coworkers, including Huan Song and Liu Ren, who contribute to the innovative projects at Robert Bosch GmbH.
Conclusion
Linean Zou's work in cycle recognition technology exemplifies the potential of innovative solutions in enhancing performance monitoring. His contributions are paving the way for advancements in various applications, showcasing the importance of innovation in today's technological landscape.