Mountain View, CA, United States of America

Kevin R Wheeler


Average Co-Inventor Count = 3.1

ph-index = 2

Forward Citations = 426(Granted Patents)


Company Filing History:


Years Active: 2002-2004

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2 patents (USPTO):Explore Patents

Title: Kevin R. Wheeler: Innovator in Bioelectric Signal Recognition

Introduction

Kevin R. Wheeler is a notable inventor based in Mountain View, CA (US). He has made significant contributions to the field of bioelectric signal recognition, holding a total of 2 patents. His work focuses on developing methods and systems that enhance the interaction between humans and machines through gesture recognition.

Latest Patents

One of his latest patents is titled "Characterization of Bioelectric Potentials." This invention outlines a method and system for recognizing and characterizing bioelectric potential or electromyographic (EMG) signals associated with both coarse and fine gestures performed by a person. The system utilizes statistical averaging of bioelectric signals during selected time intervals as gestures are performed. Hidden Markov model analysis is employed to identify hidden, gesture-related states. A metric is used to compare signals from a volitional gesture with those of reference gestures, allowing the system to identify the closest match. This technology has applications in controlling aircraft, data entry from keyboards, and operating instruments in extreme environments.

Career Highlights

Throughout his career, Kevin has worked with prestigious organizations, including IBM and the United States of America as represented by the Administrator of NASA. His experience in these companies has contributed to his expertise in the field of bioelectric signal processing.

Collaborations

Kevin has collaborated with notable individuals such as David Charles Martin and Hansel Joseph Miranda, further enriching his work and contributions to the field.

Conclusion

Kevin R. Wheeler's innovative work in bioelectric signal recognition demonstrates his commitment to advancing technology that enhances human-machine interaction. His patents reflect a deep understanding of gesture recognition and its practical applications in various fields.

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