Menlo Park, CA, United States of America

Caleb T Kemere


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 21(Granted Patents)


Company Filing History:


Years Active: 2006

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1 patent (USPTO):Explore Patents

Title: The Innovations of Caleb T Kemere

Introduction

Caleb T Kemere is an accomplished inventor based in Menlo Park, CA. He has made significant contributions to the field of brain-machine interfaces, particularly in decoding neural signals for movement control. His innovative work has the potential to revolutionize how machines interact with human neural activity.

Latest Patents

Caleb holds a patent for the "Decoding of neural signals for movement control." This brain-machine interface is designed to decode neural signals for the control of machines. It estimates and combines information from two classes of neural activity. The first estimator decodes movement plan information from neural signals representing plan activity, utilizing an adaptive point-process filter or a maximum likelihood filter. The second estimator decodes peri-movement information from neural signals representing peri-movement activity. Each estimator is tailored to estimate different aspects of movement, such as movement goal variables or movement execution variables. He has 1 patent to his name.

Career Highlights

Caleb is affiliated with Leland Stanford Junior University, where he continues to advance his research in neural signal decoding. His work is at the forefront of integrating neuroscience with technology, paving the way for new applications in assistive devices and robotics.

Collaborations

Caleb has collaborated with notable colleagues, including Gopal Santhanam and Byron M Yu. These partnerships enhance the interdisciplinary approach to his research, combining expertise from various fields to drive innovation.

Conclusion

Caleb T Kemere's contributions to the field of brain-machine interfaces exemplify the intersection of neuroscience and technology. His innovative patent and collaborative efforts position him as a key figure in advancing our understanding of neural signal decoding.

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