JHU Neuroengineering & Biomedical Instrumentation Lab
The Neuroengineering & Biomedical Instrumentation Lab is run by Prof. Nitish Thakor at Johns Hopkins University in Baltimore, MD.
The mission and interest of our laboratory is to study the brain and translate that knowledge into clinical applications. The mission and interest of our laboratory is to develop novel instrumentation and technologies to study the brain at several levels - from single cell to the whole brain - with the goal of translating the work into practical research and clinical applications. Our personnel in
10/09/2018
Big congratulations to Luke Osborn for being named a Siebel Scholar!
Two biomedical engineering graduate students named Siebel Scholars Biomedical engineering PhD students John Hickey and Luke Osborn have been named Siebel Scholars for 2019, an annual award that recognizes nearly 100 of the top graduate students from universities across the nation who are studying in the fields of business, bioengineering, computer science, and ener...
Congratulations to our lab alumnus, Damini Agarwal, for receiving her second Google Leadership Award, which will involve her with Google's network of emerging leaders in today's world!
07/22/2018
Undergraduate BME Christopher Shallal traveled to the 40th International Conference of IEEE EMBS in Honolulu, Hawaii last week to present the adaptive socket team's paper, titled "Dynamically Mapping Socket Loading Conditions During Real Time Operation of an Upper Limb Prosthesis". The paper was co-authored by Jonathan Fu, Harrison Nguyen, William Kim and Jasmine Cho, all undergraduates in the lab!
06/27/2018
Hear Johns Hopkins Biomedical Engineering graduate student Luke Osborn talk about some of our latest work with Frank Stasio on "The State of Things" on WUNC.
Ouch! What Is Pain, And What Is It Good For? Researchers have developed a new part for a prosthetic hand: a synthetic skin that can feel pain. The electronic dermis, or “e-dermis,” fits over the
06/21/2018
Nice coverage on some of our recent work. Thanks IEEE Spectrum!
A Prosthetic That Feels Pain Electronic receptors mimic the ability of human skin to sense pain and pressure
06/20/2018
Our paper on a neuromorphic multilayered e-dermis for pain detection in a prosthesis is out now in Science Robotics.
http://robotics.sciencemag.org/content/3/19/eaat3818
Also in the same issue is a paper on simultaneous and proportional prosthesis control.
http://robotics.sciencemag.org/content/3/19/eaat3630
Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain The human body is a template for many state-of-the-art prosthetic devices and sensors. Perceptions of touch and pain are fundamental components of our daily lives that convey valuable information about our environment while also providing an element of protection from damage to our bodies. Advances....
06/18/2018
IBT is moving to downtown Baltimore!
When you are mailing or returning a product after July 2nd, please use our new address:
8 Market Place, Suite 500
Baltimore MD 21202
We are very excited about our new space in the heart of the city!
03/26/2018
Our recent paper on using adaptive sparse representations for improving myoelectric prosthesis control is featured on IEEE Trans. Biomed. Eng.'s website: https://goo.gl/2Co8FM! Read the full paper here: http://ieeexplore.ieee.org/document/7956176/
Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations from Extreme Learning Classification algorithms used to predict intended movements of an amputee for upper-limb prosthesis control using EMG signals must tolerate changes in limb position and loads which affect those signals. Extreme Adaptive Sparse Representation Classification (EASRC) significantly outperforms other cl...
01/10/2018
Lab Bio: Sapna Kumar
"I am a masters student who is interested in the study of electrode interface to measure surface Electromyography (sEMG) and its signal source in people with upper limb amputations. My work involves developing an electrode interface for EMG signal source optimization to improve performance of upper limb Myoelectric control systems."
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