NSF news: Artificial Retina Receives FDA Approval

February 14, 2013

From: https://www.nsf.gov/news/news_summ.jsp?cntn_id=126756

The U.S. Food and Drug Administration (FDA) granted market approval to an artificial retina technology today, the first bionic eye to be approved for patients in the United States. The prosthetic technology was developed in part with support from the National Science Foundation (NSF).

The device, called the Argus® II Retinal Prosthesis System, transmits images from a small, eye-glass-mounted camera wirelessly to a microelectrode array implanted on a patient’s damaged retina. The array sends electrical signals via the optic nerve, and the brain interprets a visual image.

The FDA approval currently applies to individuals who have lost sight as a result of severe to profound retinitis pigmentosa (RP), an ailment that affects one in every 4,000 Americans. The implant allows some individuals with RP, who are completely blind, to locate objects, detect movement, improve orientation and mobility skills and discern shapes such as large letters.

The Argus II is manufactured by, and will be distributed by, Second Sight Medical Products of Sylmar, Calif., which is part of the team of scientists and engineers from the university, federal and private sectors who spent nearly two decades developing the system with public and private investment.

“Seeing my grandmother go blind motivated me to pursue ophthalmology and biomedical engineering to develop a treatment for patients for whom there was no foreseeable cure,” says the technology’s co-developer, Mark Humayun, associate director of research at the Doheny Eye Institute at the University of Southern California and director of the NSF Engineering Research Center for Biomimetic MicroElectronic Systems (BMES). “It was an interdisciplinary approach grounded in biomedical engineering that has allowed us to develop the Argus II, making it the first commercially approved retinal implant in the world to restore sight to some blind patients,” Humayun adds.

The effort by Humayun and his colleagues has received early and continuing support from NSF, the National Institutes of Health and the Department of Energy, with grants totaling more than $100 million. The private sector’s support nearly matched that of the federal government.

“The retinal implant exemplifies how NSF grants for high-risk, fundamental research can directly result in ground-breaking technologies decades later,” said Acting NSF Assistant Director for Engineering Kesh Narayanan. “In collaboration with the Second Sight team and the courageous patients who volunteered to have experimental surgery to implant the first-generation devices, the researchers of NSF’s Biomimetic MicroElectronic Systems Engineering Research Center are developing technologies that may ultimately have as profound an impact on blindness as the cochlear implant has had for hearing loss.”

Although some treatments to slow the progression of degenerative diseases of the retina are available, no treatment has existed that could replace the function of lost photoreceptors in the eye.

The researchers began their retinal prosthesis research in the late 1980s to address that need, and in 1994 Humayun received his first NSF grant, an NSF Young Investigator Award, which built upon additional support from the Whittaker Foundation. Humayun used the funding to develop the first conceptualization of the Argus II’s underlying artificial retina technology.

Since that time, he and his collaborators–including Wentai Liu of the University of California, Los Angeles and fellow USC researchers Jim Weiland and Eugene de Juan, Jr.–received six additional NSF grants, totaling $40 million, some of which was part of NSF’s funding for BMES, launched in 2003. BMES drives research into a range of sophisticated prosthetic technologies to treat blindness, paralysis and other conditions.

“We were encouraged by the team’s exploratory work in the 1980s and 1990s, supported by NSF and others, which revealed that healthy neural pathways can carry information to the brain, even though other parts of the eye are damaged,” adds Narayanan. “The retinal prosthesis they developed from that work simulates the most complex part of the eye. Based on the promise of that implant, we decided in 2003 to entrust the research team with an NSF Engineering Research Center,” says Narayanan. “The center was to scale up technology development and increase device sensitivity and biocompatibility, while simultaneously preparing students for the workforce and building partnerships to speed the technology to the marketplace, where it could make a difference in people’s lives. The center has succeeded with all of those goals.”

The researchers’ efforts have bridged cellular biology–necessary for understanding how to stimulate the retinal ganglion cells without permanent damage–with microelectronics, which led to the miniaturized, low-power integrated chip for performing signal conversion, conditioning and stimulation functions. The hardware was paired with software processing and tuning algorithms that convert visual imagery to stimulation signals, and the entire system had to be incorporated within hermetically sealed packaging that allowed the electronics to operate in the vitreous fluid of the eye indefinitely. Finally, the research team had to develop new surgical techniques in order to integrate the device with the body, ensuring accurate placement of the stimulation electrodes on the retina.

“The artificial retina is a great engineering challenge under the interdisciplinary constraint of biology, enabling technology, regulatory compliance, as well as sophisticated design science,” adds Liu. “The artificial retina provides an interface between biotic and abiotic systems. Its unique design characteristics rely on system-level optimization, rather than the more common practice of component optimization, to achieve miniaturization and integration. Using the most advanced semiconductor technology, the engine for the artificial retina is a ‘system on a chip’ of mixed voltages and mixed analog-digital design, which provides self-contained power and data management and other functionality. This design for the artificial retina facilitates both surgical procedures and regulatory compliance.”

The Argus II design consists of an external video camera system matched to the implanted retinal stimulator, which contains a microelectrode array that spans 20 degrees of visual field. The NSF BMES ERC has developed a prototype system with an array of more than 15 times as many electrodes and an ultra-miniature video camera that can be implanted in the eye. However, this prototype is many years away from being available for patient use.

“The external camera system-built into a pair of glasses-streams video to a belt-worn computer, which converts the video into stimulus commands for the implant,” says Weiland. “The belt-worn computer encodes the commands into a wireless signal that is transmitted to the implant, which has the necessary electronics to receive and decode both wireless power and data. Based on those data, the implant stimulates the retina with small electrical pulses. The electronics are hermetically packaged and the electrical stimulus is delivered to the retina via a microelectrode array.”

In 1998, Robert Greenberg founded Second Sight to develop the technology for the marketplace. While under development, the Argus I and Argus II systems have won wide recognition, including a 2010 Popular Mechanics Breakthrough Award and a 2009 R&D 100 Award, but it is only with FDA approval that the technology can now be made available to patients.

“An artificial retina can offer hope to those with retinitis pigmentosa, as it may help them achieve a level of visual perception that enhances their quality of life, enabling them to perform functions of daily living more easily and the chance to enjoy simple pleasures we may take for granted,” says Narayanan. “Such success is the result of fundamental studies in several fields, technology improvements based on those results and feedback from clinical trials–all enabled by sustained public and private investment from entities like NSF.”

For more, please see an NSF Science Nation video on the Argus I technology, and read more about the early stages of development for both devices in this feature story.
https://www.nsf.gov/news/news_videos.jsp?org=NSF&cntn_id=126756&media_id=73830

-NSF-

Brain to Brain Communication

Our Brain-to-Brain communication research focuses on advancing the precision of non-invasive recording and stimulation of the brain cortex. The precision is increased by the development of advanced optimization algorithms combined with accurate tissue modeling. The models are augmented by our development of hardware stimulation and recording systems to allow independent fine-tuned stimulation of large amount of channels and fast data transmission between multiple brain-interface devices in real-time. Our bold aim is to step beyond a brain-computer interface and instead make human brain to brain connection possible, thus making scientific fiction a reality.

 

Congratulations, Dr. Ying Li!

Ying Li Thesis Defense
Left to right: Yi-Wen Meng, Luyao Chen, Dr. Ying Li, Professor Wen-tai Liu, Yushan Wang, Nicole Chow, Ma Li, Jia-Heng Chang and Stanislav Culaclii from UCLA Biomimetic Research Lab

Congratulations to Dr. Ying Li for a wonderful and successful thesis defense!

Stimulation Artifact Cancellation

2016-07-01_15_04_54_02sec-pageLive Stimulation Artifact Cancellation

 

Recovering neural responses from electrode recordings is fundamental for understanding the dynamics of neural networks. This effort is often obscured by stimulus artifacts in the recordings, which result from stimuli injected into the electrode-tissue interface. Stimulus artifacts, which can be orders of magnitude larger than the neural responses of interest, can mask short-latency evoked responses. Furthermore, simultaneous neural stimulation and recording on the same electrode generates artifacts with larger amplitudes compared to a separate electrode setup, which inevitably overwhelm the amplifier operation and cause unrecoverable neural signal loss. This paper proposes an end-to-end system combining hardware and software techniques for actively cancelling stimulus artifacts, avoiding amplifier saturation, and recovering neural responses during current-controlled in-vivo neural stimulation and recording. The proposed system is tested in-vitro under various stimulation settings by stimulating and recording on the same electrode with a superimposed pre-recorded neural signal. Experimental results show that neural responses can be recovered with minimal distortion even during stimulus artifacts that are several orders greater in magnitude.

 

Artifact Cancellation fig1_systemOverview copy
System-Level Overview

 


Publication

“A Hybrid Hardware and Software Approach for Cancelling Stimulus Artifacts During Same-electrode Neural Stimulation and Recording,” Stanislav Culaclii, Brian Kim, Yi-Kai Lo, and Wentai Liu, accepted by EMBC 2016.

Cross Frequency Coupling (CFC)

 

 

CFC-3

 

Cross Frequency Coupling (CFC) is the interaction between brain oscillations of different frequencies, and the coupling phenomenon has been observed in the brain of rodent and human. Phase-amplitude coupling (PAC) is a type of CFC, which describes the dependence between the phase of a low-frequency component and the amplitude of a high-frequency component of electrical brain activities. It has been claimed that the modulation of low frequency phase on high frequency amplitude plays a functional role in cognition and information processing, such as learning and memory. The change of PAC patterns has been associated with various neurological disorders, e.g., epilepsy and  schizophrenia.

Five seizure stages classified by firing patterns (on the left). PAC pattern comparisons between the conventional method (middle) and HHT method (right) of two patients.
Five seizure stages classified by firing patterns (on the left). PAC pattern comparisons between the conventional method (middle) and HHT method (right) of two patients.

Interview for KTLA News

We are honored to have our research projects featured in the KTLA special report “Medical Miracles”. The special will air in May, 2016. The report focuses on our retinal prosthetic device that restores sight for patients with retinitis pigmentosa or age-related macular degeneration and our spinal cord implant to help patients paralyzed due to spinal cord injury regain motor function.

 

Non-stationary and nonlinear techniques for seizure detection algorithms

Epilepsy is one of the most common neurological diseases, affecting over 3 million people in U.S. and 50 million (~1%) people worldwide. An automated and accurate seizure detection method can be very helpful. Currently, most people use stationary and linear methods (i.e. Fast Fourier Transform (FFT), etc.) to analyze the signal. However, EEG signal is non-stationary and nonlinear in nature, thus these methods will introduce inaccuracy. Hence, we are developing non-stationary and nonlinear algorithms to improve the accuracy of seizure detection.
Corr3

 

Collaborators


  1. Dr. Yue-Loong Hsin, Chung Shan Medical University, Taiwan

Electrode-based Bio-imaging

Our goal is to develop an Electrode-based Bio-imaging System that will be fMRI-competitive. Currently, fMRI is very popular since it offers high spatial resolution (~3mm); however, its temporal resolution is limited (~1s) and is impossible to be used in portable applications. EEG has excellent temporal resolution (~1ms), portable mobility that allowed to be used in daily life. Here, we devote to improving the spatial resolution of EEG in the aspects of both hardware and software.
 
1. Hardware
We developed a Focused Electrode that improves spatial resolution, recording SNR and reduce crosstalk and correlation with adjacent electrodes. The Focused Electrode is adaptive to the geometry parameters of electrode array including electrode size, pitch and source depth, such as EEG or ECoG. Simulation results show that the Focused Electrode increases the number of electrodes up to 7x in EEG and 30x in ECoG without overlapping information if the array covers half of head.

300px-Model
2. Software
We study the inverse imaging using realistic head model based on MR image (NFT toolbox). On one hand, we are studying the influence of various factors (i.e. noise, electrode number, head model, inverse solution, etc.) on inverse imaging; on the other hand, we are developing more accurate inverse imaging algorithms.

 

source-localization-gif-2

 

 

 

Collaborators


  1. Prof. Scott Makeig, SCCN, UCSD
  2. Dr. Yue-Loong Hsin, Chung Shan Medical University, Taiwan