University of Houston researchers are helping the Pentagon build reliable mind-controlled prosthetic devices that military and civilian amputees can use the rest of their lives. Prosthetic limbs that can be maneuvered by neural implants have shown promise in the laboratory, but there are challenges to making them work in the real world. Chief among these obstacles is the neural implants’ nearly inevitable failure over time, often in a matter of weeks. Roysam and his group have received a three-year, $5.4 million grant from the Defense Advanced Research Projects Agency (DARPA). Researchers from Seattle Children’s Research Institute, the University of Michigan, Rensselaer Polytechnic Institute and two companies also are involved in the project.
The grant is part of DARPA’s Histology for Interface Stability Over Time program, which is the next phase of its Revolutionizing Prosthetics project that began in 2000
Roysam said neural implants can fail within six to eight weeks. Once implanted, the brain treats these tiny devices like foreign objects and immediately begins to try to isolate them for its own protection.
“The tissue surrounding the device undergoes complex changes that in the end isolate it electrically. At this point, it (the implant) stops functioning,” Roysam said.
All existing methods to extract human neural information are inadequate for high-performance prostheses, because either the level of extracted information is too low (< 500 events/sec) or the functional lifetime is too short (< 2 years). Recent technological advances present new opportunities to solve both of these neural interface limitations. The HIST program contains a multi-disciplined perspective necessary to quantitatively and objectively study the mechanisms and pathways that lead to the short operational lifetime of nearly all existing neural-recording-interface technologies. One of the blue-sky aspects of this program is to develop methods to accelerate interface-reliability evaluation. This is a technique which is commonly used in semiconductor design device and manufacturing, but has not successfully been deployed in the biological domain. The four technical areas being advanced by the HIST program are: 1. Quantitatively identify dominant failure mechanisms of neural-recording interfaces, with objectivity and strong statistical confidence. 2. Develop new quantitative in-vitro and in-vivo techniques for assessing neural-recording-interface degradation and failure. 3. Predict the failure of neural-recording interfaces by creating new statistically validated models and early-precursor-signal-based techniques. 4. Accelerate the failure of neural-recording interfaces by creating new statistically validated models and stressor-signal-based techniques. The HIST program will develop tissue-response-mitigating implanted cortical microelectrodes, which can extend interface lifetime well beyond 2 years and toward the lifetime of the patient. Furthermore, the program will develop predictive models of failure, robust indicators of interface reliability, repeatable insertion methodologies, and high-throughput biological test techniques . This will enable the technology required to reliably extract information from the nervous system, and to do so at a scale and rate necessary to control many degree-of-freedom (DOF) machines, such as high-performance prosthetic limbs. Technologies and techniques emerging from this program will enable the construction of reliable neural-recording interfaces, which will be suitable for clinical use over the lifetime of an injured soldier (~70 years). Additionally, an objective understanding of the failure mechanisms will lead to high-throughput biological testing, due to the discovery of predictive markers linked to a high probability of failure and other accelerated-testing techniques.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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