Simplified analysis method could lead to improved prosthetics, a Stanford study suggests

Brain-machine interfaces (BMI) are an emerging field at the intersection of neuroscience and engineering that may improve the quality of life for amputees and individuals with paralysis. These patients are unable to get signals from their motor cortex — the part of the brain that normally controls movement — to their muscles.

Researchers are overcoming this disconnect by implanting in the brain small electrode arrays, which measure and decode the electrical activity of neurons in the motor cortex. The sensors’ electrical signals are transmitted via a cable to a computer and then translated into commands that control a computer cursor or prosthetic limb. Someday, scientists also hope to eliminate the cable, using wireless brain sensors to control prosthetics.

In order to realize this dream, however, they need to improve both the brain sensors and the algorithms used to decode the neural signals. Stanford electrical engineer Krishna Shenoy, PhD, and his collaborators are tackling this algorithm challenge, as described in a recent paper in Neuron.

Currently, most neuroscientists process their BMI data looking for “spikes” of electrical activity from individual neurons. But this process requires time-consuming manual or computationally-intense automatic data sorting, which are both prone to errors.

Manual data sorting will also become unrealistic for future technologies, which are expected to record thousands to millions of electrode channels compared to the several hundred channels recorded by today’s state-of-the-art sensors. For example, a dataset composed of 1,000 channels could take over 100 hours to hand sort, the paper says. In addition, neuroscientists would like to measure a greater brain volume for longer durations.

So, how can they decode all of this data?

Shenoy suggests simplifying the data analysis by eliminating spike sorting for applications that depend on the activity of neural populations rather than single neurons — such as brain-machine interfaces for prosthetics.

In their new study, the Stanford team investigated whether eliminating this spike sorting step distorted BMI data. Turning to statistics, they developed an analysis method that retains accuracy while extracting information from groups rather than individual neurons. Using experimental data from three previous animal studies, they demonstrated that their algorithms could accurately decode neural activity with minimal distortion — even when each BMI electrode channel measured several neurons. They also validated these experimental results with theory.

 “This study has a bit of a hopeful message in that observing activity in the brain turns out to be easier than we initially expected,” says Shenoy in a recent Stanford Engineering news release. The researchers hope their work will guide the design and use of new low-power, higher-density devices for clinical applications since their simplified analysis method reduces the storage and processing requirements.

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Photo by geralt.

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Designing an inexpensive surgical headlight: A Q&A with a Stanford surgeon

2017_Ethiopia_Jared Forrester_Black Lion_Pediatric OR by cell phone_2_crop
Photo by Jared Forrester / © Lifebox 2017

For millions of people throughout the world, even the simplest surgeries can be risky due to challenging conditions like frequent power outages. In response, Stanford surgeon Thomas Weiser, MD, is part of a team from Lifebox working to develop a durable, affordable and high-quality surgical headlamp for use in low-resource settings. Lifebox is a nonprofit that aims to make surgery safer throughout the world.

Why is an inexpensive surgical headlight important?

“The least expensive headlight in the United States costs upwards of $1000, and most cost quite a bit more. They are very powerful and provide excellent light, but they’re not fit for purpose in lower-resource settings. They are Ferraris when what we need is a Tata – functional, but affordable.

Jared Forrester, MD, a third-year Stanford surgical resident, lived and worked in Ethiopia for the last two years. During that time, he noted that 80 percent of surgeons working in low- and middle-income countries identify poor lighting as a safety issue and nearly 20 percent report direct experience of poor-quality lighting leading to negative patient outcomes. So there is a massive need for a lighting solution.”

How did you develop your headlamp specifications?

“Jared started by passing around a number of off-the-shelf medical headlights with surgeons in Ethiopia. We also asked surgeons in the U.S. and the U.K. to try them out to see how they felt and evaluate what was good and bad about them.

We performed some illumination and identification tests using pieces of meat in a shoebox with a slit cut in it to mimic a limited field of view and a deep hole. We asked surgeons to use lights at various power with the room lights off, with just the room lights on and with overhead surgical lights focused on the field. That way we could evaluate the range of light needed in settings with highly variable lighting, something that does not really exist here in the U.S.”

How do they differ from recreational headlamps?

“Recreational headlights have their uses and I’ve seen them used for providing care — including surgery. However, they tend to be uncomfortable during long cases and not secure on the head. Also, the light isn’t uniformly bright. You can see this when you shine a recreational light on a wall: there is a halo and the center is a different brightness than the outer edge of the light. This makes distinguishing tissue planes and anatomy more difficult.”

What are the barriers to implementation?

“While surgeons working in these settings all express interest in having a quality headlight, there is no reliable manufacturer or distributor for them. Surgeons cannot afford expensive lights, and no one has stepped up to provide a low-cost alternative that is robust, high quality and durable. We’re working to change that.”

What are your next steps?

“We are now evaluating a select number of headlights and engaging manufacturers in discussions about their current devices and what changes might be needed to make a final light at a price point that would be affordable to clinicians and facilities in these settings. By working through our networks and using our logistical capacity, we can connect the manufacturer with a new market that currently does not exist  — but is ready and waiting to be developed.

We believe these lights will improve the ability of surgeons to provide better, safer surgical care and also allow emergency cases to be completed at night when power fluctuations are most problematic. These lights should increase the confidence of the surgeon that the operation can be performed safely.”

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.