Bionic legs that use sensors and a control system to allow amputees to seamlessly traverse almost any terrain; robotic arms with a sophisticated brain-computer interface (BMI) allow paralyzed patients to closely match the speed and coordination of a typical human limb; even a computerized bladder that could eventually alert patients with spinal cord injury when to go to the bathroom.
These are just some examples of BMIs that harness electrical activity produced by neurons in the brain to control the movement of a variety of robotic devices. The hope is that in the not-too-distant future, patients with a variety of neurologic disorders may recover their mobility and leave their wheelchair and other clumsy assistive devices behind.
The field of robot-assisted healthcare is burgeoning, but although the technology is evolving rapidly, such issues as regulatory approvals, clinician training, and high costs stand in the way of biomedical robotics eventually becoming part of everyday medicine.
New research into robotic and neuroprosthetic technologies, along with several review and perspective articles examining the state of the art in this field, was highlighted November 6 in a special issue of Science Translational Medicine.
Robotic Legs
In 1 report, Michael Goldfarb, PhD, professor, mechanical engineering, and professor, physical medicine and rehabilitation, Vanderbilt University, Nashville, Tennessee, and colleagues describe components of the latest robotic leg technology. These components include ankle and knee motors, knee and ankle angle sensors, and heel and toe ground force reaction sensors.
The sensors replace aspects of the peripheral nervous system. Combined information from these sensors is fed into a microcontroller, which provides the equivalent function of the central nervous system (CNS).
To measure information from the CNS, and to act in unison with it, electrodes can be implanted in the peripheral nerves or motor cortex. Because the robotic limb is isolated from the metabolic power supply (the circulatory system), the prosthesis has its own power supply, often an electric battery.
Since the robotic prosthesis can emulate all aspects of muscular function, it can reproduce many biomechanical features that aren't possible with conventional prostheses. For example, users have enhanced gait symmetry and stable, controlled movements and can better negotiate slopes and stairs.
They're also less likely to fall. "[R]ecent studies indicate that the annual incidence of falls in the lower-limb amputee population exceeds that of the elderly population, the rate of seeking medical attention as a result of such falling is comparable with that of the institution-living elderly, and the incidence of falling (and consequently requiring medical attention) is higher in younger amputees than in older amputees, presumably because younger amputees are less restrained in their choice of activities and terrain," Dr. Goldfarb and colleagues write.
Another benefit of this new robotic leg is that unlike energetically passive prostheses, it doesn't necessitate compensatory movements that increase the stress on intact joints, which can lead to musculoskeletal degeneration.
The authors point out that studies on the biomechanical benefits of robotic leg prostheses with physical sensor interfaces have appeared in the literature and the devices have started to emerge on the commercial market.
Future models promise to be even more functional, and the authors expect that the full promise of robotic prostheses will increasingly be realized. The result, they said, should be improvement in patient mobility and quality of life.
Moving Arms
Similar translational technology is being applied to other limbs. Researchers have developed a robotic arm that patients with spinal cord injury and other paralyzed patients can learn to maneuver via a sophisticated brain-computer interface.
In one example, reported last December in The Lancet, surgeons using stereotactic image guidance with structural and functional MRI implanted 2 microelectrodes into the left motor cortex of a woman with chronic tetraplegia due to spinocerebellar degeneration. This allowed researchers to pinpoint and record neuronal activity when the woman was asked to imagine using her hand and arm.
After some practice, the woman was able to grasp items and fluidly move the hand with the coordination, skill, and speed of an able-bodied person.