Researchers at the College of Engineering at Carnegie Mellon University (CMU) have developed a novel design approach for exoskeletons and prosthetic limbs that incorporates direct feedback from the human body. This technique, called human-in-the-loop optimization, customizes walking assistance for individuals and significantly improves energy economy during walking. The findings were published June 23 in Science.
Optimizing device characteristics on the basis of measured human performance could lead to improved designs.
Photograph courtesy of the study authors and CMU.
“Existing exoskeleton devices, despite their potential, have not improved walking performance as much as we think they should,” said Steven Collins, PhD, a CMU professor of mechanical engineering. “We’ve seen improvements related to computing, hardware, and sensors, but the biggest challenge has remained the human element—we just haven’t been able to guess how they will respond to new devices.”
The new technique uses a software algorithm combined with emulator hardware that automatically identifies optimal assistance strategies for individuals. During experiments, each user received a unique pattern of assistance from an exoskeleton worn on one ankle. The algorithm tested the users’ responses to 32 different patterns over the course of an hour, making adjustments based on measurements of their energy use with each pattern. The optimized assistance pattern produced larger benefits than any exoskeleton to date, including devices acting at all joints on both legs, the researchers said.
“When we walk, we naturally optimize coordination patterns for energy efficiency,” said Collins. “Human-in-the-loop optimization acts in a similar way to optimize the assistance provided by wearable devices. We are really excited about this approach because we think it will dramatically improve energy economy, speed, and balance for millions of people, especially those with disabilities.”
Editor’s note: This story was adapted from materials provided by CMU.
