Optimizing Exoskeleton Assistance for Faster Self-Selected Walking.

Area of Science:

• Biomechanics
• Robotics
• Human-computer interaction

Background:

• Self-selected walking speed is crucial for mobility.
• Exoskeletons can augment walking speed, but optimal assistance strategies and performance limits are not fully understood.

Purpose of the Study:

• To investigate if ankle exoskeleton assistance can substantially enhance self-selected walking speed using human-in-the-loop optimization.
• To determine the upper limits of walking speed augmentation with exoskeletons.

Main Methods:

• Employed human-in-the-loop optimization to identify speed-maximizing exoskeleton torque patterns.
• Healthy participants (N=10) walked on a treadmill with tethered ankle exoskeletons.
• Compared walking speeds achieved with speed-optimized torque versus energy-optimized or slow-walking torque.

Main Results:

• Participants walked 42% faster with speed-optimized ankle exoskeleton torque (1.83 m/s) compared to normal shoes (1.31 m/s).
• Speed increases varied significantly across individuals (6% to 91%).
• Metabolic cost of transport changes were variable, averaging a 2% decrease.

Conclusions:

• Ankle exoskeletons, when optimized for speed, can dramatically increase self-selected walking speed.
• This technology has potential applications for individuals with impaired mobility, including older adults.
• Gait adaptations and metabolic costs associated with speed optimization are highly individual.