Yigit Menguc, Ph.D.
Yigit Menguc, Ph.D.
Harvard Microrobotics Laboratory
School of Engineering & Applied Sciences
Dr. Yigit Menguc works at the interface of mechanical engineering and robotics, and creates soft mechanisms and devices inspired by nature. He received his B.S. (2006) in Mechanical Engineering at Rice University in Houston, Texas and his Ph.D. (2011) in Mechanical Engineering at Carnegie Mellon University in Pittsburgh, Pennsylvania where he created gecko-inspired, self-cleaning adhesives for wall-climbing robots and robotic manipulators. He is currently a postdoctoral fellow making sensors for soft wearable robots at Harvard University's School of Engineering and Applied Sciences and the Wyss Institute for Biologically Inspired Engineering.
Wearable Soft Sensing Suit for Human Gait Measurement
A fundamental challenge for next generation soft wearable robots is monitoring the movement of the wearer and robot without the use of rigid materials. Here we provide design and fabrication guidelines for a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles with hyper-elastic strain sensors composed of liquid metal embedded elastomer. Mechanical design incorporates stiff-to-soft graded modulus and hook-and-loop material that robustly interfaces with the soft suit. Characterization of individual sensors shows they are compliant (joint torque resistances < 0.17%), sensitive (gauge factors > 2.2), electrically and mechanically stable for 1500 cycles (< 2% change), and extensible (stretch to 396% at failure in an extreme case). We evaluate the accuracy and repeatability of the soft sensing suit by comparing the joint angle data captured with it to that obtained from optical motion capture. For three participants running, we found RMS errors of 6°, 15°, and 10° for the hip, knee, and ankle, respectively. While walking, RMS errors were less than 5°. These sensors have obvious applications in wearable robotics, but also hold promise for physiological and biomechanical studies of human gait.