Wearable soft sensing suit for human gait measurement

Wearable robots based on soft materials will augment mobility and performance of the host without restricting natural kinematics. These wearable robots will need wearable soft sensors to monitor the movement of the wearer and robot outside the lab. Until now wearable soft sensors have not demonstrated significant mechanical robustness nor been systematically characterized for human motion studies of walking and running. Here, we present the design and systematic characterization of a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles. We used hyper-elastic strain sensors based on microchannels of liquid metal embedded within elastomer, but refined their design with the use of discretized stiffness gradients to improve mechanical durability. Characterization of individual sensors shows they are compliant (stretch up to 396% at failure and provide joint torque resistances < 0.17%), sensitive (gauge factors > 2.2), and stable (electromechanical specifications changed < 2% over 1500 cycles). We also evaluated the accuracy and variability of the soft sensing suit by comparing it to joint angle data obtained through optical motion capture. The sensing suit had root mean square (RMS) errors of less than 5 degrees for walking speeds and reached a maximum RMS error of 15 degrees for running speeds. The variability of the sensing suit was equivalent to that of the optical motion capture at all speeds. We anticipate that wearable soft sensing will also have applications beyond wearable robotics, such as in medical diagnostics and in human-computer interaction.