Motion sensing has played an important role in the study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical or inertial based motion capture systems, have relatively high accuracy in detecting body motions, they still have inherent limitations with regards to mobility and wearability. In this paper, we present a soft motion sensing suit for measuring lower extremity joint motion. The sensing suit prototype includes a pair of elastic tights and three hyperelastic strain sensors. The strain sensors are made of silicone elastomer with embedded microchannels filled with conductive liquid. To form a sensing suit, these sensors are attached at the hip, knee, and ankle areas to measure the joint angles in the sagittal plane. The prototype motion sensing suit has significant potential as an autonomous system that can be worn by individuals during many activities outside the laboratory, from running to rock climbing. In this study we characterize the hyperelastic sensors in isolation to determine their mechanical and electrical responses to strain, and then demonstrate the sensing capability of the integrated suit in comparison with a ground truth optical motion capture system. Using simple calibration techniques, we can accurately track joint angles and gait phase. Our efforts result in a calculated trade off: with a maximum error less than 8%, the sensing suit does not track joints as accurately as optical motion capture, but its wearability means that it is not constrained to use only in a lab.

In this paper we present a soft lower-extremity robotic exosuit intended to augment normal muscle function in healthy individuals. Compared to previous exoskeletons, the device is ultra-lightweight, resulting in low mechanical impedance and inertia. The exosuit has custom McKibben style pneumatic actuators that can assist the hip, knee and ankle. The actuators attach to the exosuit through a network of soft, inextensible webbing triangulated to attachment points utilizing a novel approach we call the virtual anchor technique. This approach is designed to transfer forces to locations on the body that can best accept load. Pneumatic actuation was chosen for this initial prototype because the McKibben actuators are soft and can be easily driven by an off-board compressor. The exosuit itself (human interface and actuators) had a mass of 3500 g and with peripherals (excluding air supply) is 7144 g. In order to examine the exosuit's performance, a pilot study with one subject was performed which investigated the effect of the ankle plantar-flexion timing on the wearer's hip, knee and ankle joint kinematics and metabolic power when walking. Wearing the suit in a passive unpowered mode had little effect on hip, knee and ankle joint kinematics as compared to baseline walking when not wearing the suit. Engaging the actuators at the ankles at 30% of the gait cycle for 250 ms altered joint kinematics the least and also minimized metabolic power. The subject's average metabolic power was 386.7 W, almost identical to the average power when wearing no suit (381.8 W), and substantially less than walking with the unpowered suit (430.6 W). This preliminary work demonstrates that the exosuit can comfortably transmit joint torques to the user while not restricting mobility and that with further optimization, has the potential to reduce the wearer's metabolic cost during walking.

Lower limb dynamic cadaveric gait simulators are useful to investigate the biomechanics of the foot and ankle, but many systems have several common limitations, which include simplified tendon forces, nonphysiologic tibial kinematics, greatly reduced velocities, scaled body weight (BW), and, most importantly, trial-and-error vertical ground reaction force (vGRF) control. This paper presents the design, development, and validation of the robotic gait simulator (RGS), which addresses these limitations. A 6-degrees-of-freedom (6-DOF) parallel robot was utilized as part of the RGS to recreate the relative tibia to ground motion. A custom-designed nine-axis proportional-integral-derivative (PID) force-control tendon actuation system provided force to the extrinsic tendons of the cadaveric lower limb. A fuzzy logic vGRF controller was developed, which altered tendon forces in real time and iteratively adjusted the robotic trajectory in order to track a target vGRF. The RGS was able to accurately reproduce 6-DOF tibial kinematics, tendon forces, and vGRF with a cadaveric lower limb. The fuzzy logic vGRF controller was able to track the target in vivo vGRF with an average root-mean-square error of only 5.6% BW during a biomechanically realistic 3/4 BW, 2.7-s stance phase simulation.