Introduction: Powered orthoses have the potential to benefit pathologic or geriatric populations by increasing the quality of theirmobility, reducing metabolic cost, and helping restore functional status. However, user interface design of powered orthoses is rarely considered, and may limit their clinical impact. The aim of this study was to design and evaluate a novel user interface for a powered hip orthosis. We hypothesized that our interface design would reduce metabolic costs, reduce skin irritation, increase user comfort, and reduce pain during ambulation when compared with an off-the-shelf (OTS) interface. Methods: A novel, custom-fit torso user interface was designed to have extended trimlines and load the iliac crests. This allows for improved purchase over anatomic structures and potentially improves weight distribution of the powered hip orthosis. The design was compared with an OTS user interface. Subjects ambulated in three conditions: without a powered orthosis, with an OTS interface, and with the novel interface. Five healthy subjects (23.6 +/- 2.2 years) with no neuromuscular limitations ambulated on a treadmill for 6 minutes at 0.8 m/s while measuring metabolic cost for three levels of torque assistance. Subjects repeated this procedure for all three conditions. After ambulating in each interface, skin was inspected at t = 0, 10, and 30 minutes. They completed the OPUS (Orthotics and Prosthetics User's Survey) Satisfaction with Device survey and reported pain on a 1-to-10 scale (0 = no pain). Results: The novel interface reduced metabolic cost for all conditions when compared with OTS componentry. Maximal difference was at the 13% torque assistance level where the difference was 0.18 W/kg +/- 0.11 (SEM) (9.48%). The novel design generally reduced pain scale and skin irritation. The average pain rating decreased froma 3/10 +/- 1.17 (SEM) in the OTS condition to 2/ 10 +/- 0.84 (SEM). The novel design generally increased OPUS Satisfaction with Device score when compared with the OTS condition; the OPUS score increased from an average of 32/45 +/- 2.56 (SEM) for the OTS condition to 36/45 +/- 2.1 (SEM). Discussion: The novel design tended to reduce metabolic cost for all tested powered orthotic conditions. This may be explained by the novel design's more proximal trimlines and increased loading of anatomic structures. These features may be due to maximized biomechanical leverage and minimized compensatory motions during ambulation. Conclusions: The user interface may impact metabolic cost of walking and user comfort. Moving forward, it should be considered an essential element of powered orthosis design. It is critical to optimize the user interface in future powered hip orthotic designs due to minimal surface area available for weight-bearing and reduced number of actuated joints. Therefore, those interested in optimizing powered hip orthotic user interface designs should focus on loading anatomic structures, including the shoulders and iliac crests, and on supporting the curvature of the lumbar spine.

In order for the lower limb exoskeletons to realize their considerable potential, a greater understanding of optimal assistive performance is required. While others have shown positive results, the fundamental question of how the exoskeleton interacts with the human remains unknown. Understanding the optimal assistance magnitude is not simply relevant for control, it is a critical knowledge for exoskeleton designers. An accurate understanding of assistance levels will enable the designers to minimize exoskeleton mass and improve the performance by avoiding excessive actuators and drivetrains. We explored the relationship between the assistance magnitude and the energetic cost benefits by using a series elastic actuator driven powered hip exoskeleton. The exoskeleton controller mimics a human biological hip moment to provide the assistance during the gait cycle. Ten able-bodied subjects walked using the exoskeleton with different magnitudes of assistance in both hip flexion and extension. Generally, the resulting metabolic cost across different assistance conditions showed a U-shape trend which was consistent across all subjects (p < 0.01). The interpreted optimal assistance point through the quadratic fit resulted in a 6% metabolic cost reduction with respect to the no-assistance condition. The study validated that simply increasing the assistance level did not yield higher energetic return.

Robotic exoskeletons have the capability to improve community ambulation in aging individuals. These exoskeleton controllers utilize different environmental information such as walking speeds and slope inclines to provide corresponding assistance. Several numerical approaches for estimating this environmental information have been implemented; however, they tend to be limited during dynamic changes. A possible solution is a machine learning model utilizing the user's electromyography (EMG) signals along with mechanical sensor data. We developed a neural network-based walking speed and slope estimator for a powered hip exoskeleton and explored the EMG signal contributions in both static and dynamic settings while wearing the device. We also analyzed the performance of different EMG electrode placements. The resulting machine learning model achieved error rates below 0.08 m/s RMSE and 1.3 RMSE. Our study findings from four able-bodied and two elderly subjects indicate that EMG can improve the performance by reducing the error rate by 14.8% compared to the model using only mechanical sensors. Additionally, results show that using EMG electrode configuration within the exoskeleton interface region is sufficient for the EMG model performance.

Recent technological advancements have expanded the field of human augmentation. Specifically, lower limb exoskeletons have benefited many by providing assistance to increase mobility. The proposed study aims to develop a novel bilateral hip exoskeleton that provides mechanical power assistance in both hip flexion and extension during walking. Each actuation unit employs series elastic actuator for a high fidelity closed loop torque control utilizing a ball screw transmission incorporated with a fiberglass leaf spring. The control architecture was divided into three tiers and each tier implemented different control algorithms. The device was experimentally validated with both benchtop and human testing. Benchtop testing was done to tune required control parameters in the low-level controller and to validate the torque response. We tested five able-bodied subjects walking with our device. We analyzed their kinematic and kinetic data with different levels of mechanical power assistance during walking. Our benchtop testing results showed that the low-level PID gains were tuned to achieve desired bandwidth and torque tracking. Human testing results demonstrated that the high-level controller provided an accurate information for assistance onset timing that the hip exoskeleton was able to assist the user effectively.

The purpose of this study was to explore the effectiveness of a neural controller for a single-joint bilateral hip exoskeleton. The device provides mechanical torque in the sagittal plane and uses series elastic actuators for feedback control. The system consists of three control layers: (1) a high-level controller that estimates the current gait phase, (2) a mid-level controller that converts the electromyography (EMG) signals to desired exoskeleton torques, and (3) a low-level controller that ensures the output torque matches the commanded torque. To evaluate the effectiveness of the proportional EMG controller, one able-body subject walked with the exoskeleton under 3 assistance conditions: (1) a baseline proportional gain condition (× G), (2) a double proportional gain condition (× 2G) for faster scaling, and (3) an on/off set value torque assistance (SV). The third condition provides the same net mechanical power as the baseline (× G) condition to compare whether proportional scaling of the hip torque was significant. The subject’s hip-joint kinematics, metabolic rate, and muscle activities were collected as outcome measurements. In summary, the EMG controller could generate seamless torque to the user with a response time of 80 ms. The × 2G condition resulted in a 23.3% EMG activity reduction while SV condition reduced the metabolic rate by 8.1%. Interestingly, the largest EMG reduction condition (× 2G) did not result in largest metabolic reduction (SV). Our preliminary findings suggest that the proportional scaling of the hip torque may not be the most important parameter to minimize metabolic cost.

Here we show that novel, energy-recycling stairs reduce the amount of work required for humans to both ascend and descend stairs. Our low-power, interactive, and modular steps can be placed on existing staircases, storing energy during stair descent and returning that energy to the user during stair ascent. Energy is recycled through event-triggered latching and unlatching of passive springs without the use of powered actuators. When ascending the energy-recycling stairs, naive users generated 17.4 ± 6.9% less positive work with their leading legs compared to conventional stairs, with the knee joint positive work reduced by 37.7 ± 10.5%. Users also generated 21.9 ± 17.8% less negative work with their trailing legs during stair descent, with ankle joint negative work reduced by 26.0 ± 15.9%. Our low-power energy-recycling stairs have the potential to assist people with mobility impairments during stair negotiation on existing staircases.