Search for: All records

For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. Despite the high accuracy of measurement, marker-based systems are largely limited to laboratory environments, making it nearly impossible to collect the desired gait data in real-world daily-living scenarios. To address this problem, the authors propose a novel exoskeleton-based gait data collection system, which provides the capability of conducting independent measurement of lower limb movement without the need for stationary instrumentation. The basis of the system is a lightweight exoskeleton with articulated knee and ankle joints. To minimize the interference to a wearer’s natural lower-limb movement, a unique two-degrees-of-freedom joint design is incorporated, integrating a primary degree of freedom for joint motion measurement with a passive degree of freedom to allow natural joint movement and improve the comfort of use. In addition to the joint-embedded goniometers, the exoskeleton also features multiple positions for the mounting of inertia measurement units (IMUs) as well as foot-plate-embedded force sensing resistors to measure the foot plantar pressure. All sensor signals are routed to a microcontroller for data logging and storage. To validate the exoskeleton-provided joint angle measurement, a comparison study on three healthy participants was conducted, which involves locomotion experiments in various modes, including overground walking, treadmill walking, and sit-to-stand and stand-to-sit transitions. Joint angle trajectories measured with an eight-camera motion capture system served as the benchmark for comparison. Experimental results indicate that the exoskeleton-measured joint angle trajectories closely match those obtained through the optical motion capture system in all modes of locomotion (correlation coefficients of 0.97 and 0.96 for knee and ankle measurements, respectively), clearly demonstrating the accuracy and reliability of the proposed gait measurement system. 

This paper presents the design and preliminary testing of an instrumented exoskeleton system, which is targeted at collecting gait data of the human locomotion to support the controller development of lower-limb wearable robots. This compact and lightweight device features a unique two-degree-of-freedom joint to minimize the interference to the user movement and a simple yet effective adjustment mechanism to fit subjects at different heights. For the gait measurement, the device incorporates embedded joint goniometers to obtain the knee and ankle positions, and inertial measurement units to obtain three-dimensional kinematic information. Force-sensing resistors are also incorporated into the shoe insole for plantar pressure measurement. Sensor signals are routed to an onboard microcontroller system for data storage and transfer, and the system is fully self-contained with onboard battery to facilitate data collection in various environments. A prototype of the exoskeleton was fabricated, and preliminary testing was conducted on two healthy subjects in various postures and modes of movement (walking, sitting, standing, stair climbing, etc.). The evaluation of a temporal event detection test showed no more than 5.5% mean variation in the measure of step counts by the sensory system and video annotation. These results indicate that the exoskeleton can provide an accurate measurement of gait information, using measurements taken from external video recordings as the benchmark in this preliminary validation study.