Inertial measurement units (IMUs) are small wearable sensors that have tremendous potential to be applied to clinical gait analysis. They allow objective evaluation of gait and movement disorders outside the clinic and research laboratory, and permit evaluation on large numbers of steps. However, repeatability and validity data of these systems are sparse for gait metrics. The purpose of this study was to determine the validity and between-day repeatability of spatiotemporal metrics (gait speed, stance percent, swing percent, gait cycle time, stride length, cadence, and step duration) as measured with the APDM Opal IMUs and Mobility Lab system. We collected data on 39 healthy subjects. Subjects were tested over two days while walking on a standard treadmill, split-belt treadmill, or overground, with IMUs placed in two locations: both feet and both ankles. The spatiotemporal measurements taken with the IMU system were validated against data from an instrumented treadmill, or using standard clinical procedures. Repeatability and minimally detectable change (MDC) of the system was calculated between days. IMUs displayed high to moderate validity when measuring most of the gait metrics tested. Additionally, these measurements appear to be repeatable when used on the treadmill and overground. The foot configuration of the IMUs appeared to better measure gait parameters; however, both the foot and ankle configurations demonstrated good repeatability. In conclusion, the IMU system in this study appears to be both accurate and repeatable for measuring spatiotemporal gait parameters in healthy young adults.

This study was registered at ClinicalTrials.gov, identifier NCT02093520.

Functional strength training is becoming increasingly popular when rehabilitating individuals with neurological injury such as stroke or cerebral palsy. Typically, resistance during walking is provided using cable robots or weights that are secured to the distal shank of the subject. However, there exists no device that is wearable and capable of providing resistance across the joint, allowing over ground gait training. In this study, we created a lightweight and wearable device using eddy current braking to provide resistance to the knee. We then validated the device by having subjects wear it during a walking task through varying resistance levels. Electromyography and kinematics were collected to assess the biomechanical effects of the device on the wearer. We found that eddy current braking provided resistance levels suitable for functional strength training of leg muscles in a package that is both lightweight and wearable. Applying resistive forces at the knee joint during gait resulted in significant increases in muscle activation of many of the muscles tested. A brief period of training also resulted in significant aftereffects once the resistance was removed. These results support the feasibility of the device for functional strength training during gait. Future research is warranted to test the clinical potential of the device in an injured population.

Physical therapy is an important component of gait recovery for individuals with locomotor dysfunction. There is a growing body of evidence that suggests that incorporating a motor learning task through visual feedback of movement trajectory is a useful approach to facilitate therapeutic outcomes. Visual feedback is typically provided by recording the subject’s limb movement patterns using a three-dimensional motion capture system and displaying it in real-time using customized software. However, this approach can seldom be used in the clinic because of the technical expertise required to operate this device and the cost involved in procuring a three-dimensional motion capture system. In this paper, we describe a low cost two-dimensional real-time motion tracking approach using a simple webcam and an image processing algorithm in LabVIEW Vision Assistant. We also evaluated the accuracy of this approach using a high precision robotic device (Lokomat) across various walking speeds. Further, the reliability and feasibility of real-time motion-tracking were evaluated in healthy human participants. The results indicated that the measurements from the webcam tracking approach were reliable and accurate. Experiments on human subjects also showed that participants could utilize the real-time kinematic feedback generated from this device to successfully perform a motor learning task while walking on a treadmill. These findings suggest that the webcam motion tracking approach is a feasible low cost solution to perform real-time movement analysis and training.

Three-dimensional (3-D) motion capture systems are commonly used for gait analysis because they provide reliable and accurate measurements. However, the downside of this approach is that it is expensive and requires technical expertise; thus making it less feasible in the clinic. To address this limitation, we recently developed and validated (using a high-precision walking robot) a low-cost, two-dimensional (2-D) real-time motion tracking approach using a simple webcam and LabVIEW Vision Assistant. The purpose of this study was to establish the repeatability and minimal detectable change values of hip and knee sagittal plane gait kinematics recorded using this system. Twenty-one healthy subjects underwent two kinematic assessments while walking on a treadmill at a range of gait velocities. Intraclass correlation coefficients (ICC) and minimal detectable change (MDC) values were calculated for commonly used hip and knee kinematic parameters to demonstrate the reliability of the system. Additionally, Bland-Altman plots were generated to examine the agreement between the measurements recorded on two different days. The system demonstrated good to excellent reliability (ICC > 0.75) for all the gait parameters tested on this study. The MDC values were typically low (< 5°) for most of the parameters. The Bland-Altman plots indicated that there was no systematic error or bias in kinematic measurements and showed good agreement between measurements obtained on two different days. These results indicate that kinematic gait assessments using webcam technology can be reliably used for clinical and research purposes.