IMU-derived kinematics detect gait differences with age or knee osteoarthritis but differ from marker-derived inverse kinematics

Common in-lab, marker-based gait analyses may not represent daily, real-world gait. Real-world gait analyses may be feasible using inertial measurement units (IMUs), especially with recent advancements in open-source methods (e.g., OpenSense). Before using OpenSense to study real-world gait, we must determine whether these methods: (1) estimate joint kinematics similarly to traditional marker-based motion capture (MoCap) and (2) differentiate groups with clinically different gait mechanics. Healthy young and older adults and older adults with knee osteoarthritis completed this study. We captured MoCap and IMU data during overground walking at self-selected and faster speeds. MoCap and IMU kinematics were computed with appropriate OpenSim workflows. We tested whether sagittal kinematics differed between MoCap- and IMU-derived data, whether tools detected between-group differences similarly, and whether kinematics differed between tools by speed. MoCap data showed more flexion than IMU data (hip: 0-47 and 65-100% stride, knee: 0-38 and 58-91% stride, ankle: 18-100% stride). Group kinematics differed at the hip (young extension > knee osteoarthritis at 30-47% stride) and ankle (young plantar flexion > older healthy at 62-65% stride). Group-by-tool interactions occurred at the hip (61-63% stride). Significant tool-by-speed interactions were found, with hip and knee flexion increasing more for MoCap than IMU data with speed (hip: 12-15% stride, knee: 60-63% stride). While MoCap- and IMU-derived kinematics differed, our results suggested that the tools similarly detected clinically meaningful differences in gait. Results of the current study suggest that IMU-derived kinematics with OpenSense may enable the valid and reliable evaluation of gait in real-world, unobserved settings.

Prediction of Lower Extremity Multi-Joint Angles during Overground Walking by Using a Single IMU with a Low Frequency Based on an LSTM Recurrent Neural Network

The joint angle during gait is an important indicator, such as injury risk index, rehabilitation status evaluation, etc. To analyze gait, inertial measurement unit (IMU) sensors have been used in studies and continuously developed; however, they are difficult to utilize in daily life because of the inconvenience of having to attach multiple sensors together and the difficulty of long-term use due to the battery consumption required for high data sampling rates. To overcome these problems, this study propose a multi-joint angle estimation method based on a long short-term memory (LSTM) recurrent neural network with a single low-frequency (23 Hz) IMU sensor. IMU sensor data attached to the lateral shank were measured during overground walking at a self-selected speed for 30 healthy young persons. The results show a comparatively good accuracy level, similar to previous studies using high-frequency IMU sensors. Compared to the reference results obtained from the motion capture system, the estimated angle coefficient of determination (R2) is greater than 0.74, and the root mean square error and normalized root mean square error (NRMSE) are less than 7° and 9.87%, respectively. The knee joint showed the best estimation performance in terms of the NRMSE and R2 among the hip, knee, and ankle joints.

Overground Walking in a Fully Immersive Virtual Reality: A Comprehensive Study on the Effects on Full-Body Walking Biomechanics

Virtual reality (VR) is an emerging technology offering tremendous opportunities to aid gait rehabilitation. To this date, real walking with users immersed in virtual environments with head-mounted displays (HMDs) is either possible with treadmills or room-scale (overground) VR setups. Especially for the latter, there is a growing interest in applications for interactive gait training as they could allow for more self-paced and natural walking. This study investigated if walking in an overground VR environment has relevant effects on 3D gait biomechanics. A convenience sample of 21 healthy individuals underwent standard 3D gait analysis during four randomly assigned walking conditions: the real laboratory (RLab), a virtual laboratory resembling the real world (VRLab), a small version of the VRlab (VRLab−), and a version which is twice as long as the VRlab (VRLab+). To immerse the participants in the virtual environment we used a VR-HMD, which was operated wireless and calibrated in a way that the virtual labs would match the real-world. Walking speed and a single measure of gait kinematic variability (GaitSD) served as primary outcomes next to standard spatio-temporal parameters, their coefficients of variant (CV%), kinematics, and kinetics. Briefly described, participants demonstrated a slower walking pattern (−0.09 ± 0.06 m/s) and small accompanying kinematic and kinetic changes. Participants also showed a markedly increased gait variability in lower extremity gait kinematics and spatio-temporal parameters. No differences were found between walking in VRLab+ vs. VRLab−. Most of the kinematic and kinetic differences were too small to be regarded as relevant, but increased kinematic variability (+57%) along with increased percent double support time (+4%), and increased step width variability (+38%) indicate gait adaptions toward a more conservative or cautious gait due to instability induced by the VR environment. We suggest considering these effects in the design of VR-based overground training devices. Our study lays the foundation for upcoming developments in the field of VR-assisted gait rehabilitation as it describes how VR in overground walking scenarios impacts our gait pattern. This information is of high relevance when one wants to develop purposeful rehabilitation tools.

Association of Walking Energetics With Amyloid Status: Findings From the Baltimore Longitudinal Study of Aging

Higher energetic costs for mobility are associated with slow and declining gait speed. Slow gait is linked to cognitive decline and Alzheimer’s disease (AD), but the physiological underpinnings are note well-understood. We investigated the cross-sectional association between the energetic cost of walking and amyloid status (+/-) in 174 cognitively unimpaired men and women (52%) aged 78.5±8.6 years. The energetic cost of walking was assessed as the average oxygen consumption (VO2) during 2.5 minutes of customary-paced overground walking. Amyloid status was determined from 11C-Pittsburgh compound B (PiB) positron emission tomography (PET) imaging. Average energetic cost of walking was .169±.0379 ml/kg/m and 30% of the sample was PiB+. In logistic regression adjusted for demographics, APOE-e4, body composition and comorbidities, each 0.01ml/kg/m higher energy cost was associated with 12% increased odds of being PiB+ (OR=1.12; 95% CI:1.01-1.24). Inefficient walking may be a clinically meaningful physiological indicator of emerging AD-related pathology.

Regional difference in prefrontal oxygenation prior to and during overground walking in humans: A wearable multi-channel NIRS study

Using wireless multi-channel near-infrared spectroscopy, regional difference in cortical activity over the prefrontal cortex (PFC) was examined prior to and during overground walking, and in response to changes in speed and cognitive demand. Oxygenated-hemoglobin concentration (Oxy-Hb) as index of cortical activity in ventrolateral PFC (VLPFC), dorsolateral PFC (DLPFC), and frontopolar cortex (FPC) was measured in 14 subjects, while heart rate was measured as estimation of exercise intensity in 6 subjects. The impact of mental imagery on prefrontal Oxy-Hb was also explored. On both sides, Oxy-Hb in VLPFC, DLPFC, and lateral FPC was increased prior to the onset of normal speed walking, whereas Oxy-Hb in medial FPC did not respond prior to walking onset. During the walking, Oxy-Hb further increased in bilateral VLPFC, whereas Oxy-Hb was decreased in DLPFC and lateral and medial FPC. Increasing walking speed did not alter the increase in Oxy-Hb in VLPFC but counteracted the decrease in Oxy-Hb in DLPFC (but not in lateral and medial FPC). Treadmill running evoked a greater Oxy-Hb increase in DLPFC (n = 5 subjects). Furthermore, increasing cognitive demand during walking, by deprivation of visual feedback, counteracted the decrease in Oxy-Hb in DLPFC and lateral and medial FPC, but it did not affect the increase in Oxy-Hb in VLPFC. Taken together, the profound and localized Oxy-Hb increase is a unique response for the VLPFC. The regional heterogeneity of the prefrontal Oxy-Hb responses to natural overground walking was accentuated by increasing walking speed or cognitive demand, suggesting functional distinction within the PFC.

Human-Human Hand Interactions Aid Balance During Walking by Haptic Communication

Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x 3.7 m long) and the other person walked overground by their side. We compare balance performance during partnered vs. solo beam-walking to examine the effects of haptic interaction, and we compare hand interaction mechanics during partnered beam-walking vs. overground walking to examine how the interaction aided balance. While holding the hand of a partner, participants were able to walk further on the beam without falling, reduce lateral sway, and decrease angular momentum in the frontal plane. We measured small hand force magnitudes (mean of 2.2 N laterally and 3.4 N vertically) that created opposing torque components about the beam axis and calculated the interaction torque, the overlapping opposing torque that does not contribute to motion of the beam-walker’s body. We found higher interaction torque magnitudes during partnered beam-walking vs. partnered overground walking, and correlation between interaction torque magnitude and reductions in lateral sway. To gain insight into feasible controller designs to emulate human-human physical interactions for aiding walking balance, we modeled the relationship between each torque component and motion of the beam-walker’s body as a mass-spring-damper system. Our model results show opposite types of mechanical elements (active vs. passive) for the two torque components. Our results demonstrate that hand interactions aid balance during partnered beam-walking by creating opposing torques that primarily serve haptic communication, and our model of the torques suggest control parameters for implementing human-human balance aid in human-robot interactions.

Epidural Spinal Electrogram Provides Direct Spinal Recordings in Awake Human Participants

Little is known about the electrophysiological activity of the spinal cord during voluntary movement control in humans. We present a novel method for recording electrophysiological activity from the human spinal cord using implanted epidural electrodes during naturalistic movements including overground walking. Spinal electrograms (SEGs) were recorded from epidural electrodes implanted as part of a test trial for patients with chronic pain undergoing evaluation for spinal cord stimulation. Externalized ends of the epidural leads were connected to an external amplifier to capture SEGs. Electromyographic and accelerometry data from the upper and lower extremities were collected using wireless sensors and synchronized to the SEG data. Patients were instructed to perform various arm and leg movements while SEG and kinematic data were collected. This study proves the safety and feasibility of performing epidural spinal recordings from human subjects performing movement tasks.