Project description:Lower extremity powered exoskeletons (LEPE) are an emerging technology that assists people with lower-limb paralysis. LEPE for people with complete spinal cord injury walk at very slow speeds, below 0.5m/s. For the able-bodied population, very slow walking uses different neuromuscular, locomotor, postural, and dynamic balance control. Speed dependent kinetic and kinematic regression equations in the literature could be used for very slow walking LEPE trajectory scaling; however, kinematic and kinetic information at walking speeds below 0.5 m/s is lacking. Scaling LEPE trajectories using current reference equations may be inaccurate because these equations were produced from faster than real-world LEPE walking speeds. An improved understanding of how able-bodied people biomechanically adapt to very slow walking will provide LEPE developers with more accurate models to predict and scale LEPE gait trajectories. Full body motion capture data were collected from 30 healthy adults while walking on an instrumented self-paced treadmill, within a CAREN-Extended virtual reality environment. Kinematic and kinetic data were collected for 0.2 m/s-0.8 m/s, and self-selected walking speed. Thirty-three common sagittal kinematic and kinetic gait parameters were identified from motion capture data and inverse dynamics. Gait parameter relationships to walking speed, cadence, and stride length were determined with linear and quadratic (second and third order) regression. For parameters with a non-linear relationship with speed, cadence, or stride-length, linear regressions were used to determine if a consistent inflection occurred for faster and slower walking speeds. Group mean equations were applied to each participant's data to determine the best performing equations for calculating important peak sagittal kinematic and kinetic gait parameters. Quadratic models based on walking speed had the strongest correlations with sagittal kinematic and kinetic gait parameters, with kinetic parameters having the better results. The lack of a consistent inflection point indicated that the kinematic and kinetic gait strategies did not change at very slow gait speeds. This research showed stronger associations with speed and gait parameters then previous studies, and provided more accurate regression equations for gait parameters at very slow walking speeds that can be used for LEPE joint trajectory development.
Project description:Although it is relevant to understand spine and lower body motions in healthy individuals for a variety of applications, such as clinical diagnosis, implant design, and the analysis of treatment outcomes, proper assessment and characterization of normative gait symmetry in healthy individuals remains unclear. The purpose of this study was to investigate the in vivo 3-dimensional (3D) spine and lower body gait symmetry kinematics during treadmill walking in healthy individuals. Sixty healthy young adults (30 males and 30 females) were evaluated during normal and fast treadmill walking using a motion capture system approach. Statistical parametric mapping and the normalized symmetry index approaches were used to determine spine, pelvis, and lower body asymmetries during treadmill walking. The spine and pelvis angular motions associated with the left and right lower limb motions, as well as the left and right lower extremity joint angles were compared for normal and fast treadmill walking. The lower lumbar left-right rotation (5.74±0.04°) and hip internal rotation (5.33±0.18°) presented the largest degrees of asymmetry during normal treadmill. Upper lumbar left-right lateral flexion (1.48±0.14°) and knee flexion (2.98±0.13°) indicated the largest asymmetries and during fast treadmill walking. Few asymmetry patterns were similar between normal and fast treadmill walking, whereas others appeared either only during normal or fast treadmill walking in this cohort of participants. These findings could provide insights into better understanding gait asymmetry in healthy individuals, and use them as reference indicators in diagnosing and evaluating abnormal gait function.
Project description:Introduction: This study aimed to quantify the relationship between prosthetic users' emotional response to prosthesis aesthetics and specific product properties. Methods: Words representing prosthesis users' emotional response (Kansei) to different aesthetic designs of prostheses were identified via interviews and mood boards. A group of experts consolidated the words into thematic groups, each represented by a single, high-level 'Kansei' word. 53 lower limb prosthesis users completed a questionnaire, rating their perception of 13 aesthetic designs using the 'Kansei' words. Quantification Theory Type 1 was applied to explore the relationship between words and product properties. Sub-analyses assessed for differences based on sex, age and level of extroversion. Results: 5 high-level Kansei words were identified ('Natural', 'Technological', 'Cool', 'Unique' and 'Functional'). The Kansei word 'Natural' had a strong association with realistic looking prostheses while the words 'Technological', 'Cool' and 'Unique' were strongly associated with expressive designs which incorporate hard, colourful covers. The word 'Functional' was not a reliable predictor of product properties. No major differences were observed within sub-grouped categories. Conclusion: Kansei words identified in this study can be used to help guide clients in their aesthetic design choices and to assist designers in achieving the desired response from their products.
Project description:BackgroundWomen Veterans with amputation are a group with unique needs whose numbers have grown over the last 5 years, accounting for nearly 3% of all Veterans with amputation in 2019. Although identified as a national priority by the Veterans Health Administration, the needs of this population have remained largely underrepresented in amputation research.ObjectiveTo describe the experiences of women Veterans with lower extremity amputation (LEA) related to prosthetic care provision and devices.DesignNational qualitative study using semi-structured individual interviews.ParticipantsThirty women Veterans with LEA who had been prescribed a prosthesis at least 12 months prior.ApproachInductive content analysis.Key resultsFour key themes emerged: (1) a sense of "feeling invisible" and lacking a connection with other women Veterans with amputation; (2) the desire for prosthetic devices that meet their biological and social needs; (3) the need for individualized assessment and a prosthetic limb prescription process that is tailored to women Veterans; the current process was often perceived as biased and either dismissive of women's concerns or failing to adequately solicit them; and (4) the desire for prosthetists who listen to and understand women's needs.ConclusionsWomen Veterans with LEA articulated themes reminiscent of those previously reported by male Veterans with LEA, such as the importance of prostheses and the central role of the provider-patient relationship. However, they also articulated unique needs that could translate into specific strategies to improve prosthetic care, such as integrating formal opportunities for social support and peer interaction for women Veterans with LEA, advocating for administrative changes and research efforts to expand available prosthetic component options, and ensuring that clinical interactions are gender-sensitive and free of bias.
Project description:The objective of this research was to assess the performance of an embedded sensing system designed to measure the distance between a prosthetic socket wall and residual limb. Low-profile inductive sensors were laminated into prosthetic sockets and flexible ferromagnetic targets were created from elastomeric liners with embedded iron particles for four participants with transtibial amputation. Using insights from sensor performance testing, a novel calibration procedure was developed to quickly and accurately calibrate the multiple embedded sensors. The sensing system was evaluated through laboratory tests in which participants wore sock combinations with three distinct thicknesses and conducted a series of activities including standing, walking, and sitting. When a thicker sock was worn, the limb typically moved further away from the socket and peak-to-peak displacements decreased. However, sensors did not measure equivalent distances or displacements for a given sock combination, which provided information regarding the fit of the socket and how a sock change intervention influenced socket fit. Monitoring of limb⁻socket displacements may serve as a valuable tool for researchers and clinicians to quantitatively assess socket fit.
Project description:This study introduces a deep learning framework for estimating lower-limb joint kinematics using inertial measurement units (IMUs). While deep learning methods avoid sensor drift, extensive calibration, and complex setup procedures, they require substantial data. To meet this demand, we leveraged an open-source dataset to develop and evaluate three training approaches. The first involved training a model exclusively on data from a single user, resulting in high accuracy for that individual only. The second approach trained a model on data from multiple users to generalize across individuals; however, demonstrated lower accuracy due to variations in gait patterns across users. The third approach added transfer learning to the second, improving estimation accuracy for new users through fine-tuning with a small portion of their data. This model overcame the limitations of the previous methods' dependency on extensive data collection, and achieved comparable performance to inverse kinematics, making it an effective solution for diverse populations. Additionally, our analysis on IMU combinations suggests that IMUs placed on the femur and calcaneus are the best for most cases. This framework not only reduces the need for extensive data collection but also enhances personalized gait analysis, enabling more efficient and accessible applications in both clinical assessments and real-world environments for broader use.
Project description:We test whether locomotor posture is associated with body mass and lower limb length in humans and explore how body size and posture affect net joint moments during walking. We acquired gait data for 24 females and 25 males using a three-dimensional motion capture system and pressure-measuring insoles. We employed the general linear model and commonality analysis to assess the independent effect of body mass and lower limb length on flexion angles at the hip, knee, and ankle while controlling for sex and velocity. In addition, we used inverse dynamics to model the effect of size and posture on net joint moments. At early stance, body mass has a negative effect on knee flexion (p < 0.01), whereas lower limb length has a negative effect on hip flexion (p < 0.05). Body mass uniquely explains 15.8% of the variance in knee flexion, whereas lower limb length uniquely explains 5.4% of the variance in hip flexion. Both of the detected relationships between body size and posture are consistent with the moment moderating postural adjustments predicted by our model. At late stance, no significant relationship between body size and posture was detected. Humans of greater body size reduce the flexion of the hip and knee at early stance, which results in the moderation of net moments at these joints.
Project description:Lower-limb intersegmental coordination is a complex component of human walking. Aging may result in impairments of motor control and coordination contributing to the decline in mobility inducing loss of autonomy. Investigating intersegmental coordination could therefore provide insights into age-related changes in neuromuscular control of gait. However, it is unknown whether the age-related declines in gait performance relates to intersegmental coordination. The aim of this study was to evaluate the impact of aging on the coordination of lower limb kinematics and kinetics during walking at a conformable speed. We then assessed the body kinematics and kinetics from gait analyses of 84 volunteers from 25 to 85 years old when walking was performed at their self-selected speeds. Principal Component Analysis (PCA) was used to assess lower-limb intersegmental coordination and to evaluate the planar covariation of the Shank-Thigh and Foot-Shank segments. Ankle and knee stiffness were also estimated. Age-related effects on planar covariation parameters was evaluated using multiple linear regressions (i.e., without a priori age group determination) adjusted to normalized self-selected gait velocity. Colinearity between parameters was assessed using a variation inflation factor (VIF) and those with a VIF < 5 were entered in the analysis. Normalized gait velocity significantly decreased with aging (r = -0.24; P = 0.028). Planar covariation of inter-segmental coordination was consistent across age (99.3 ± 0.24% of explained variance of PCA). Significant relationships were found between age and intersegmental foot-shank coordination, range of motion of the ankle, maximal power of the knee, and the ankle. Lower-limb coordination was modified with age, particularly the coordination between foot, and shank. Such modifications may influence the ankle motion and thus, ankle power. This observation may explain the decrease in the ankle plantar flexor strength mainly reported in the literature. We therefore hypothesize that this modification of coordination constitutes a neuromuscular adaptation of gait control accompanying a loss of ankle strength and amplitude by increasing the knee power in order to maintain gait efficiency. We propose that foot-shank coordination might represent a valid outcome measure to estimate the efficacy of rehabilitative strategies and to evaluate their efficiency in restoring lower-limb synergies during walking.
Project description:A proper movement categorization reduces the complexity of understanding or reproducing human movements in fields such as physiology, rehabilitation, and robotics, through partitioning a wide variety of human movements into representative sub-motion groups. However, how to establish a categorization (especially a quantitative categorization) for various human lower limb movements is rarely investigated in literature and remains challenging due to the diversity and complexity of the lower limb movements (diverse gait modes and interaction styles with the environment). Here we present a quantitative categorization for the various lower limb movements. To this end, a similarity measure between movements was first built based on limb kinematic synergies that provide a unified and physiologically meaningful framework for evaluating the similarities among different types of movements. Then, a categorization was established via hierarchical cluster analysis for thirty-four lower limb movements, including walking, running, hopping, sitting-down-standing-up, and turning in different environmental conditions. According to the movement similarities, the various movements could be divided into three distinct clusters (cluster 1: walking, running, and sitting-down-standing-up; cluster 2: hopping; cluster 3: turning). In each cluster, cluster-specific movement synergies were required. Besides the uniqueness of each cluster, similarities were also found among part of the synergies employed by these different clusters, perhaps related to common behavioral goals in these clusters. The mix of synergies shared across the clusters and synergies for specific clusters thus suggests the coexistence of the conservation and augmentation of the kinematic synergies underlying the construction of the diverse and complex motor behaviors. Overall, the categorization presented here yields a quantitative and hierarchical representation of the various lower limb movements, which can serve as a basis for the understanding of the formation mechanisms of human locomotion and motor function assessment and reproduction in related fields.
Project description:Precise form-fitting of prosthetic sockets is important for the comfort and well-being of persons with limb amputations. Capabilities for continuous monitoring of pressure and temperature at the skin-prosthesis interface can be valuable in the fitting process and in monitoring for the development of dangerous regions of increased pressure and temperature as limb volume changes during daily activities. Conventional pressure transducers and temperature sensors cannot provide comfortable, irritation-free measurements because of their relatively rigid construction and requirements for wired interfaces to external data acquisition hardware. Here, we introduce a millimeter-scale pressure sensor that adopts a soft, three-dimensional design that integrates into a thin, flexible battery-free, wireless platform with a built-in temperature sensor to allow operation in a noninvasive, imperceptible fashion directly at the skin-prosthesis interface. The sensor system mounts on the surface of the skin of the residual limb, in single or multiple locations of interest. A wireless reader module attached to the outside of the prosthetic socket wirelessly provides power to the sensor and wirelessly receives data from it, for continuous long-range transmission to a standard consumer electronic device such as a smartphone or tablet computer. Characterization of both the sensor and the system, together with theoretical analysis of the key responses, illustrates linear, accurate responses and the ability to address the entire range of relevant pressures and to capture skin temperature accurately, both in a continuous mode. Clinical application in two prosthesis users demonstrates the functionality and feasibility of this soft, wireless system.