Continuous A-Mode Ultrasound-Based Prediction of Transfemoral Amputee Prosthesis Kinematics Across Different Ambulation Tasks.

OBJECTIVE: Volitional control systems for powered prostheses require the detection of user intent to operate in real life scenarios. Ambulation mode classification has been proposed to address this issue. However, these approaches introduce discrete labels to the otherwise continuous task that is ambulation. An alternative approach is to provide users with direct, voluntary control of the powered prosthesis motion. Surface electromyography (EMG) sensors have been proposed for this task, but poor signal-to-noise ratios and crosstalk from neighboring muscles limit performance. B-mode ultrasound can address some of these issues at the cost of reduced clinical viability due to the substantial increase in size, weight, and cost. Thus, there is an unmet need for a lightweight, portable neural system that can effectively detect the movement intention of individuals with lower-limb amputation. METHODS: In this study, we show that a small and lightweight A-mode ultrasound system can continuously predict prosthesis joint kinematics in seven individuals with transfemoral amputation across different ambulation tasks. Features from the A-mode ultrasound signals were mapped to the user's prosthesis kinematics via an artificial neural network. RESULTS: Predictions on testing ambulation circuit trials resulted in a mean normalized RMSE across different ambulation modes of 8.7 ± 3.1%, 4.6 ± 2.5%, 7.2 ± 1.8%, and 4.6 ± 2.4% for knee position, knee velocity, ankle position, and ankle velocity, respectively. CONCLUSION AND SIGNIFICANCE: This study lays the foundation for future applications of A-mode ultrasound for volitional control of powered prostheses during a variety of daily ambulation tasks.

User-Centered Configuration of Soft Hip Flexion Exosuit Designs to Assist Individuals with Multiple Sclerosis Through Simulated Human-in-the-Loop Optimization.

Soft exosuits hold promise as assistive technology for people with gait deficits owing to a variety of causes. A key aspect of providing useful assistance is to keep the human user at the center of all considerations made in the design, configuration, and prescribed use of an assistive device. This work details a method for informing the configuration of a soft hip flexion exosuit by 1) modeling the user's shape and movements in order to simulate the mechanical interaction of the exosuit and user, 2) incorporating the mechanical effects of the exosuit into a muscle-driven musculoskeletal gait simulation, and 3) using the results of these simulations to define a cost function that is minimized via Bayesian optimization. This process is carried out for models of four different people with multiple sclerosis, and the final optimized configurations for each subject are compared. For all users, the estimated metabolic cost of transport was reduced below baseline, no-device levels. This work represents a step toward more individualized, user-centric modeling of assistive devices, and demonstrates a system for informing the physical configuration of an exosuit on a case-by-case basis using real patient data.

Model Predictions that Consider Individualized Gait Patterns and Patient Mobility Level for the Use of Passive Hip-Flexion Exosuits by Persons with Unilateral Transfemoral Amputation.

The muscular remodeling that occurs during a transfemoral amputation surgery and subsequent long-term use of mechanically-passive prostheses have significant impacts on the mobility and gait pattern of the patient. At toe-off and during the subsequent swing phase, this behavior is characterized by increased hip flexion moment and power provided by the biological limb. In other patient populations (e.g., individuals with multiple sclerosis) passive tension-generating assistive elements have been shown to restore altered hip flexion mechanics at toe off. We hypothesized that an exosuit of the same basic architecture could be well applied to individuals with transfemoral amputation. In this paper, we simulate the effects of such a device for 18 patients of K2 and K3 Medicare functional classification levels. The device consists of two parallel elastic bands. Our approach considers the wrapping and geometric behavior of these elements over the residual limb in full-body patient-specific kinematic simulations of level ground walking. A nonlinear least squares problem was solved via the Levenberg-Marquardt method to find the band properties that best match (in order to offset) the intrinsic power delivery of the muscles during the swing phase. We found higher mobility patients (K3) often require a stiffer device, which leads to a greater error in the kinetic match between the biological limb and exosuit. In contrast, this method appears to be effective for K2 patients, which suggests that a different means of parameter selection or power delivery (e.g., active devices) may be necessary for higher mobility levels.

Relationships between self-perceived and clinical expression of pain and function differ based on the underlying pathology of the human hip.

BACKGROUND: Patient-reported outcomes are commonly used to assess patient symptoms. The effect of specific hip pathology on relationships between perceived and objectively measured symptoms remains unclear. The purpose of this study was to evaluate differences of function and pain in patients with FAIS and DDH, to assess the correlation between perceived and objective function, and to determine the influence of pain on measures of function. METHODS: This prospective cross-sectional study included 35 pre-operative patients (60% female) with femoroacetabular impingement syndrome (FAIS) and 37 pre-operative patients (92% female) with developmental dysplasia of the hip (DDH). Objectively measured function (6-min walk [6MWT], single leg hop [SLHT], Biodex sway [BST], hip abduction strength [HABST], and STAR excursion balance reach [STAR] tests), patient-reported function (UCLA Activity, Hip Outcome Score [HOS], Short Form 12 [SF-12], and Hip Disability and Osteoarthritis Outcome Score [HOOS]), and patient-reported pain (HOOS Pain, visual analogue scale (VAS), and a pain location scale) were collected during a pre-surgical clinic visit. Between-group comparisons of patient scores were performed using Wilcoxon Rank-Sum tests. Within-group correlations were analyzed using Spearman's rank correlation coefficients. Statistical correlation strength was defined as low (r = ± 0.1-0.3), moderate (r = ± 0.3-0.5) and strong (r > ± 0.5). RESULTS: Patients with DDH reported greater pain and lower function compared to patients with FAIS. 6MWT distance was moderately-to-strongly correlated with a number of patient-reported measures of function (FAIS: r = 0.37 to 0.62, DDH: r = 0.36 to 0.55). Additionally, in patients with DDH, SLHT distance was well correlated with patient reported function (r = 0.37 to 0.60). Correlations between patient-reported pain and objectively measured function were sparse in both patient groups. In patients with FAIS, only 6MWT distance and HOOS Pain (r = -0.53) were significantly correlated. In patients with DDH, 6MWT distance was significantly correlated with VAS Average (r = -0.52) and Best (r = -0.53) pain. CONCLUSION: Pain is greater and function is lower in patients with DDH compared to patients with FAIS. Moreover, the relationship between pain and function differs between patient groups. Understanding these differences is valuable for informing treatment decisions. We recommend these insights be incorporated within the clinical continuum of care, particularly during evaluation and selection of surgical and therapeutic interventions.

There are unique kinematics during locomotor transitions between level ground and stair ambulation that persist with increasing stair grade.

Human ambulation is typically characterized during steady-state isolated tasks (e.g., walking, running, stair ambulation). However, general human locomotion comprises continuous adaptation to the varied terrains encountered during activities of daily life. To fill an important gap in knowledge that may lead to improved therapeutic and device interventions for mobility-impaired individuals, it is vital to identify how the mechanics of individuals change as they transition between different ambulatory tasks, and as they encounter terrains of differing severity. In this work, we study lower-limb joint kinematics during the transitions between level walking and stair ascent and descent over a range of stair inclination angles. Using statistical parametric mapping, we identify where and when the kinematics of transitions are unique from the adjacent steady-state tasks. Results show unique transition kinematics primarily in the swing phase, which are sensitive to stair inclination. We also train Gaussian process regression models for each joint to predict joint angles given the gait phase, stair inclination, and ambulation context (transition type, ascent/descent), demonstrating a mathematical modeling approach that successfully incorporates terrain transitions and severity. The results of this work further our understanding of transitory human biomechanics and motivate the incorporation of transition-specific control models into mobility-assistive technology.

A-Mode Ultrasound-Based Prediction of Transfemoral Amputee Prosthesis Walking Kinematics Via an Artificial Neural Network.

Lower-limb powered prostheses can provide users with volitional control of ambulation. To accomplish this goal, they require a sensing modality that reliably interprets user intention to move. Surface electromyography (EMG) has been previously proposed to measure muscle excitation and provide volitional control to upper- and lower-limb powered prosthesis users. Unfortunately, EMG suffers from a low signal to noise ratio and crosstalk between neighboring muscles, often limiting the performance of EMG-based controllers. Ultrasound has been shown to have better resolution and specificity than surface EMG. However, this technology has yet to be integrated into lower-limb prostheses. Here we show that A-mode ultrasound sensing can reliably predict the prosthesis walking kinematics of individuals with a transfemoral amputation. Ultrasound features from the residual limb of 9 transfemoral amputee subjects were recorded with A-mode ultrasound during walking with their passive prosthesis. The ultrasound features were mapped to joint kinematics through a regression neural network. Testing of the trained model against untrained kinematics from an altered walking speed show accurate predictions of knee position, knee velocity, ankle position, and ankle velocity, with a normalized RMSE of 9.0 ± 3.1%, 7.3 ± 1.6%, 8.3 ± 2.3%, and 10.0 ± 2.5% respectively. This ultrasound-based prediction suggests that A-mode ultrasound is a viable sensing technology for recognizing user intent. This study is the first necessary step towards implementation of volitional prosthesis controller based on A-mode ultrasound for individuals with transfemoral amputation.

Shaping Human Movement via Bimanually-Dependent Haptic Force Feedback.

Haptic feedback can enhance training and performance of human operators; however, the design of haptic feedback for bimanual coordination in robot-assisted tasks (e.g., control of surgical robots) remains an open problem. In this study, we present four bimanually-dependent haptic force feedback conditions aimed at shaping bimanual movement according to geometric characteristics: the number of targets, direction, and symmetry. Haptic conditions include a virtual spring, damper, combination spring-damper, and dual springs placed between the hands. We evaluate the effects of these haptic conditions on trajectory shape, smoothness, and speed. We hypothesized that for subjects who perform worse with no haptic feedback (1) a spring will improve the shape of parallel trajectories, (2) a damper will improve the shape of point symmetric trajectories, (3) dual springs will improve the shape of trajectories with one target, and (4) a damper will improve smoothness for all trajectories. Hypotheses (1) and (2) were statistically supported at the p < 0.001 level, but hypotheses (3) and (4) were not supported. Moreover, bimanually-dependent haptic feedback tended to improve shape accuracy for movements that subjects performed worse on under no haptic condition. Thus, bimanual haptic feedback based on geometric trajectory characteristics shows promise to improve performance in robot-assisted motor tasks.

Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks.

Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this requires a large number of sensors, has a low signal-to-noise ratio, and cannot distinguish between superficial and deep muscle activations. An alternative sensing modality, A-mode ultrasound, can detect and distinguish between changes in superficial and deep muscles. It has also shown promising results in upper limb gesture classification. Despite these advantages, A-mode ultrasound has yet to be employed for lower limb activity classification. Here we show that A- mode ultrasound can classify ambulation mode with comparable, and in some cases, superior accuracy to mechanical sensing. In this study, seven transfemoral amputee subjects walked on an ambulation circuit while wearing A-mode ultrasound transducers, IMU sensors, and their passive prosthesis. The circuit consisted of sitting, standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent, and a spatial-temporal convolutional network was trained to continuously classify these seven activities. Offline continuous classification with A-mode ultrasound alone was able to achieve an accuracy of 91.8±3.4%, compared with 93.8±3.0%, when using kinematic data alone. Combined kinematic and ultrasound produced 95.8±2.3% accuracy. This suggests that A-mode ultrasound provides additional useful information about the user's gait beyond what is provided by mechanical sensors, and that it may be able to improve ambulation mode classification. By incorporating these sensors into powered prostheses, users may enjoy higher reliability for their prostheses, and more seamless transitions between ambulation modes.

Biomechanical mechanism of peak braking force modulation during increased walking speed in healthy young adults.

Walking speed is an important indicator of health and function across a variety of populations. Faster walking requires both larger propulsive and braking forces, thoughof the two, propulsive force generation has been far more extensively investigated. This study seeks to develop and validatea quasi-static biomechanical model of braking forcein healthy individualsacrossself-selected and fast walking speeds. Additionally, the model was used to quantify the relative contribution of knee extension torque versus leading limb angle (LLA) to changes in braking force across walking speeds. Kinetic and kinematic data from 44 young healthy participants walking overground at 2 different speeds were analyzed. The model prediction correlated strongly with actual braking force production at the self-selected speed (r = 0.9; p < 0.01), the fast speed (r = 0.97; p < 0.01) andthe change between speeds (r = 0.95, p < 0.01). On average, increases in knee extension torque and the LLA contributed 132 % and 12 %, respectively, to increases in peak braking force (PBF). Increases in the external lever arm length operated to reduce predicted braking force by 56 %. The results highlight the importance of rapid eccentric contraction of the knee extensors during braking force modulation in healthy gait.

Relating Underlying Performance Objectives of Overground Walking to Observable Walking Mechanics using Predictive Musculoskeletal Simulations.

There exists motor redundancy during human gait that allows individuals to perform the same task in different observable ways (i.e., with varied styles). However, how differences in observable walking mechanics depend on unique and underlying biomechanical objectives is unclear. As an example, these objectives could include metabolic energy consumption, sum of muscle activations, limb mechanical loading, balance and combinations thereof. In this study, we develop predictive neuromuscular simulations to investigate the relationships between these biomechanical objectives and observable mechanics during level walking. We simulated 3D normal walking of five healthy subjects, while optimizing each of the aforementioned objectives-resulting in 25 forward dynamics simulations for analysis. We compared the resulting joint kinematics and moments of different simulations. One of main findings suggests that decreased hip abduction angle is tightly related to when the regulation of dynamic balance (computed as whole-body angular momentum) is included in a movement cost function. We also find that increased joint moments are related to including metabolic cost (i.e., objectives associated with improving the energy economy of movement). Further, the timing of joint kinematics is adjusted for different performance objectives. These findings could guide the development of rehabilitation training and assistive devices that target specific individuals, tasks, and specific styles of movement.

Modeling the Influence of the Human Form and Ambulation Context on Moment- and Power-Generating Abilities of Soft Hip-Flexion Exosuits.

Exosuits are close-fitting devices, which are meant to be worn without restricting the motion of the user in the way that a rigid device would. These soft devices augment lower-limb biomechanics by using flexible, joint-spanning linear elements that are actuated to create moments about the spanned joints, effectively using the human body as the mechanical transmission from input to output. Consequently, the size of the moment arm that an exosuit creates about a given joint is dependent on the size and shape of the user, as well as their individualized gait patterns that depend on the terrain they are negotiating. These highly-variable human and environmental factors affect the performance of all soft exosuits (both passive and active), and the ability to quantify these effects would benefit assistive device development. In this work, we present a system for modeling the effects of user body mass index, biological sex, and gait kinematics on task-dependent exosuit performance. We use this system to estimate the performance of a hip-flexion exosuit over a range of body shapes obtained from a database of 3D human surface models, and with gait kinematics from physical experiments. Our results demonstrate that the user's body mass index, sex, and gait kinematics are necessary factors to consider when designing an exosuit for personalized assistance. This type of analysis can allow device developers to account for the unique shape and gait patterns of individuals, either in generating new designs, developing online control algorithms, or in configuring devices for specific individuals.

Evaluating Electromyography and Sonomyography Sensor Fusion to Estimate Lower-Limb Kinematics Using Gaussian Process Regression.

Research on robotic lower-limb assistive devices over the past decade has generated autonomous, multiple degree-of-freedom devices to augment human performance during a variety of scenarios. However, the increase in capabilities of these devices is met with an increase in the complexity of the overall control problem and requirement for an accurate and robust sensing modality for intent recognition. Due to its ability to precede changes in motion, surface electromyography (EMG) is widely studied as a peripheral sensing modality for capturing features of muscle activity as an input for control of powered assistive devices. In order to capture features that contribute to muscle contraction and joint motion beyond muscle activity of superficial muscles, researchers have introduced sonomyography, or real-time dynamic ultrasound imaging of skeletal muscle. However, the ability of these sonomyography features to continuously predict multiple lower-limb joint kinematics during widely varying ambulation tasks, and their potential as an input for powered multiple degree-of-freedom lower-limb assistive devices is unknown. The objective of this research is to evaluate surface EMG and sonomyography, as well as the fusion of features from both sensing modalities, as inputs to Gaussian process regression models for the continuous estimation of hip, knee and ankle angle and velocity during level walking, stair ascent/descent and ramp ascent/descent ambulation. Gaussian process regression is a Bayesian nonlinear regression model that has been introduced as an alternative to musculoskeletal model-based techniques. In this study, time-intensity features of sonomyography on both the anterior and posterior thigh along with time-domain features of surface EMG from eight muscles on the lower-limb were used to train and test subject-dependent and task-invariant Gaussian process regression models for the continuous estimation of hip, knee and ankle motion. Overall, anterior sonomyography sensor fusion with surface EMG significantly improved estimation of hip, knee and ankle motion for all ambulation tasks (level ground, stair and ramp ambulation) in comparison to surface EMG alone. Additionally, anterior sonomyography alone significantly improved errors at the hip and knee for most tasks compared to surface EMG. These findings help inform the implementation and integration of volitional control strategies for robotic assistive technologies.

A Predictive Framework to Provide Neuromuscular Insights in Reshaping Dynamic Balance during Transient Locomotion.

Anticipated and unanticipated directional changes are commonplace in daily lives. The need for dynamic balance is amplified when these transitions are performed in an unplanned (i.e., unanticipated) manner. In this study, we used predictive simulations and optimal control constructs to test a method for reshaping dynamic balance of unanticipated crossover cuts. We also compare how such improvements can be mediated at the musculotendon level. Our study shows that the performance of unanticipated crossover cuts can be optimized to improve dynamic balance, and highlight the potential for predictive simulations and optimal control to provide quantitative targets for reshaping dynamic balance in unanticipated crossover cuts-targets which are biologically-feasible.Clinical Relevance-This approach could inform task-specific rehabilitation therapy by suggesting how to reshape an individual's dynamic balance and which joint-level kinematic adjustments and muscle groups would be optimal to engage in doing so.

Ultrasound-Derived Features of Muscle Architecture Provide Unique Temporal Characterization of Volitional Knee Motion.

Sonomyography, or dynamic ultrasound imaging of skeletal muscle, has gained significant interest in rehabilitation medicine. Previously, correlations relating sonomyography features of muscle contraction, including muscle thickness, pennation angle, angle between aponeuroses and fascicle length, to muscle force production, strength and joint motion have been established. Additionally, relationships between grayscale image intensity, or echogenicity, with maximum voluntary isometric contraction of muscle have been noted. However, the time relationship between changes in various sonomyography features during volitional motion has yet to be explored, which would highlight if unique information pertaining to muscle contraction and motion can be obtained from this real-time imaging modality. These new insights could inform how we assess muscle function and/or how we use this modality for assistive device control. Thus, our objective was to characterize the time synchronization of changes in five features of rectus femoris contraction extracted from ultrasound images during seated knee extension and flexion. A cross-correlation analysis was performed on data recorded by a handheld ultrasound system as able-bodied subjects completed seated trials of volitional knee extension and flexion. Changes in muscle thickness, angle between aponeuroses, and mean image echogenicity, a change in brightness of the grayscale image, preceded changes in our estimates of pennation angle and fascicle length. The leading nature of these features suggest they could be objective features for early detection of impending joint motion. Finally, multiple sonomyographic features provided unique temporal information associated with this volitional task.Clinical Relevance-This work evaluates the time relationship between five commonly reported features of skeletal muscle architecture during volitional motion, which can be used for targeted clinical assessments and intent detection.

A Computational Framework based on Medical Imaging and Random Sampling to Guide Optimal Residual Limb Designs for Individuals with Transfemoral Limb Loss.

The purpose of this study was to understand how the form (i.e., shape and presence of underlying soft tissue) of residual limb tissue influences limb function and comfort for individuals with transfemoral limb loss. Specifically, there exist surgical techniques that are frequently applied to the lower limbs of individuals to reduce an excessive soft tissue envelope. However, the clinical goals are frequently from a cosmetic perspective and are applied most commonly to individuals who are obese and not necessarily those with limb loss. For specific individuals with transfemoral limb loss, there likely exist limb shapes and distributions of underlying soft tissue that more optimally engage with lower-limb prostheses. Based on recent experimental findings, optimizing the limb and its physical connection to lower-limb prostheses, may have equivalent if not greater impact on user outcomes than selection of prosthetic components. This study develops and tests a method for informing optimal designs of the residual limb for individuals with transfemoral amputation. The framework uses patient-specific MRI images of an individual's residual limb, and within a mechanical modeling framework applies Latin hypercube sampling to investigate which portions of the underlying limb tissue most positively affect mechanical objectives associated with limb function and comfort. These theoretical results predicted from this system aimed to inform optimal limb designs were then compared to a currently used surgical method known as medial thighplasty, which was previously applied in one patient, to assess agreement. These simulations showed that the regions of the limb most contributing negatively to the objective function were located at the distal end of the limb and were far from muscle tissue (i.e., were mostly superficial). These findings suggest that limb techniques which seek to produce residual limbs that are most slim at their medial and distal end are beneficial and may lead to improved fit and function of lower-limb prostheses.Clinical Relevance-Prosthetic technology advancement within the last decade has heightened the hopes of individuals with amputation. However, how these devices integrate to their human users is non-trivial and can curtail these advancements. Tools are needed to inform how residual limb itself can be optimized to better integrate with prostheses.

Femur Abduction Associated with Transfemoral Amputation Alters the Profile of Lumbopelvic Mechanical Loads During Generalized End-Limb Loading.

Pain in the lower back is frequent problem for most individuals with transfemoral amputation, which limits their overall mobility and quality of life. While the underlying root causes of back pain are multifactorial, a contributing factor is the mechanical loading environment within the lumbopelvic joint. Specifically, this study aims to explore the upstream effects amputation has on the mechanical loading environment of the lumbopelvic joint using a 3D musculoskeletal model of transfemoral amputation. A generic musculoskeletal model was altered to represent a transfemoral amputation. Muscle parameters were adjusted to represent a myodesis amputation surgery that preserved musculotendon tension in a neutral anatomical pose. The model contained a total of 28 degrees of freedom and 76 muscles spanning the lower-limb and torso. In forward dynamics simulations, generalized external forces were applied to the distal end of the residual limb at a series of directions. Axial, oblique and transverse 10 N end-limb loads were applied. In addition, simulations were performed for 0°, 4°, and 8° of femur abduction, which are clinically observed in individuals with transfemoral amputation. In these simulations, reaction forces and moments at the lumbopelvic joint were computed. In general, femur abduction had little effect on back loading for an axial applied end-limb force. These data showed that while the individual magnitudes of lumbopelvic force and moment reactions did not significantly deviate for differing levels of femur abduction, the pattern of how these forces changes in response to different end-limb force directions (applied circumferentially along the limb) was affected by femur abduction angle.Clinical Relevance- The changes in joint reaction forces in the lumbopelvic joint from an aligned position to an abducted position reinforce the importance of avoiding hip flexion-abduction contracture during amputation surgery. This suggests that surgical techniques such as myodesis, osseointegration, or medial thighplasty, which intend to maintain anatomical alignment may have beneficial upstream effects for the patients during locomotion. Given the prevalence of lower back pain in individuals with transfemoral amputation, teasing out the causes of lower back pain could bring relief to a population that struggles with community independence.

Whole-body and Segmental Contributions to Dynamic Balance in Stair Ambulation are Sensitive to Early-Stage Parkinson's Disease.

Stair ambulation is commonplace in daily living activities, yet biomechanically more challenging compared to level-ground walking. With reduced lower-limb muscle strength and increased rigidity of extremities, people with Parkinson's disease (PD) experience impaired balance and higher incidence of falls each year. However, the regulation of whole-body dynamic balance of individuals with PD in stair walking is unclear. Whole-body angular momentum (H) is a useful metric for assessing dynamic balance that accounts for the angular movements of all body segments about the body center-of-mass (COM). In this study we investigated the regulation of H and segmental contributions to H during stair ascent and descent walking in individuals with PD compared to healthy subjects. During stair descent, the magnitude of sagittal-plane H increased in participants with PD compared to healthy subjects in ipsilateral (most affected side) leg stance. Meanwhile, the legs contributed more to sagittal-plane H in individuals with PD compared to healthy subjects. During stair descent walking, the magnitude of transverse-plane H was also greater in participants with PD compared to healthy subjects during the second half of ipsilateral leg gait cycle. The increased magnitude of negative (i.e., forward) sagittal-plane H in the ipsilateral stance of stair descent walking suggests that individuals with PD experience greater difficulties maintaining their forward rotation during such tasks.

Performance of Sonomyographic and Electromyographic Sensing for Continuous Estimation of Joint Torque During Ambulation on Multiple Terrains.

Advances in powered assistive device technology, including the ability to provide net mechanical power to multiple joints within a single device, have the potential to dramatically improve the mobility and restore independence to their users. However, these devices rely on the ability of their users to continuously control multiple powered lower-limb joints simultaneously. Success of such approaches rely on robust sensing of user intent and accurate mapping to device control parameters. Here, we compare two non-invasive sensing modalities: surface electromyography and sonomyography, (i.e., ultrasound imaging of skeletal muscle), as inputs to Gaussian process regression models trained to estimate hip, knee and ankle joint moments during varying forms of ambulation. Experiments were performed with ten non-disabled individuals instrumented with surface electromyography and sonomyography sensors while completing trials of level, incline (10°) and decline (10°) walking. Results suggest sonomyography of muscles on the anterior and posterior thigh can be used to estimate hip, knee and ankle joint moments more accurately than surface electromyography. Furthermore, these results can be achieved by training Gaussian process regression models in a task-independent manner; i.e., incorporating features of level and ramp walking within the same predictive framework. These findings support the integration of sonomyographic and electromyographic sensing within powered assistive devices to continuously control joint torque.

Lower-limb kinematics and kinetics during continuously varying human locomotion.

Human locomotion involves continuously variable activities including walking, running, and stair climbing over a range of speeds and inclinations as well as sit-stand, walk-run, and walk-stairs transitions. Understanding the kinematics and kinetics of the lower limbs during continuously varying locomotion is fundamental to developing robotic prostheses and exoskeletons that assist in community ambulation. However, available datasets on human locomotion neglect transitions between activities and/or continuous variations in speed and inclination during these activities. This data paper reports a new dataset that includes the lower-limb kinematics and kinetics of ten able-bodied participants walking at multiple inclines (±0°; 5° and 10°) and speeds (0.8 m/s; 1 m/s; 1.2 m/s), running at multiple speeds (1.8 m/s; 2 m/s; 2.2 m/s and 2.4 m/s), walking and running with constant acceleration (±0.2; 0.5), and stair ascent/descent with multiple stair inclines (20°; 25°; 30° and 35°). This dataset also includes sit-stand transitions, walk-run transitions, and walk-stairs transitions. Data were recorded by a Vicon motion capture system and, for applicable tasks, a Bertec instrumented treadmill.

Biomechanical analysis of an unpowered hip flexion orthosis on individuals with and without multiple sclerosis.

BACKGROUND: Gait impairment is a common complication of multiple sclerosis (MS). Gait limitations such as limited hip flexion, foot drop, and knee hyperextension often require external devices like crutches, canes, and orthoses. The effects of mobility-assistive technologies (MATs) prescribed to people with MS are not well understood, and current devices do not cater to the specific needs of these individuals. To address this, a passive unilateral hip flexion-assisting orthosis (HFO) was developed that uses resistance bands spanning the hip joint to redirect energy in the gait cycle. The purpose of this study was to investigate the short-term effects of the HFO on gait mechanics and muscle activation for people with and without MS. We hypothesized that (1) hip flexion would increase in the limb wearing the device, and (2) that muscle activity would increase in hip extensors, and decrease in hip flexors and plantar flexors. METHODS: Five healthy subjects and five subjects with MS walked for minute-long sessions with the device using three different levels of band stiffness. We analyzed peak hip flexion and extension angles, lower limb joint work, and muscle activity in eight muscles on the lower limbs and trunk. Single-subjects analysis was used due to inter-subject variability. RESULTS: For subjects with MS, the HFO caused an increase in peak hip flexion angle and a decrease in peak hip extension angle, confirming our first hypothesis. Healthy subjects showed less pronounced kinematic changes when using the device. Power generated at the hip was increased in most subjects while using the HFO. The second hypothesis was not confirmed, as muscle activity showed inconsistent results, however several subjects demonstrated increased hip extensor and trunk muscle activity with the HFO. CONCLUSIONS: This exploratory study showed that the HFO was well-tolerated by healthy subjects and subjects with MS, and that it promoted more normative kinematics at the hip for those with MS. Future studies with longer exposure to the HFO and personalized assistance parameters are needed to understand the efficacy of the HFO for mobility assistance and rehabilitation for people with MS.