Traumatic brachial plexus injury (BPI) results in significant disability, often hindering functionality in the patient's daily life. Post- surgery, muscle strength recovery can take up to two years, with 40% of patients requiring even longer. A powered elbow orthosis can enhance functionality during activities of daily living (ADLs). This study tested a novel powered myoelectric elbow orthosis (PMEO) during ADLs. Subjects with BPI were fitted with the PMEO and divided into two groups: more impaired (Manual Muscle Test (MMT) < 3, N = 5) and less impaired (MMT≤ 3, N = 4). They performed four ADLs involving full elbow motion, including an activity requiring the subjects to lift a basket with weights. Upper extremity kinematics, electromyographic activity, weight lifted, and subject feedback on the device's form and fit were collected and analyzed. Results showed that the PMEO significantly improved elbow range of motion in the more impaired group (14 ± 23 degrees, p = 0.019) without any additional compensatory motions in the shoulder or trunk. More impaired subjects lifted an average of 1.1 ± 0.6 kg with the PMEO, whereas they could not do so without it (p = 0.011). Subjects appreciated the PMEO's weight, fit, and form. All could don and doff the device with minimal assistance. These findings demonstrate that the PMEO is a viable option to enhance ADL function for patients with BPI.

Older adults have a decreased trunk movement control which is linked to their higher fall risk. While motor/cognitive dual-tasking deteriorates balance and walking in older adults, there is limited understanding on how trunk kinematics and kinetics are affected by dual-tasking in scenarios where falls can occur. Therefore, the purpose of the study was to determine the impacts of a challenging motor dual-task, specifically obstacle avoidance during walking, on trunk and lower-body kinematics and kinetics of older adults compared to young adults. The study captured three-dimensional kinematic and kinetic data from 12 young adults and 10 older adults as they walked on a treadmill and stepped over an obstacle with both legs. The study analyzed trunk, hip, knee, and ankle angles and torques. Trunk torque was further broken down to trunk muscle torque, gravitational torque, and inertia torque. A linear mixed effects model was used to investigate the difference in each variable between the two groups. Older adults exhibited significantly increased trunk flexion angle and trunk extension muscle torque compared to young adults, with the trunk being the only segment/joint showing differences in both kinematics and kinetics. Trunk torque breakdown analysis revealed that larger trunk flexion led to a larger gravitational torque, which contributed to an increased compensatory trunk muscle torque. Moreover, older adults' less controlled trunk flexion during weight shifting from trail leg to the lead leg, necessitated a compensatory trunk deceleration during trail leg obstacle avoidance which was achieved by generating additional increase in trunk muscle torque. The study demonstrated that motor dual-tasking has the most negative effects on trunk control in older adults compared to young adults. This exposes older adults to a higher fall risk. Therefore, future work should focus on supporting trunk control during daily multi-tasking conditions where falls can occur.

Despite advances in wearable robots across various fields, there is no consensus definition or design framework for the application of this technology in rehabilitation or musculoskeletal (MSK) injury prevention. This paper aims to define wearable robots and explore their applications and challenges for military rehabilitation and force protection for MSK injury prevention. We conducted a modified Delphi method, including a steering group and 14 panelists with 10+ years of expertise in wearable robots. Panelists presented current wearable robots currently in use or in development for rehabilitation or assistance use in the military workforce and healthcare. The steering group and panelists met to obtain a consensus on the wearable robot definition applicable for rehabilitation or primary injury prevention. Panelists unanimously agreed that wearable robots can be grouped into three main applications, as follows: (1) primary and secondary MSK injury prevention, (2) enhancement of military activities and tasks, and (3) rehabilitation and reintegration. Each application was presented within the context of its target population and state-of-the-art technology currently in use or under development. Capturing expert opinions, this study defines wearable robots for military rehabilitation and MSK injury prevention, identifies health outcomes and assessment tools, and outlines design requirements for future advancements.

INTRODUCTION:Recovering from neuromuscular injuries or conditions can be a challenging journey that involves complex surgeries and extensive physical rehabilitation. During this process, individuals often rely on orthotic devices to support and enable movement of the affected limb. However, users have criticized current commercially available powered orthotic devices for their bulky and heavy design. To address these limitations, we developed a novel powered myoelectric elbow orthosis. MATERIALS AND METHODS:The orthosis incorporates 3 mechanisms: a solenoid brake, a Bowden cable-powered constant torque elbow mechanism, and an extension limiter. The device controller and battery are in a backpack to reduce the weight on the affected arm. We performed extensive calculations and testing to ensure that the orthosis could withstand at least 15 Nm of elbow torque. We developed a custom software effectively control the orthosis, enhancing its usability and functionality. A certified orthotist fitted a subject who had undergone a gracilis free functioning muscle transfer surgery with the device. We studied the subject under Mayo clinic IRB no. 20-006849 and obtained objective measurements to assess the orthosis's impact on upper extremity functionality during daily activities. RESULTS:The results are promising since the orthosis significantly improved elbow flexion range of motion by 40° and reduced compensatory movements at the shoulder (humerothoracic joint) by 50°. Additionally, the subject was able to perform tasks which were not possible before, such as carrying a basket with weights, highlighting the enhanced functionality provided by the orthosis. CONCLUSION:In brief, by addressing the limitations of existing devices, this novel powered myoelectric elbow orthosis offers individuals with neuromuscular injuries/conditions improved quality of life. Further research will expand the patient population and control mechanisms.

We present a wearable "exo-shell " device inspired by the human spine for improving the gait of elderly people during obstacle avoidance tasks. This device-designed and fabricated with origami-inspired techniques-features a serial chain of lockable joints that can be stiffened using a braking system inspired by laminar jamming concepts. Current related work has identified that the trunk plays a crucial role in obstacle avoidance tasks. In this article, we thus propose an affordable wearable system that can be quickly fabricated and whose design can be adjusted to fit the individual wearer. The design leverages switchable, passive systems, in combination with lightweight materials that remain as "transparent " to the user as possible when inactive. This article focuses on translating human requirements into a tangible design that addresses the current state of our biomechanics knowledge. We describe the kinematics and forces of our proposed device, describe the performance of our system in a locked and unlocked state, discuss the integration of various sensors into our device, and characterize the performance of the device when locked and unlocked.

This chapter presents three experiments extending projectile perception and interception research by examining the influence of a symmetry axis on the perception of a thrown, oblong, symmetric projectile, specifically an American football. The experiments verify the existence of similar perceptual biases in 3-dimensional space, in a real-world, spatial judgment task. First experiment consists of a web-survey examining participant's accounts of the in-flight behavior of an American football. In Experiment 2, the researchers empirically examined the physics of the in-flight behavior of a thrown football, with a focus on the relationship of the axis of symmetry to the trajectory. Experiment 3 compared performance in a spatial judgment task that asked participants to predict the final destination of spherical and oblong projectiles, specifically, Volleyballs and footballs. With advancing locomotive technology, the existence of these biases has important implications in perceptual judgments of real-world objects such as naval vessels, airplanes, skidding automobiles and spacecraft.

This commentary merges perspectives from robotics engineering with marketing to achieve two goals: First, the commentary briefly illustrates how wearable robotics are likely to affect the entire marketing value chain and its connections to customer experiences, and it points to some substantive research implications for marketers. Second, the commentary then broadens its analytical lens and proposes `transhumanist marketing' as a fruitful and overarching conceptual foundation for future research related to wearable robotics.

Dynamic and cognitive multi-tasking might affect balance and walking negatively and increase risk of falling. Trunk movement control is critical for balance maintenance and fall-prevention. The impact of multi-tasking on trunk movement control has not been thoroughly studied. In a challenging dynamic multi-tasking condition such as walking and obstacle avoidance, presence of a cognitive task not only increases risk of tripping but also may increase risk of falling by deteriorating trunk control. Our objective was to investigate the impacts of a challenging dynamic and cognitive multi-tasking condition (walking + obstacle avoidance + cognitive task) on trunk kinematics and kinetics and compare those with other joints/segments. Trunk, pelvis, hip, knee, and ankle kinematics and kinetics of 12 young adults were compared between joints/segments and conditions. During walking and obstacle avoidance (dynamic multi-tasking), the trunk had the largest normalized increase in peak flexion angle and extension torque compared to walking, among the other joints/segments. The presence of a cognitive task during walking and obstacle avoidance (dynamic and cognitive multi-tasking) did not impact any of the joints/segments biomechanics except the trunk peak extension torque that was increased. Furthermore, trunk kinematics showed the largest residual differences (post-effects) in 3 cycles after obstacle avoidance compared to walking. The presence of a cognitive task (dynamic and cognitive multitasking) did not impact the post-effects of obstacle avoidance on any joints/segments except the trunk with its residual difference from normal walking further increased. These results suggest that a cognitive task deteriorates trunk control and interferes with the ability to regain normal trunk biomechanics after obstacle avoidance. In summary, the trunk requires the largest biomechanical adjustments in a challenging dynamic and cognitive multi-tasking condition where there is a risk of falling. Our study provides baseline results suggesting that trunk control demands more attention and is more negatively affected by dynamic and cognitive multi-tasking. Our results raise a concern for elderly population as their trunk control is already impaired and common daily multi-tasking could further deteriorate their trunk control and increase fall risk.

Abstract Back pain is one of the largest drivers of workplace injury and lost productivity in industries around the world. Back injuries were one of the leading reasons in resulting in days away from work at 38.5% across all occupations, increasing for manual laborers to 43%. While the cause of the back pain can vary across occupations, for materiel movers it is often caused from repetitive poor lifting. To reduce the issues, the Aerial Porter Exoskeleton (APEx) was created. The APEx uses a hip-mounted, powered exoskeleton attached to an adjustable vest. An onboard computer calculates the configuration of the user to determine when to activate. Lift form is assisted by using a novel lumbar brace mounted on the sides of the hips. Properly worn, the APEx holds the user upright while providing additional hip torque through a lift. This was tested by having participants complete a lifting test with the exoskeleton worn in the “on” configuration compared with the exoskeleton not worn. The APEx has been shown to deliver 30 Nm of torque in lab testing. The activity recognition algorithm has also been shown to be accurate in 95% of tested conditions. When worn by subjects, testing has shown average peak reductions of 14.9% BPM, 8% in VO2 consumption, and an 8% change in perceived effort favoring the APEx.

In this work, the lower extremity physiological parameters are recorded during normal walking gait, and the dynamical systems theory is applied to determine a stability analysis. The human walking gait pattern of kinematic and dynamical data is approximated to periodic behavior. The embedding dimension analysis of the kinematic variable's time trace and use of Taken's theorem allows us to compute a reduced-order time series that retains the essential dynamics. In conjunction with Floquet theory, this approach can help determine the system's stability characteristics. The Lyapunov–Floquet (L-F) transformation application results in constructing an invariant manifold resembling the form of a simple oscillator system. It is also demonstrated that the simple oscillator system, when re-mapped back to the original domain, reproduces the original system's time evolution (hip angle or knee angle, for example). A reinitialization procedure is suggested that improves the accuracy between the processed data and actual data. The theoretical framework proposed in this work is validated with the experiments using a motion capture system.

Abstract Ground Reaction Force (GRF) is an essential gait parameter. GRF analysis provides important information regarding various aspects of gait. GRF has been traditionally measured using bulky force plates within lab environments. There exist portable force sensing units, but their accuracy is wanting. Estimation of GRF has applications in remote wearable systems for rehabilitation, to measure performance in athletes, etc. This article explores a novel method for GRF estimation using the Lyapunov-Floquet (LF) and invariant manifold theory. We assume human gait to be a periodic motion without external forcing. Using time delayed embedding, a reduced order system can be reconstructed from the vertical GRF data. LF theory can be applied to perform system identification via Floquet Transition Matrix and the Lyapunov Exponents. A Conformal Map was generated using the Lyapunov Floquet Transformation that maps the original time periodic system on a linear Single Degree of Freedom (SDoF) oscillator. The response of the oscillator system can be calculated numerically and then remapped back to the original domain to get GRF time evolution. As an example, the GRF data from an optical motion capture system for two subjects was used to construct the reduced order model and system identification. A comparison between the original system and its reduced order approximation showed good correspondence.

A hip exoskeleton was designed that can assist hip extension during squat lifting and pushing. The device incorporates a motor, ball screw in a compact lightweight package. The total weight of the system including the battery is 3.94 kg and the system can supply over 30 Nm of torque to each leg. The device assists lifting and pushing and is not engaged during walking, running or other tasks.

The complex dynamics of human gait is yet to be completely understood. Researchers have quantified stability of walking gait using Floquet multipliers as well as Lyapunov exponents. In this article, we utilize the techniques and tools from dynamical system theory and invariant manifolds to map the gait data onto a time invariant representation of a dynamical system. As an example, the complex behavior of the joint angle during walking was studied using a conformal mapping approach that transformed the time periodic system into a time invariant linear system. Time-delay embedding was used to reconstruct the dynamics of the original gait system with time series kinematic data. This minimal realization of the system was used to construct a Single Degree of Freedom (SDOF) oscillator. The time evolution of the linear oscillatory system was mapped back using the conformal mapping derived using Lyapunov-Floquet Theory. This algorithm was verified for walking gait kinematics data for two healthy human subjects. A comparison was drawn between the phase space behavior of the original time periodic system and the remapped time invariant system. The two systems showed good correlation. The algorithm resulted in a well correlated phase space representation.

It is important to know and be able to classify the drivers' behavior as good, bad, keen or aggressive, which would aid in driver assist systems to avoid vehicle crashes. This research attempts to develop, test, and compare the performance of machine learning methods for classifying human driving behavior. It also proposes to correlate driver affective states with the driving behavior. The major contributions of this work are to classify the driver behavior using Electroencephalograph (EEG) while driving simulated vehicle and compare them with the behavior classified using vehicle parameters and affective states. The study involved both classical machine learning techniques such as k-Nearest Neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) and latest "unsupervised" Hybrid Deep Learning techniques, and compared the accuracy ofclassification across subjects, various driving scenarios and affective states.

An active ankle-foot orthosis (AAFO) was developed with the intent of providing propulsive ground reaction force to individuals at risk of experiencing fall.The device makes use of one double-acting cylinder per leg, and a lever arm system to transfer propulsive force to the ground, and potentially assist in fall prevention and rehabilitation.Preliminary tests have been shown to improve ground reaction forces in walking.In this paper, the design and construction of the device is included as well as the control algorithm used and testing procedure.This research may be used to advance the field of gait assistance and fall prevention through use of active foot orthotics.

The design of a phase-based robust oscillator for wearable robots, that could assist humans performing periodic or repetitive tasks, is presented in this paper. The bounds on perturbations, that guaranteed the stability of the output for the phase oscillator controller, were identified and the Lyapunov redesign method was applied to construct a robust controller using a bounding function. The robust controller produced a bounded control signal to modify the amplitude and frequency of the resulting second-order oscillator to modulate the stiffness and damping properties. In this paper, the focus is on the mathematical modeling of the controller, its dynamic stability and robustness for human–robot application. The proposed approach was verified through a simple pendulum experiment. The results provided evidence that a better limit cycle, with a controlled radial spread of the steady state, was obtained with Lyapunov redesigned phase oscillator. Finally, the potential of the proposed approach for hip assistance in a healthy subject wearing HeSa (Hip Exoskeleton for Superior Assistance) during periodic activities are discussed with preliminary results.

Developing controllers for exoskeletons has many challenging requirements: one of which is creating a torque command based on measured human data that that is in phase with the user (in-synchrony with the human gait). We show that the hip torque for walking gait can be modeled using a phase angle based on hip angular position and velocity. This model is superior to a standard impedance model based on inertia, damping, and stiffness parameters because the phase model uses less parameters and they change linearly with varying speed and weight. The controller has been tested on ten subjects (weighing from 68 to 118kg) wearing the hip exoskeleton walking at speeds from 0.7 to 1.8m/s in outdoor environments.

In the Human Machine Integration laboratory, we have been designing wearable robots.For our robotic systems, the user's walking pattern and intent must be determined to generate appropriate motor outputs.In the past, we have used tunable gait patterns, variable stiffness patterns, and a tibia based controller.In this paper, we focus on understanding human gait and the underlying patterns by studying phase curves.For example, we use the progression of the shank phase angle as a metronome to determine the user's percent gait cycle.We go one step further by studying the phase angle of the shank as a function of the phase angle of the foot.A signature pattern between the two phase angles is shown.The pattern seems to be invariant to different tasks such as walking, walking quickly, and walking on slopes.In the future, it is hoped that a shank phase angle with a unique orientation and angular speed can be used to determine a unique foot phase angle allowing the generation of appropriate motor outputs.

This paper investigates the design of a robotic fabric-based, soft ankle module capable of generating 50% of the human ankle stiffness, in plantarflexion and dorsiflexion for walking. Kinematics, dynamics, and anatomy of the human ankle joint are studied to set the functional requirements of the module. The design of the compliant and lightweight soft ankle module uses fabric-based inflatable actuator arrays for actuation. Models for the human ankle stiffness, as well as a data-driven model of soft ankle module is presented. A high-level stiffness controller utilizing the human ankle and soft ankle model with a low-level pressure controller is implemented. We demonstrate the ability to closely follow the ankle stiffness trajectory using soft ankle module.

In this paper, an adaptive oscillator method Amplitude Omega Adaptive Oscillator (AωAO), is proposed to provide bilateral hip assistance for human locomotion. A realtime human locomotion recognition algorithm is integrated with AωAO to make it robust for various gait activities. The human locomotion recognition algorithm comprises both low-level (to detect activities) and high-level classifiers to detect transitions between activities. The Support Vector Machine (SVM) and Discrete Hidden Markov Model (DHMM) are used as low-level and high-level classifiers respectively. The human locomotion recognition algorithm is trained using two-dimensional features, Amplitude (A) and Omega (ω), obtained from thigh angle measurements, using a single Inertial Measurement Unit (IMU) on each limb. In AωAO, a pool with four adaptive oscillators (AOs) is used to estimate the filtered thigh angle trajectory. This pool converges to the frequency and phase of the signal, adaptively. To account for amplitude convergence, the amplitude parameters of the oscillator need to be reinitialized based on the human activity, identified by the human locomotion recognition algorithm. In addition to the adaptive oscillators, a Gaussian kernel function based nonlinear filter is employed to predict the future estimates of thigh angles. These predicted estimates, along with the user thigh angles, are used to calculate hip assistive torque in real-time. To verify the efficacy of the proposed approach, experiments were performed, using Hip exoskeleton for Superior Assistance (HeSA), on three healthy subjects. The human locomotion recognition algorithm reported higher classification and prediction accuracy of 95.2% and 94.9 % respectively. Activity Classification, Assistive devices, Human Activity Recognition