Long jumpers with below the knee amputation (BKA) that take off from their running-specific prosthesis (RSP) improved performances significantly over the last years. The long jump biomechanics differs compared to athletes without BKA and the question arises whether the spring-like properties of the RSP facilitate achieving long jumping distances. The aim of this work is to propose a long jump model for athletes with and without BKA, to evaluate it and to apply it for comparing long jump motions with and without RSP. We establish rigid multi-body system models of one athlete with and one athlete without below the knee amputation (BKA). Long jump motions are computed by solving a specific optimal control problem (OCP) with constraints enforcing a physically correct dynamics, both for motion reconstruction or motion synthesis. With the proposed long jump model, we are able to compute realistic long jump motions. We discuss the causes of differences in measured long jumps and show directions for eliminating them. For both athletes, the synthesized solutions reveal potential for performance improvement. The jumping distance of the athlete without BKA is 64cm (6.9

The application of autonomous robotics to close-contact healthcare tasks, such as the nasopharyngeal (NP) swab test, has clear potential for reducing infection risks to staff and improving efficiency. We propose a control system that performs the NP swab test with a collaborative manipulator arm, guided by an instrumented end-effector that measures force and visual information. We assume a scenario where the patient is unrestrained, with hardware general enough for other types of close-contact tasks. The system employs visual servo control to align the swab with the nostrils. A compliant joint velocity controller inserts the swab into the nasal cavity, following a planned trajectory adjusted with force feedback. Fuzzy logic systems are designed to detect when the swab reaches the nasopharynx and enforce safety criteria. We validate the system using a second robotic arm that holds a nasal cavity phantom and simulates natural head motions. Extensive experiments identify controller configurations capable of effectively performing the NP swab test even with significant head motion.

BackgroundStanding up and sitting down are important activities of daily living, but require large leg moments that often exceed the muscle strength of older adults. Some robotic rollators are designed to provide standing-up and sitting-down assistance through actuated handles or armrests to reduce the loads on the legs, but it is still unclear how they should move. There is limited information on appropriate assistance trajectories and their effects on the body during standing up and sitting down.MethodsWe designed four physiological, scalable and parameterized handle trajectories based on unassisted shoulder movement that can be readily implemented in robotic assistive devices, and evaluated their effect on leg loading, energy input, handle forces and perceived assistance in 15 healthy younger adults. We created a robotic assistance simulator device equipped with moving handles to compare the trajectories to static handles (representing a conventional rollator), and collected full-body motion, ground reaction forces, handle forces and scored perceived assistance.ResultsThe proposed handle trajectories substantially decreased leg loads compared to the static handle assistance (non-moving handle), with the two best-performing trajectories reducing the peak hip extension moment by over 70% and the peak knee extension moment by over 50% during standing up and sitting down. This is associated with an increase in peak vertical handle forces of over 30%, with the total bilateral vertical forces reaching up to 60% of body weight, and a decrease in peak horizontal force of more than 50%. The subjective participants' perception reflected the lower limb mechanical load. The handle velocity was shown to play a secondary role within the investigated range.ConclusionThe proposed support trajectories can be scaled to the person's anthropometry and readily implemented in robotic assistive devices, and were shown to substantially reduce leg loading, potentially improving life quality of individuals with difficulties in standing up. However, the large vertical handle forces and thus upper body demand during moving-handle assistance is a trade-off with relieving the lower limb load. This work provides a comprehensive foundation for the design of the necessary further experimental assessments with the target population.

BACKGROUND AND OBJECTIVES:Maintaining mobility is crucial for older adults to support daily activities and independent living. Despite advancements in robotic assistive devices for walking and sit-to-stand (STS) assistance, their adoption among older adults remains limited, and research on their preferences is scarce. This study aims to better understand older adults' attitudes towards such devices using a mixed-methods online evaluation procedure. RESEARCH DESIGN AND METHODS:The evaluation started with video presentations to demonstrate the design and functionality of three robotic devices, i.e. a STS assistive device, an exoskeleton device, and an exosuit device. Participants provided feedback via open questions and established scales after watching the videos. In total, N = 117 healthy participants (mean age: 67.7 years) completed the evaluation. Data were analysed using qualitative content analysis, analyses of variance, and multiple regression analyses following a mixed-methods approach. RESULTS:Participants mentioned more benefits than challenges but concerns were raised about ease of use, portability, and integration into everyday life. More challenges were reported for the exoskeleton compared to the sit-to-stand assistive device and the exosuit. Regression analyses predicting intention to use showed gender-based differences in preferences for the exoskeleton and exosuit. DISCUSSION AND IMPLICATIONS:Findings highlight usability, safety, and everyday integration as key factors for acceptance. While all three devices show potential, participants favoured the sit-to-stand device for its simplicity and reliability. Results underscore user-centered designs prioritising ease of use and adaptability, and demonstrate that online evaluations can guide early-stage development before costly prototyping.

Sit-to-stand (STS) transfer is a fundamental but challenging movement that plays a vital role in older adults' daily activities. The decline in muscular strength and coordination ability can result in difficulties performing STS and, therefore, the need for mobility assistance by humans or assistive devices. Robotics rollators are being developed to provide active mobility assistance to older adults, including STS assistance. In this paper, we consider the robotic walker SkyWalker, which can provide active STS assistance by moving the handles upwards and forward to bring the user to a standing configuration. In this context, it is crucial to monitor if the user is performing the STS and adapt the rollator's control accordingly. To achieve this, we utilized a standard vision-based method for estimating the human pose during the STS movement using Mediapipe pose tracking. Since estimating a user's state from extreme proximity to the camera is challenging, we compared the pose identification results from Mediapipe to ground truth data obtained from Vicon marker-based motion capture to assess accuracy and reliability of the STS motion. The fourteen kinematic features critical for accurate pose estimation were selected based on literature review and the specific requirements of our robot's STS method. By employing these features, we have implemented a phase classification system that enables the SkyWalker to classify the user's STS phase in real-time. The selected kinematics from vision-based human state estimation method and trained classifier can be furthermore generalized to other types of motion support, including adaptive STS path planning and emergency stops for safety insurance during STS.

The understanding of natural human adaptation during exoskeleton-assisted locomotion - particularly individual differences in adaptation behaviors and temporal progression - remains limited. In this work, we investigate temporal evolution of biomechanical variables to uncover participant-specific adaptation strategies across different exoskeleton-assisted locomotion scenarios. Nine healthy participants performed treadmill walking under three conditions: without an exoskeleton, with exoskeleton active ankle assistance, and with exoskeleton zero-torque. Lower limb kinematics, inter-joint coordination, and metabolic cost of transport (MCoT) were analyzed at both the group and individual levels. Results indicate that adaptation is gradual and highly individualized, with substantial variability in convergence timing and movement patterns across participants. Kinematic adaptation occurred asynchronously across lower limb, with larger fluctuations during the swing phase. Metabolic responses were heterogeneous and often non-convergent, highlighting the limitations of steady-state assumptions commonly adopted in the literature. These findings emphasize the importance of individual-level, temporal evolution analyses for understanding adaptation dynamics in exoskeleton use.

The shortage of healthcare staff is a challenge in geriatric care. To address this, robots can be integrated into care settings to provide assistance and emotional support. A promising application is walking guidance, particularly benefiting older adults as navigation skills deteriorate with aging. As walking guidance involves direct contact, the aim of this study is to understand how older adults perceive and respond to different touch modes during guided walking. 24 older adults (68 - 88 yrs.) walked four times a ten-meter trajectory guided by the robot TIAGo Pro in four contact conditions: no physical contact (NC); physical contact through holding the robot's wrist with the hand (HH); physical interaction through linking arms with the robot (LA); and physical contact through resting the forearm on the robots forearm (FC). A multimodal assessment approach included electrocardiogram, electrodermal activity, contact force, distance to robot, and questionnaires. Physiological results reveal a slight increase in stress levels during robot interaction. Behavioural and subjective measures, however, show overall acceptance of robotic touch. The two conditions corresponding to larger interaction forces (HH and FC) were associated with lower relative distances between participant and robot, indicating a higher trust and confidence. Questionnaire responses supported these findings, evidencing greater perceived safety, trust and comfort in these conditions. This study provides insights for the design of robotic walking guidance assistance, indicating that gentle, stable touch is preferred by older adults in comparison to contactless interaction.

Addressing the global caregiver shortage through socially assistive robots necessitates a deep understanding of their psychological and physiological impacts on older adults. This study addresses whether social robots can serve as effective interaction partners compared to humans, and if "positive prompts" can similarly enhance these interactions. We conducted a comparative study with 35 participants (aged 70+) to evaluate responses during both human-human and human-robot encounters, including an assessment of "positive prompts" for cognitive reappraisal. Our multi-modal analysis, integrating facial expression data, heart rate variability, and subjective questionnaires, revealed no significant differences in overall stress levels between human and robot interactions. Facial expression analysis confirmed that the robot was accepted as a valid interaction partner, while physiological data showed slightly lower heart rates during robot interactions, suggesting a more relaxed state compared to human-led sessions. These findings indicate that social robots can engage older adults without inducing psychological strain and are capable of alleviating caregiver burden by performing structured tasks, such as health-sensing surveys. Future work should address the identified "appearance-content mismatch" in robot design to facilitate even more natural and effective interactions.

The nasopharyngeal (NP) swab test is a method for collecting cultures to diagnose for different types of respiratory illnesses, including COVID-19. Delegating this task to robots would be beneficial in terms of reducing infection risks and bolstering the healthcare system, but a critical component of the NP swab test is having the swab aligned properly with the nasal cavity so that it does not cause excessive discomfort or injury by traveling down the wrong passage. Existing research towards robotic NP swabbing typically assumes the patient’s head is held within a fixture. This simplifies the alignment problem, but is also dissimilar to clinical scenarios where patients are typically free-standing. Consequently, our work creates a vision-guided pipeline to allow an instrumented robot arm to properly position and orient NP swabs with respect to the nostrils of free-standing patients. The first component of the pipeline is a precomputed joint lookup table to allow the arm to meet the patient’s arbitrary position in the designated workspace, while avoiding joint limits. Our pipeline leverages semantic face models from computer vision to estimate the Euclidean pose of the face with respect to a monocular RGB-D camera placed on the end-effector. These estimates are passed into an unscented Kalman filter on manifolds state estimator and a pose based visual servo control loop to move the swab to the designated pose in front of the nostril. Our pipeline was validated with human trials, featuring a cohort of 25 participants. The system is effective, reaching the nostril for 84% of participants, and our statistical analysis did not find significant demographic biases within the cohort.

With rapid advancements in lower-limb exoskeleton hardware, two key challenges persist: the accurate assessment of user biomechanics and the reliable control of device behavior in real-world settings. This study presents a modular, sensor-based system designed to enhance both biomechanical evaluation and control of lower-limb exoskeletons, leveraging advanced sensor technologies and fuzzy logic. The system addresses the limitations of traditional lab-bound, high-cost methods by integrating inertial measurement units, force-sensitive resistors, and load cells into instrumented crutches and 3D-printed insoles. These components work independently or in unison to capture critical biomechanical metrics, including the anteroposterior center of pressure and crutch ground reaction forces. Data are processed in real time by a central unit using fuzzy logic algorithms to estimate gait phases and support exoskeleton control. Validation experiments with three participants, benchmarked against motion capture and force plate systems, demonstrate the system’s ability to reliably detect gait phases and accurately measure biomechanical parameters. By offering an open-source, cost-effective design, this work contributes to the advancement of wearable robotics and promotes broader innovation and accessibility in exoskeleton research.

When using lower limb exoskeletons, the human body naturally adopts neuromotor learning to adapt to the newly introduced conditions and interactions. However, due to the limited comprehension of human adaptation processes and strategies, defining the methodologies and metrics for identifying when and how the adaptation occurred remains a challenge. This study aims to investigate the human adaptation behaviour during exoskeleton use from the biomechanics perspective. Rather than focusing only on the statistical inferences of the general population, discrete analyses of individual participants are carried out to capture different adaptation strategies. The preliminary results indicated potential human-exoskeleton adaptation features exhibited by the converged increase of plantar flexion angle upon exoskeleton use. On the contrary, the three participants displayed unique response patterns in metabolic cost, suggesting that generally defining adaptation with only metabolic cost information may potentially be erroneous.

IntroductionControlling a powered lower-limb exoskeleton may increase the demand for cognitive resources due to mechanical constraints and assisting torques that disrupt natural movement.MethodThis study employed a dual-task paradigm to investigate cognitive-motor interferences and short-term familiarization effects in an outdoor walking experiment with twenty healthy adults using a powered lower-limb exoskeleton.Results and discussionIn contrast to unassisted walking, performing a serial subtraction task during exoskeleton-assisted walking led to a slight increase in gait velocity and a reduction in stride time variability. This suggests that externalizing attention may facilitate the coordination with external rhythmic cues provided by the exoskeleton. Concurrently, cognitive performance, measured by correct response rates, declined during exoskeleton-assisted walking, indicating a posture-first strategy. Short-term familiarization during exoskeleton-assisted walking reduced perceived workload and improved cognitive performance, yet cognitive performance remained lower than in both the seated control condition and unassisted walking. This suggests that walking with the exoskeleton continues to require significant attentional resources. These findings emphasize the necessity of evaluating the cognitive fit of exoskeletons to ensure safe human-exoskeleton interaction.

Background and ObjectivesAging suits are widely used as arguably didactic tool to foster understanding for age-related challenges in healthcare training by mimicking physical impairments associated with aging. However, effects on functional levels are ambiguous and necessitating validation of their potential to simulate age-related walking impairments. We evaluated effects of wearing an aging suit on kinematic gait variables, in younger and middle-aged adults in different walking conditions. Available reference data were used to compare aging-suit induced effects to standard and dual-task walking in older adults.Research Design and MethodsWhole-body kinematics (sagittal ankle-, knee-, hip-angles, arm-swing, trunk-bend) and spatiotemporal parameters (walking speed, stride length, step width) were measured in 14 young (20-34 years) and 15 middle-aged adults (40-63 years). SPM analysis and mixed ANOVA were conducted to evaluate the effects of the suit, age-group and their interaction.ResultsOverall, wearing the aging suit changed gait patterns, but kinematic parameters were hardly affected in both groups. During standard walking, arm-swing decreased by 17%, walking speed by 9%, and step width increased by 15% across both groups. Compared to reference data, changes in arm-swing corresponded to an instant aging effect of 45-55 years in young and 15-25 years in middle-aged adults.Discussion and ImplicationsThe aging suit changed gait patterns considerably making both groups walk more cautiously compared to reference values of older adults. However, performance deficits seen in individuals 80+ years were clearly not attained. Caution is advised when using aging suits as an educational tool to simulate age-related walking impairments.

Difficulties in standing up and sitting down can greatly impact the quality of life of older adults. Robotic rollators equipped with moving handles can provide support to prolong the ability to live independently. However, appropriate trajectories are still unknown while the corresponding human-machine interaction dynamics are poorly understood. This study proposes bio-inspired, easy-to-implement assistance trajectories and investigates their biomechanical effects on standing-up and sitting-down motion in 15 young adults using moving handles of a robotic assistance device in a motion capture lab. The results show that moving-handles assistance can provide up to twice as much vertical support as fixed handles while potentially reducing lower and upper limb muscle demands, and reducing the destabilizing effect of horizontal forces on the handles. Furthermore, participants' perception of provided help correlates well with the magnitude of the vertical force support. The study's subsequent phase comprises the ongoing evaluation with frail older adults.

The nasopharyngeal (NP) swab sample test, commonly used to detect COVID-19 and other respiratory illnesses, involves moving a swab through the nasal cavity to collect samples from the nasopharynx. While typically this is done by human healthcare workers, there is a significant societal interest to enable robots to do this test to reduce exposure to patients and to free up human resources. The task is challenging from the robotics perspective because of the dexterity and safety requirements. While other works have implemented specific hardware solutions, our research differentiates itself by using a ubiquitous rigid robotic arm. This work presents a case study where we investigate the strengths and challenges using compliant control system to accomplish NP swab tests with such a robotic configuration. To accomplish this, we designed a force sensing end-effector that integrates with the proposed torque controlled compliant control loop. We then conducted experiments where the robot inserted NP swabs into a 3D printed nasal cavity phantom. Ultimately, we found that the compliant control system outperformed a basic position controller and shows promise for human use. However, further efforts are needed to ensure the initial alignment with the nostril and to address head motion.

Falls occur more often as we age. To identify people at risk of falling, balance analysis requires an accurate base-of-support model. We previously developed a functional base-of-support (fBOS) model for standing young adults and showed that its area is smaller than the footprint area. Our fBOS model is a polygon that contains centre-of-pressure (COP) trajectories recorded as standing participants move their COP in the largest possible loop while keeping their feet flat on the ground. Here we assess how the size of the fBOS changes with age by comparing 38 younger (YA), 14 middle-aged (MA), and 34 older adults (OA). The fBOS area is smaller in older adults: OA area is 58% of the YA area ([Formula: see text]), and 59% of the MA area ([Formula: see text]), with no difference between YA and MA. The reduction in fBOS area among the OA is primarily caused by a reduction in the length of the fBOS. In addition, among older adults smaller fBOS areas correlated with a lower score on the Short Physical Performance Battery (τ=0.28, [Formula: see text]), a reduced walking speed (τ=0.25, [Formula: see text]), and a higher frailty level ([Formula: see text]). So that others can extend our work, we have made our fBOS models available online.

The coupling interface on wearable lower limb exoskeletons influence physical human-robot interactions (pHRI) that occur during assistance in gait and posture tasks. Despite their increasing popularity, risks to the user (i.e., skin, musculoskeletal injuries) from undesirable interactions at the interface are present. Current research examining coupling interactions, focuses on characterizing simple pressure measures (i.e., mean) independent of interface features. Consequently, design guidelines of ideal coupling interface interactions do not yet exist due to a lack of common framework and metrics tied to interface features for analysis. Other wearable devices (e.g. prostheses), use custom fit interfaces as a baseline for interface design. In this study we compare custom made single-user and generic multi-user interfaces using established and novel pressure-related measures. 5 minute overground gait trials were conducted with pressure sensors placed at the hip and thigh interfaces. Pilot study results showed increased supporting contact area at the measured surfaces and a reduction in relative movement during use of custom-fit interfaces. Average and peak pressure varied between sites, with custom thigh interfaces exhibiting notable improved performance. Pressure measures reported highlight the benefit of custom interfaces, and the value of additional pressure analysis metrics in differentiating interface designs and evaluating relative performance. We propose that custom fit interfaces can provide a common baseline for evaluating coupling interface pHRI, supported by novel methods of pressure analysis to tie pHRI improvements to specific interface design characteristics.

Falls pose a serious threat to older adults’ independence and well-being, with sit-to-stand (STS) transition frequently associated with fall incidents. To address this challenge, we propose a real-time fall detection integrated into a mobile assistive robot SkyWalker. Our approach utilizes a depth camera with onboard processing capabilities positioned at close proximity (approximately 0.5 m). A 3D skeletal model derived from MediaPipe tracks the user’s motion in real-time, extracting 14 key kinematic features that capture biomechanical information. These features serve as input to a dual-modular classification framework based on support vector machines (SVMs): one classifier predicts STS phases (sitting, rising, switching, standing). while the other identifies irregular motions indicative of falls. By focusing on this reduced yet discriminative feature set, our system remains both computationally efficient and robust to skeleton distortions often encountered at close range. We evaluated our approach using separate datasets for phase classification and fall detection, achieving high accuracy in real-time classification. Future work will extend the system to enable proactive fall prevention strategies, ensuring safer STS transitions for older adults.

Current research on physical human-robot interactions (pHRI) in wearable assistive robots, such as lower-limb exoskeletons, primarily focuses on improving net force estimates at each interface to improve robot controller performance. Consequently, estimating force distribution along physical interfaces of wearable robots, crucial for user safety and comfort, has been largely overlooked. We propose a novel computational model that uses interface geometry and strapping tension as inputs, and predicts the static pressure field generated during the user donning process by treating the supporting surface as an elastic foundation. Accuracy of the proposed computational method was validated by comparing the estimated static pressure field of a commercially available interface to experimental data. While measured pressure magnitudes were significantly lower than model prediction, likely due to a combination of assumptions and limitations associated with model design, similar loading patterns were observed. Identifying regions of high pressure from simulation and similar patterns allow for reliable scaling to reduce inaccuracies, and may be used to inform design. Further refinements of the proposed model will provide a valuable tool for developing more comfortable and safer interfaces for wearable robots.

With increasing age, motor performance declines. This decline is associated with less favorable health outcomes such as impaired activities of daily living, reduced quality of life, or increased mortality. Through regular assessment of motor performance, changes over time can be monitored, and targeted therapeutic programs and interventions may be informed. This can ensure better individualization of any intervention approach (e.g. by considering the current motor performance status of a person) and thus potentially increase its effectiveness with regard to maintaining current performance status or delaying further decline. However, in older adults, motor performance assessment is time consuming and requires experienced examiners and specific equipment, amongst others. This is particularly not feasible in care facility/nursing home settings. Wearable robotic devices, such as exoskeletons, have the potential of being used to assess motor performance and provide assistance during physical activities and exercise training for older adults or individuals with mobility impairments, thereby potentially enhancing motor performance. In this manuscript, we aim to (1) provide a brief overview of age-related changes of motor performance, (2) summarize established clinical and laboratory test procedures for the assessment of motor performance, (3) discuss the possibilities of translating established test procedures into exoskeleton-based procedures, and (4) highlight the feasibility, technological requirements and prerequisites for the assessment of human motor performance using lower limb exoskeletons.