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Wearable robots are often powered by elastic actuators, which can mimic the intrinsic compliance observed in human joints, contributing to safe and seamless interaction. However, due to their increased complexity, when compared to direct drives, elastic actuators are susceptible to faults, which pose significant challenges, potentially compromising user experience and safety during interaction. In this article, we developed a fault-tolerant control strategy for torque assistance in a knee exoskeleton and investigated user experience during a walking task while emulating faults. We implemented and evaluated the torque control scheme, based on impedance control, for a mechanically adjustable compliance actuator with nonlinear torque-deflection characteristics. Conducted functional evaluation experiments showed that the control strategy is capable of providing support during gait based on a torque profile. A user study was conducted to evaluate the impact of fault severity and compensation on the perception of support, stiffness, comfort, and trust while walking with the exoskeleton. Results from the user study revealed significant differences in participants' responses when comparing support and stiffness levels without fault compensation. In contrast, no significant differences were found when faults were compensated, indicating that fault tolerance can be achieved in practice. Meanwhile, comfort and trust measurements do not seem to depend directly on torque support levels, pointing to other influencing factors that could be considered in future research. [ABSTRACT FROM AUTHOR]

Climbing stairs is relatively challenging for seniors, post-stroke individuals or even healthy young men when carrying heavy objects. In this paper, we have developed a rigid-soft hybrid exosuit that helps the wearer to climb the stairs by offering a driving torque to the knee joint. By combining the advantage of rigid and soft exoskeletons, the exosuit is more comfortable when assisting wearers at a high level of assistance. To simplify the detection system, but keep it versatile, only the surface electromyography sensor is used to detect human movement. This paper uses a hierarchical control strategy based on gait detection and force tracking. To verify the capability of this exosuit system, we conducted experiments with four healthy users walking upstairs in different levels of assistance and climbing speeds. By comparing the muscle activity of participants with exosuit and without exosuit, the vastus lateralis activity was reduced by 3% to 15%, depending on the subject. This research shows the assisting capability of this exosuit under different assistance levels and climbing speeds. [ABSTRACT FROM AUTHOR]

Energy‐efficient yet energy‐dense soft actuators are essential for untethered wearable robots. This work reports a fabric‐like actuator, combining shape memory alloy (SMA) springs and electrostatic clutches (ESClutches). The SMA springs provide high force density, with only 18 g of materials generating 40 N of force at actuation strains of over 35%, but requiring 78 W of power to hold that strain. The ESClutches cannot generate motion on their own, but can maintain the force and contraction generated by SMAs consuming only a few mW, thus allowing the SMAs to be turned off. By combining SMAs and ESClutches, a soft wearable fabric actuator is developed with force and stroke suited for an upper‐limb soft exoskeleton, able to lock in any given position using negligible power. The design is scalable: the number and dimensions of the SMA springs and of the ESClutches can be chosen to meet size and actuator performance requirements. This work reports two wearable use cases, where the combined SMAs and ESClutches consume over 70% lower power than SMAs alone. [ABSTRACT FROM AUTHOR]

Soft wearable robotic devices have emerged as a promising solution for human mobility assistance and rehabilitation, yet current solutions suffer from issues such as bulkiness, high cost, nonscalability, noise, and limited portability. This study introduces a novel approach to soft robotic assistive devices using untethered, soft actuators with seamlessly integrated sensing, heating, and actuation properties through digital machine knitting and low‐boiling liquid. The proposed soft actuator operates under a voltage of less than 12.5 V, generating a tip force of up to 50 mN. This actuator achieves a bending motion when filled with 2 mL of low‐boiling liquid and supplied with 15 W. The dynamic response of the actuator is examined under consistent parameters, revealing a 60‐second inflation time and a subsequent natural cooling period of 30 s at room temperature. Notably, over 12 cycles, the tip force of the actuator exhibits minimal variation, highlighting its durability for prolonged usage. The proposed approach paves the way for overcoming the limitations of existing technologies, particularly in terms of motion assistance and rehabilitation applications, with an emphasis on at‐home usage during daily activities. [ABSTRACT FROM AUTHOR]

Spinal cord injuries (SCI) substantially affect sensory, motor, and autonomous functions below the level of injury, reducing the independence and quality of life for affected individuals. Specifically, people with SCI between C5 and C7 cervical levels encounter limitations in voluntary finger and wrist flexion, reducing grasp capability. Compensatory strategies like tenodesis grasp, whereby wrist extension passively closes the fingers, remain; this is effective for small and light objects but insufficient for heavier ones. Typically, wearable assistive exoskeletons are designed to actuate a person’s fingers, however, such devices are sensitive to anatomical variability, such as hand size and joint contractures. The Dorsal Grasper is a wearable device designed to address this challenge by leveraging voluntary wrist extension and providing human-robot collaborative grasping capabilities with underactuated supernumerary fingers on the back of the hand. In this study, we introduce kinematic assessment methods that we use to show how the Dorsal Grasper expands the graspable workspace and reduces trunk motion, especially in situations where the use of a wheelchair restricts the individual’s posture. Our functionally relevant experiments with multiple SCI participants demonstrate the Dorsal Grasper’s potential as a versatile assistive solution for enhancing grasping capability in individuals with distinct SCI profiles.

Current hand exoskeleton systems for assistive and rehabilitative purposes pose challenges due to weight, bulk, and size, thus negatively affecting user experience in terms of comfort and wearability. End-user involvement is vital during design and deployment to improve usefulness, usability, and user acceptance. A scoping review was conducted to identify the currently prioritized user requirements and user-centered practices in the development of hand exoskeleton systems. Content analysis was used to identify the user-centered design criteria and user research methodologies in 124 articles. More studies aim for rehabilitation than assistance and the dominant form of assessment is system validation. Wearability, comfort, portability, adaptability, affordability, and safety were the most frequently targeted user-centered criteria. Only 38 articles reported assessment with human subjects, the majority of them being functional tests, followed by usability tests. We offer user-centered design directions and methodological suggestions for user involvement to improve the usability and acceptability of the exoskeleton systems, and discuss the necessity for restructuring the engineering design strategy for better adaptability. This research has direct applications for the design and assessment of assistive and rehabilitative hand exoskeletons by offering user requirements. The findings and suggestions can have wider implications in the field of wearable robotics for developing, evaluating, and refining systems through a user-centered perspective. [ABSTRACT FROM AUTHOR]

Exoskeletons are technologies that can help to increase or improve mobility, dexterity, and strength. They can be used as assistive devices, to restore lost affordances, or for rehabilitation. While mechanical exoskeletons are passive and rely on the body's power for movement, powered exoskeletons are active mechanical systems that can assist or enhance a user's capacity, including in strength and performance. They also offer scope to augment or enhance beyond simple medical support, with potential in the future for superhuman power and strength. While these technologies present promising clinical opportunities, including for those who want to regain walking capacity, they also bring ethical questions, such as about data privacy and accessibility. In addition, the physical features of the technology can prove mentally, physically, and financially demanding, and may be deployed in contexts where user choice and autonomy is constrained. In this article, we discuss these issues, and raise some pertinent ethical questions, not all of which can be easily answered. We touch upon medical and therapeutic uses, for industrial and workplace settings, and in military contexts specially, given these are contexts where such technology may be required or even imposed. We argue that reasonable optimism for such technologies needs to be tempered by sufficient ethical assessment to identify and address barriers to research, development, and use. As well as managing any impacts and expectations for the health and wellbeing of users, the potential impact on autonomy and the risk of coercion, we have to consider what kind of data may be recorded or used, and the risk that these technologies could exacerbate existing inequalities or harms. [ABSTRACT FROM AUTHOR]

Using lower limb exoskeletons provides potential advantages in terms of productivity and safety associated with reduced stress. However, complex issues in human–robot interactions are still open, such as the physiological effects of exoskeletons and the impact on the user's subjective experience. In this work, an innovative exoskeleton, the Wearable Walker, is assessed using the EXPERIENCE benchmarking protocol from the EUROBENCH project. The Wearable Walker is a lower-limb exoskeleton that enhances human abilities, such as carrying loads. The device uses a unique control approach called Blend Control that provides smooth assistance torques. It operates two models simultaneously, one in the case in which the left foot is grounded and another for the grounded right foot. These models generate assistive torques combined to provide continuous and smooth overall assistance, preventing any abrupt changes in torque due to model switching. The EXPERIENCE protocol consists of walking on flat ground while gathering physiological signals, such as heart rate, its variability, respiration rate, and galvanic skin response, and completing a questionnaire. The test was performed with five healthy subjects. The scope of the present study is twofold: to evaluate the specific exoskeleton and its current control system to gain insight into possible improvements and to present a case study for a formal and replicable benchmarking of wearable robots. [ABSTRACT FROM AUTHOR]

Accurately identifying user needs in terms of assist timing and magnitude presents challenges for wearable power‐assist limb devices. Traditional approaches to gait perception—such as estimating joint angles and walking conditions—often rely on electronic sensors and neural networks, which can compromise wearability and impose high computational demands. Physical reservoir computing (PRC), which utilizes the inherent nonlinearity of physical systems for data processing, offers a promising alternative. This study proposes a novel self‐estimated physical reservoir computing (SEPRC) model that improves traditional PRC models for gait perception using a wearable pneumatic physical reservoir. A core feature of the new model is the self‐estimation structure, wherein the outputs of the physical reservoir are mutually estimated. Experimental evaluations indicate that the SEPRC model outperforms traditional PRC in clustering time‐series reservoir output sequences with the same dimensionality. This enhanced clustering performance is subsequently leveraged in gait perception by incorporating Takagi–Sugeno fuzzy logic for joint angle estimation and a softmax activation function for walking condition recognition. The newly proposed time‐sequence processing approach facilitates the traditional PRC model to achieve higher accuracy in gait perception and greater robustness against the user's walking pattern variations while preserving PRC's hardware simplicity.

Cycling stands as one of the most widely embraced leisure activities and serves purposes such as exercise, rehabilitation, and commuting. This study aimed to assess the feasibility of assisting three unimpaired participants (age: 34.0 ± 7.9 years, height: 1.86 ± 0.02 m, weight: 75.7 ± 12.7 kg) using the GuroX hip exoskeleton, originally designed for walking assistance, during cycling against a resistance of 1 W/kg. The performance evaluation employed a sweep protocol that manipulated the timing of the exoskeleton's peak extension and flexion torque in addition to human-in-the-loop optimization to enhance these timings based on metabolic cost. Our findings indicate that with a peak assistance torque of approximately 10.3 Nm for extension and flexion, the GuroX substantially reduced the net metabolic cost of cycling by 31.4 ± 8.1% and 26.4 ± 14.1% compared to transparent and without exoskeleton conditions, respectively. This demonstrates the significant potential of a hip exoskeleton developed for walking assistance to profoundly benefit cycling. Additionally, customizing the assistance strategy proves beneficial in maximizing assistance. While we attribute the average motor power to be a major contributor to the reduced cycling effort, participant feedback suggests that user comfort and synchronization between the user and exoskeleton may have played integral roles. Further research should validate our initial findings by employing a larger participant pool in real-world conditions. Incorporating a more diverse set of parameters for the human-in-the-loop optimization could enhance individualized assistance strategies. [ABSTRACT FROM AUTHOR]

Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating impedance based on the user's movement direction and nonlinear sine curves. The objective of this study was to compare active assistance, delivered by a back exosuit via our adaptive impedance controller, to three levels of assistance from passive elastics. Fifteen participants completed five experimental blocks (4 exosuits and 1 no-suit) consisting of a maximum flexion and a constrained lifting task. While a higher stiffness elastic reduced back extensor muscle activity by 13%, it restricted maximum range of motion (RoM) by 13°. The adaptive impedance approach did not restrict RoM while reducing back extensor muscle activity by 15%, when lifting. This study highlights an adaptive impedance approach might improve usability by circumventing the assistance-restriction trade-off inherent to passive approaches. Practitioner summary: This study demonstrates a soft active exosuit that delivers assistance with an adaptive impedance approach can provide reductions in overall back muscle activity without the impacts of restricted range of motion or perception of restriction and discomfort. [ABSTRACT FROM AUTHOR]

Abstract Human–robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning models for visual perception of real-world stair environments. In this study, we present a comprehensive overview of the StairNet initiative and key research to date. First, we summarize the development of our large-scale data set with over 515,000 manually labeled images. We then provide a summary and detailed comparison of the performances achieved with different algorithms (i.e., 2D and 3D CNN, hybrid CNN and LSTM, and ViT networks), training methods (i.e., supervised learning with and without temporal data, and semi-supervised learning with unlabeled images), and deployment methods (i.e., mobile and embedded computing), using the StairNet data set. Finally, we discuss the challenges and future directions. To date, our StairNet models have consistently achieved high classification accuracy (i.e., up to 98.8%) with different designs, offering trade-offs between model accuracy and size. When deployed on mobile devices with GPU and NPU accelerators, our deep learning models achieved inference speeds up to 2.8 ms. In comparison, when deployed on our custom-designed CPU-powered smart glasses, our models yielded slower inference speeds of 1.5 s, presenting a trade-off between human-centered design and performance. Overall, the results of numerous experiments presented herein provide consistent evidence that StairNet can be an effective platform to develop and study new deep learning models for visual perception of human–robot walking environments, with an emphasis on stair recognition. This research aims to support the development of next-generation vision-based control systems for robotic prosthetic legs, exoskeletons, and other mobility assistive technologies.

In this perspective paper, we explore the use of haptic feedback to enhance human-human interaction during musical tasks. We start by providing an overview of the theoretical foundation that underpins our approach, which is rooted in the embodied music cognition framework, and by briefly presenting the concepts of action-perception loop, sensorimotor coupling and entrainment. Thereafter, we focus on the role of haptic information in music playing and we discuss the use of wearable technologies, namely lightweight exoskeletons, for the exchange of haptic information between humans. We present two experimental scenarios in which the effectiveness of this technology for enhancing musical interaction and learning might be validated. Finally, we briefly discuss some of the theoretical and pedagogical implications of the use of technologies for haptic communication in musical contexts, while also addressing the potential barriers to the widespread adoption of exoskeletons in such contexts. [ABSTRACT FROM AUTHOR]

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer's upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19–30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions. [ABSTRACT FROM AUTHOR]

Human–robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning models for visual perception of real-world stair environments. In this study, we present a comprehensive overview of the StairNet initiative and key research to date. First, we summarize the development of our large-scale data set with over 515,000 manually labeled images. We then provide a summary and detailed comparison of the performances achieved with different algorithms (i.e., 2D and 3D CNN, hybrid CNN and LSTM, and ViT networks), training methods (i.e., supervised learning with and without temporal data, and semi-supervised learning with unlabeled images), and deployment methods (i.e., mobile and embedded computing), using the StairNet data set. Finally, we discuss the challenges and future directions. To date, our StairNet models have consistently achieved high classification accuracy (i.e., up to 98.8%) with different designs, offering trade-offs between model accuracy and size. When deployed on mobile devices with GPU and NPU accelerators, our deep learning models achieved inference speeds up to 2.8 ms. In comparison, when deployed on our custom-designed CPU-powered smart glasses, our models yielded slower inference speeds of 1.5 s, presenting a trade-off between human-centered design and performance. Overall, the results of numerous experiments presented herein provide consistent evidence that StairNet can be an effective platform to develop and study new deep learning models for visual perception of human–robot walking environments, with an emphasis on stair recognition. This research aims to support the development of next-generation vision-based control systems for robotic prosthetic legs, exoskeletons, and other mobility assistive technologies. [ABSTRACT FROM AUTHOR]

Wearable robots are envisioned to amplify the independence of people with movement impairments by providing daily physical assistance. For portable, comfortable, and safe devices, soft pneumatic-based robots are emerging as a potential solution. However, due to the inherent complexities, including compliance and nonlinear mechanical behavior, feedback control for facilitating human-robot interaction remains a challenge. Herein, we present the design, fabrication, and control architecture of a soft wearable robot that assists in supination and pronation of the forearm. The soft wearable robot integrates an antagonistic pair of pneumatic-based helical actuators to provide active pronation and supination torques. Our main contribution is a bio-inspired equilibrium-point control scheme for integrating proprioceptive feedback and exteroceptive input (e.g., the user's muscle activation signals) directly with the on/off valve behavior of the soft pneumatic actuators. The proposed human-robot controller is directly inspired by the equilibrium-point hypothesis of motor control, which suggests that voluntary movements arise through shifts in the equilibrium state of the antagonistic muscle pair spanning a joint. We hypothesized that the proposed method would reduce the required effort during dynamic manipulation without affecting the error. In order to evaluate our proposed method, we recruited seven pediatric participants with movement disorders to perform two dynamic interaction tasks with a haptic manipulandum. Each task required the participant to track a sinusoidal trajectory while the haptic manipulandum behaved as a Spring-Dominate system or Inertia-Dominate system. Our results reveal that the soft wearable robot, when active, reduced user effort on average by 14%. This work demonstrates the practical implementation of an equilibrium-point volitional controller for wearable robots and provides a foundational path toward versatile, low-cost, and soft wearable robots.

Abstract Background Active upper extremity (UE) assistive devices have the potential to restore independent functional movement in individuals with UE impairment due to neuromuscular diseases or injury-induced chronic weakness. Academically fabricated UE assistive devices are not usually optimized for activities of daily living (ADLs), whereas commercially available alternatives tend to lack flexibility in control and activation methods. Both options are typically difficult to don and doff and may be uncomfortable for extensive daily use due to their lack of personalization. To overcome these limitations, we have designed, developed, and clinically evaluated the NuroSleeve, an innovative user-centered UE hybrid orthosis. Methods This study introduces the design, implementation, and clinical evaluation of the NuroSleeve, a user-centered hybrid device that incorporates a lightweight, easy to don and doff 3D-printed motorized UE orthosis and a functional electrical stimulation (FES) component. Our primary goals are to develop a customized hybrid device that individuals with UE neuromuscular impairment can use to perform ADLs and to evaluate the benefits of incorporating the device into occupational therapy sessions. The trial is designed as a prospective, open-label, single-cohort feasibility study of eight-week sessions combined with at-home use of the device and implements an iterative device design process where feedback from participants and therapists informs design improvement cycles. Results All participants learned how to independently don, doff, and use the NuroSleeve in ADLs, both in clinical therapy and in their home environments. All participants showed improvements in their Canadian Occupational Performance Measure (COPM), which was the primary clinical trial outcome measure. Furthermore, participants and therapists provided valuable feedback to guide further development. Conclusions Our results from non-clinical testing and clinical evaluation demonstrate that the NuroSleeve has met feasibility and safety goals and effectively improved independent voluntary function during ADLs. The study’s encouraging preliminary findings indicate that the NuroSleeve has met its technical and clinical objectives while improving upon the limitations of the existing UE orthoses owing to its personalized and flexible approach to hardware and firmware design. Trial Registration: ClinicalTrials.gov identifier: NCT04798378, https://clinicaltrials.gov/ct2/show/NCT04798378 , date of registration: March 15, 2021.

With the global geriatric population expected to reach 1.5 billion by 2050, different assistive technologies have been developed to tackle age-associated movement impairments. Lower-limb robotic exoskeletons have the potential to support frail older adults while promoting activities of daily living, but the need for crutches may be challenging for this population. Crutches aid safety and stability, but moving in an exoskeleton with them can be unnatural to human movements, and coordination can be difficult. Frail older adults may not have the sufficient arm strength to use them, or prolonged usage can lead to upper limb joint deterioration. The research presented in this paper makes a contribution to a more detailed study of crutch-less exoskeleton use, analyzing in particular the most challenging motion, sit-to-stand (STS). It combines motion capture and optimal control approaches to evaluate and compare the STS dynamics with the TWIN exoskeleton with and without crutches. The results show trajectories that are significantly faster than the exoskeleton's default trajectory, and identify the motor torques needed for full and partial STS assistance. With the TWIN exoskeleton's existing motors being able to support 112 Nm (hips) and 88 Nm (knees) total, assuming an ideal contribution from the device and user, the older adult would need to contribute a total of 8 Nm (hips) and 50 Nm (knees). For TWIN to provide full STS assistance, it would require new motors that can exert at least 121 Nm (hips) and 140 Nm (knees) total. The presented optimal control approaches can be replicated on other exoskeletons to determine the torques required with their mass distributions. Future improvements are discussed and the results presented lay groundwork for eliminating crutches when moving with an exoskeleton.

In this perspective paper, we explore the use of haptic feedback to enhance human-human interaction during musical tasks. We start by providing an overview of the theoretical foundation that underpins our approach, which is rooted in the embodied music cognition framework, and by briefly presenting the concepts of action-perception loop, sensorimotor coupling and entrainment. Thereafter, we focus on the role of haptic information in music playing and we discuss the use of wearable technologies, namely lightweight exoskeletons, for the exchange of haptic information between humans. We present two experimental scenarios in which the effectiveness of this technology for enhancing musical interaction and learning might be validated. Finally, we briefly discuss some of the theoretical and pedagogical implications of the use of technologies for haptic communication in musical contexts, while also addressing the potential barriers to the widespread adoption of exoskeletons in such contexts.

Rehabilitation of the upper and lower limbs is crucial for patients recovering from strokes, surgeries, or injuries. Traditional rehabilitation often takes place in hospitals under the guidance of a therapist, which can delay treatment due to various constraints. This paper proposes a soft robotic device designed to aid in the flexion and extension of both the elbow and knee. The device utilizes pneumatic artificial muscles, constructed from an elastomeric bladder with a threaded mesh exterior, as its actuating mechanism. It operates in two distinct modes: a continuous passive mode, where continuous, repetitive flexion, and extension of limbs are carried out, and an active intent-based assisted mode, which detects a patient's movement intention via surface electromyography (sEMG) and subsequently aids in the movement execution. To test the effectiveness of the device, sEMG electrodes were placed on upper and lower limbs of six healthy male subjects, range of motion, and muscle activity were recorded with and without the device. Also NASA task load index (NASA-TLX) was calculated for the usability of the device. The results indicate the required muscle activity and range of motions for both upper and lower limb rehabilitation are effectively generated in both the modes. [ABSTRACT FROM AUTHOR]

Pneumatic soft actuators have been widely considered the safest actuation technology for use in wearable rehabilitation robots. For soft robotic gloves, researchers commonly put soft extending or bending actuators on dorsal fingers to assist hand flexion. In this research, we propose a novel pre-folded flat tube actuator (PFTA) to assist finger flex into a pre-set bending angle or contact force. The PFTA has three folds, aligned with each of the finger joint. Different from other soft actuators, the PFTA exerts bending torque directly on each finger joint without large actuator deformation. The PFTA made of heat shrink flat tube has a small profile, with low cost, easy fabrication, and high safety. When actuated, the PFTA has the tendency to unfold as well, we call this effect as unfolding flat tube actuation. This effect is characterized by a range of bending angles and input air pressures in which four distinct response regimes were observed. They are defined as shearing, collapsing, creasing, and flattening regimes. Similarly, experimental characterization of PFTAs is also conducted to evaluate the level of joint flexion assistance based on which design guidelines for robotic gloves are recommended. Finally, we build PFTAs on a soft wearable glove and demonstrate their capability in assisting the grasping operations of various object shapes. [ABSTRACT FROM AUTHOR]

Falling is a major cause of morbidity, and is often caused by a decrease in postural stability. A key component of postural stability is whole-body centroidal angular momentum, which can be influenced by control moment gyroscopes. In this proof-of-concept study, we explore the influence of our wearable robotic gyroscopic actuator "GyroPack" on the balance performance and gait characteristics of non-impaired individuals (seven female/eight male, 30 ± 7 years, 68.8 ± 8.4 kg). Participants performed a series of balance and walking tasks with and without wearing the GyroPack. The device displayed various control modes, which were hypothesised to positively, negatively, or neutrally impact postural control. When configured as a damper, the GyroPack increased mediolateral standing time and walking distance, on a balance beam, and decreased trunk angular velocity variability, while walking on a treadmill. When configured as a negative damper, both peak trunk angular rate and trunk angular velocity variability increased during treadmill walking. This exploratory study shows that gyroscopic actuators can influence balance and gait kinematics. Our results mirror the findings of our earlier studies; though, with more than 50% mass reduction of the device, practical and clinical applicability now appears within reach. [ABSTRACT FROM AUTHOR]

Abstract Background After above-knee amputation, the missing biological knee and ankle are replaced with passive prosthetic devices. Passive prostheses are able to dissipate limited amounts of energy using resistive damper systems during “negative energy” tasks like sit-down. However, passive prosthetic knees are not able to provide high levels of resistance at the end of the sit-down movement when the knee is flexed, and users need the most support. Consequently, users are forced to over-compensate with their upper body, residual hip, and intact leg, and/or sit down with a ballistic and uncontrolled movement. Powered prostheses have the potential to solve this problem. Powered prosthetic joints are controlled by motors, which can produce higher levels of resistance at a larger range of joint positions than passive damper systems. Therefore, powered prostheses have the potential to make sitting down more controlled and less difficult for above-knee amputees, improving their functional mobility. Methods Ten individuals with above-knee amputations sat down using their prescribed passive prosthesis and a research powered knee-ankle prosthesis. Subjects performed three sit-downs with each prosthesis while we recorded joint angles, forces, and muscle activity from the intact quadricep muscle. Our main outcome measures were weight-bearing symmetry and muscle effort of the intact quadricep muscle. We performed paired t-tests on these outcome measures to test for significant differences between passive and powered prostheses. Results We found that the average weight-bearing symmetry improved by 42.1% when subjects sat down with the powered prosthesis compared to their passive prostheses. This difference was significant (p = 0.0012), and every subject’s weight-bearing symmetry improved when using the powered prosthesis. Although the intact quadricep muscle contraction differed in shape, neither the integral nor the peak of the signal was significantly different between conditions (integral p > 0.01, peak p > 0.01). Conclusions In this study, we found that a powered knee-ankle prosthesis significantly improved weight-bearing symmetry during sit-down compared to passive prostheses. However, we did not observe a corresponding decrease in intact-limb muscle effort. These results indicate that powered prosthetic devices have the potential to improve balance during sit-down for individuals with above-knee amputation and provide insight for future development of powered prosthetics.

Telerehabilitation and robotics, either traditional rigid or soft, have been extensively studied and used to improve hand functionality after a stroke. However, a limited number of devices combined these two technologies to such a level of maturity that was possible to use them at the patients’ home, unsupervised. Here we present a novel investigation that demonstrates the feasibility of a system that integrates a soft inflatable robotic glove, a cloud-connected software interface, and a telerehabilitation therapy. Ten chronic moderate-to-severe stroke survivors independently used the system at their home for 4 weeks, following a software-led therapy and being in touch with occupational therapists. Data from the therapy, including automatic assessments by the robot, were available to the occupational therapists in real-time, thanks to the cloud-connected capability of the system. The participants used the system intensively (about five times more movements per session than the standard care) for a total of more than 8 hr of therapy on average. We were able to observe improvements in standard clinical metrics (FMA +3.9 ± 4.0, p

This work introduces a real-time intention decoding algorithm grounded in muscle synergies (Syn-ID). The algorithm detects the electromyographic (EMG) onset and infers the direction of the movement during reaching tasks to control a powered shoulder–elbow exoskeleton. Features related to muscle synergies are used in a Gaussian Mixture Model and probability accumulation-based logic to infer the user’s movement direction. The performance of the algorithm was verified by a feasibility study including eight healthy participants. The experiments comprised a transparent session, during which the exoskeleton did not provide any assistance, and an assistive session in which the Syn-ID strategy was employed. Participants were asked to reach eight targets equally spaced on a circumference of 25 cm radius (adjusted chance level: 18.1%). The results showed an average accuracy of 48.7% after 0.6 s from the EMG onset. Most of the confusion of the estimate was found along directions adjacent to the actual one (type 1 error: 33.4%). Effects of the assistance were observed in a statistically significant reduction in the activation of Posterior Deltoid and Triceps Brachii. The final positions of the movements during the assistive session were on average 1.42 cm far from the expected ones, both when the directions were estimated correctly and when type 1 errors occurred. Therefore, combining accurate estimates with type 1 errors, we computed a modified accuracy of 82.10±6.34%. Results were benchmarked with respect to a purely kinematics-based approach. The Syn-ID showed better performance in the first portion of the movement (0.14 s after EMG onset).

This document is an editorial titled "Augmenting human experience and performance through interaction technologies." It discusses the growing interest in enhancing human performance and capabilities through interdisciplinary research fields such as neuroengineering, neuroergonomics, and rehabilitation. The editorial focuses on the use of interaction technologies like Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) as transformative tools to enhance human potential. It also highlights various perspectives and studies on human augmentation, including the design of augmented systems, perception and user experience, and applications in urban planning, driving assistance, surgery, and artificial intelligence. The editorial concludes by emphasizing the importance of understanding the role of augmentation in human-machine systems and developing sustainable and integrated technologies to assist people. [Extracted from the article]

Technological advancements in the last two decades have enabled development of a variety of mechanically supporting wearable robots (i.e. exoskeletons) that are transitioning to practice in medical and industrial settings. The feedback from industry and recent controlled studies is highlighting thermal discomfort as a major reason for the disuse of the devices and a substantial barrier to their long-term adoption. Furthermore, a brief overview of the devices and their intended applications reveals that many of the potential users are likely to face thermal comfort issues because of either high exertion or medically related high heat sensitivity. The aim of this review is to discuss these emerging thermal challenges and opportunities surrounding wearable robots. This review discusses mechanisms, potential solutions, and a platform for systematically measuring heat transfer inhibition caused by wearing of an exoskeleton. Lastly, the potential for substantial metabolic rate reduction provided by exoskeletons to reduce worker thermal strain in warm-to-hot conditions is also considered. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a novel soft exosuit called inflatable assist clothing (InAC) with lightweight and flexible inflatable actuators (IfAs) and to propose a voluntary control method to control the IfA using electrical changes during muscle activity. The InAC is equipped with IfAs, which generate a contraction force by supplying compressed air from a DC vacuum pump with compressor function to assist with knee flexion and extension. In addition, our proposed control method, the bioelectrical signal (BES)-based control algorithm, estimates the desired air volume to be supplied by the DC pump to each individual IfA on the basis of the displacement volume of the BES and then performs feedback control to track the desired air volume. In this study, the control verification experiments were conducted to investigate whether the compressed air volume discharged toward the IfA was changed by using the BES measured from the rectus femoris muscle. The results indicated that the proposed algorithm embedded in the InAC can control the internal air volume of the IfA on the basis of the BES displacement while also tracking the desired air volume (mean absolute error: 3.03 mL; mean absolute percentage error: 6.85%). [ABSTRACT FROM AUTHOR]

Background: Active upper extremity (UE) assistive devices have the potential to restore independent functional movement in individuals with UE impairment due to neuromuscular diseases or injury-induced chronic weakness. Academically fabricated UE assistive devices are not usually optimized for activities of daily living (ADLs), whereas commercially available alternatives tend to lack flexibility in control and activation methods. Both options are typically difficult to don and doff and may be uncomfortable for extensive daily use due to their lack of personalization. To overcome these limitations, we have designed, developed, and clinically evaluated the NuroSleeve, an innovative user-centered UE hybrid orthosis. Methods: This study introduces the design, implementation, and clinical evaluation of the NuroSleeve, a user-centered hybrid device that incorporates a lightweight, easy to don and doff 3D-printed motorized UE orthosis and a functional electrical stimulation (FES) component. Our primary goals are to develop a customized hybrid device that individuals with UE neuromuscular impairment can use to perform ADLs and to evaluate the benefits of incorporating the device into occupational therapy sessions. The trial is designed as a prospective, open-label, single-cohort feasibility study of eight-week sessions combined with at-home use of the device and implements an iterative device design process where feedback from participants and therapists informs design improvement cycles. Results: All participants learned how to independently don, doff, and use the NuroSleeve in ADLs, both in clinical therapy and in their home environments. All participants showed improvements in their Canadian Occupational Performance Measure (COPM), which was the primary clinical trial outcome measure. Furthermore, participants and therapists provided valuable feedback to guide further development. Conclusions: Our results from non-clinical testing and clinical evaluation demonstrate that the NuroSleeve has met feasibility and safety goals and effectively improved independent voluntary function during ADLs. The study's encouraging preliminary findings indicate that the NuroSleeve has met its technical and clinical objectives while improving upon the limitations of the existing UE orthoses owing to its personalized and flexible approach to hardware and firmware design. Trial Registration: ClinicalTrials.gov identifier: NCT04798378, https://clinicaltrials.gov/ct2/show/NCT04798378, date of registration: March 15, 2021. [ABSTRACT FROM AUTHOR]

After above-knee amputation, the missing biological knee and ankle are commonly replaced with a passive prosthesis, which cannot provide net-positive energy to assist the user. During activities such as sit-to-stand, above-knee amputees must compensate for this lack of power using their upper body, intact limb, and residual limb, resulting in slower, less symmetric, and higher effort movements. Previous studies have shown that powered prostheses can improve symmetry and speed by providing positive assistive power. However, we still lack a systematic investigation of the effect of powered prosthesis assistance. Without this knowledge, researchers and clinicians have no framework for tuning powered prostheses to optimally assist users. Here we show that varying the assistive knee torque significantly affected weight-bearing symmetry, effort, and speed during the stand-up movement in eight above-knee amputees. Specifically, we observed improvements in the index of asymmetry of the vertical ground reaction force at the point approximating maximum vertical center of mass acceleration, the integral of the intact vastus medialis activation measured using electromyography, and the stand-up duration compared to the passive prosthesis. We saw significant improvements in all three metrics when subjects used the powered prosthesis compared to the passive prosthesis. We saw improvements in all three metrics with increasing assistive torque levels commanded by the powered prosthesis. We also observed increased weight-bearing asymmetry at the end of movement, and increased kinematic asymmetry with increasing assistance from the powered prosthesis. These results show that powered prostheses can improve functional mobility, potentially increasing quality of life for millions of people living with above-knee amputations.

Fabric-based pneumatic actuators (FPAs) are extensively employed in the design of lightweight and compliant soft wearable assistive gloves. However, conventional FPAs typically exhibit limited output force, thereby restricting the applications of such gloves. This paper presents the development of a novel honeycomb pneumatic actuator (HPA) constructed using flexible thermoplastic polyurethane (TPU) coating through hot pressing or ultrasonic welding techniques. Compared to the previously utilized double-layer fabric-based pneumatic actuators (DLFPAs), the HPAs yields a remarkable 862% increase in end output force. It can produce a tip force of 13.57 N at a pressure of 150 kPa. The integration of HPAs onto a soft pneumatic glove enables the facilitation of various activities of daily living. A series of trials involving nine patients were conducted to assess the effectiveness of the soft glove. The experimental results indicate that when assisted by the glove, the patients’ finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints achieved angles of 87.67 ± 19.27° and 64.2 ± 30.66°, respectively. Additionally, the average fingertip force reached 10.16 ± 4.24 N, the average grip force reached 26.04 ± 15.08 N, and the completion rate of daily functions for the patients increased from 39% to 76%. These outcomes demonstrate that the soft glove effectively aids in finger movements and significantly enhances the patients’ daily functioning.

Studies on robotic interventions for gait rehabilitation after stroke require: (i) rigorous performance evidence; (ii) systematic procedures to tune the control parameters; and (iii) combination of control modes. In this study, we investigated how stroke individuals responded to training for two weeks with a knee exoskeleton (ABLE-KS) using both Assistance and Resistance training modes together with auditory feedback to train peak knee flexion angle. During the training, the torque provided by the ABLE-KS and the biofeedback were systematically adapted based on the subject’s performance and perceived exertion level. We carried out a comprehensive experimental analysis that evaluated a wide range of biomechanical metrics, together with usability and users’ perception metrics. We found significant improvements in peak knee flexion ( ${p} = {0}.{0016}$ ), minimum knee angle during stance ( ${p} = {0}.{0053}$ ), paretic single support time ( ${p} = {0}.{0087}$ ) and gait endurance ( ${p} = {0}.{022}$ ) when walking without the exoskeleton after the two weeks of training. Participants significantly ( ${p} < {0}.{00025}$ ) improved the knee angle during the stance and swing phases when walking with the exoskeleton powered in the high Assistance mode in comparison to the No Exo and the Unpowered conditions. No clinically relevant differences were found between Assistance and Resistance training sessions. Participants improved their performance with the exoskeleton (24-55 %) for the peak knee flexion angle throughout the training sessions. Moreover, participants showed a high level of acceptability of the ABLE-KS (QUEST 2.0 score: 4.5 ± 0.3 out of 5). Our preliminary findings suggest that the proposed training approach can produce similar or larger improvements in post-stroke individuals than other studies with knee exoskeletons that used higher training intensities.

Lower-limb exoskeletons enhance motor function in patients, benefiting both clinical rehab and daily activities. Nevertheless, pediatric exoskeletons remain largely underdeveloped. To address this gap, this study presents a new robotic lower-limb exoskeleton (LLE) design specifically tailored for children. Utilizing anthropometric data from the target demographic, the LLE has a size-adjustable design to accommodate children aged 8 to 12. The design incorporates six active joints at the hip and knee, actuated using Brushless DC motors in conjunction with Harmonic Drive gears. This study conducts a rigorous analysis of forward and inverse kinematics applied to the robotic LLE. While forward kinematics are essential for dynamic modeling and model-based control formulation, inverse kinematics play a crucial role in facilitating balance control. The study uses an algebraic-geometric method to solve the inverse kinematics of LLEs with four DOFs per leg, including one in the frontal plane and three in the sagittal plane. A unique model of validation and verification is then employed using the Simulink® and SimscapeTM computational environments. The accuracy of the forward kinematic analysis is confirmed by comparing separately modeled outcomes in both environments. The validity of the inverse kinematic model is verified by implementing sequential forward and inverse kinematic analyses, comparing the forward kinematic inputs with inverse kinematic outputs. Simulation results conclusively validate both the forward and inverse kinematic analyses, suggesting the exoskeleton’s potential in accommodating standard gait patterns.

Control systems of robotic prostheses should be designed to decode the users’ intent to start, stop, or change locomotion; and to select the suitable control strategy, accordingly. This paper describes a locomotion mode recognition algorithm based on adaptive Dynamic Movement Primitive models used as locomotion templates. The models take foot-ground contact information and thigh roll angle, measured by an inertial measurement unit, for generating continuous model variables to extract features for a set of Support Vector Machines. The proposed algorithm was tested offline on data acquired from 10 intact subjects and 1 subject with transtibial amputation, in ground-level walking and stair ascending/descending activities. Following subject-specific training, results on intact subjects showed that the algorithm can classify initiatory and steady-state steps with up to 100.00% median accuracy medially at 28.45% and 27.40% of the swing phase, respectively. While the transitory steps were classified with up to 87.30% median accuracy medially at 90.54% of the swing phase. Results with data of the transtibial amputee showed that the algorithm classified initiatory, steady-state, and transitory steps with up to 92.59%, 100%, and 93.10% median accuracies medially at 19.48%, 51.47%, and 93.33% of the swing phase, respectively. The results support the feasibility of this approach in robotic prosthesis control.

Control systems of robotic prostheses should be designed to decode the users’ intent to start, stop, or change locomotion; and to select the suitable control strategy, accordingly. This paper describes a locomotion mode recognition algorithm based on adaptive Dynamic Movement Primitive models used as locomotion templates. The models take foot-ground contact information and thigh roll angle, measured by an inertial measurement unit, for generating continuous model variables to extract features for a set of Support Vector Machines. The proposed algorithm was tested offline on data acquired from 10 intact subjects and 1 subject with transtibial amputation, in ground-level walking and stair ascending/descending activities. Following subject-specific training, results on intact subjects showed that the algorithm can classify initiatory and steady-state steps with up to 100.00% median accuracy medially at 28.45% and 27.40% of the swing phase, respectively. While the transitory steps were classified with up to 87.30% median accuracy medially at 90.54% of the swing phase. Results with data of the transtibial amputee showed that the algorithm classified initiatory, steady-state, and transitory steps with up to 92.59%, 100%, and 93.10% median accuracies medially at 19.48%, 51.47%, and 93.33% of the swing phase, respectively. The results support the feasibility of this approach in robotic prosthesis control. [ABSTRACT FROM AUTHOR]

Studies on robotic interventions for gait rehabilitation after stroke require: (i) rigorous performance evidence; (ii) systematic procedures to tune the control parameters; and (iii) combination of control modes. In this study, we investigated how stroke individuals responded to training for two weeks with a knee exoskeleton (ABLE-KS) using both Assistance and Resistance training modes together with auditory feedback to train peak knee flexion angle. During the training, the torque provided by the ABLE-KS and the biofeedback were systematically adapted based on the subject’s performance and perceived exertion level. We carried out a comprehensive experimental analysis that evaluated a wide range of biomechanical metrics, together with usability and users’ perception metrics. We found significant improvements in peak knee flexion (${p} = {0}.{0016}$), minimum knee angle during stance (${p} = {0}.{0053}$), paretic single support time (${p} = {0}.{0087}$) and gait endurance (${p} = {0}.{022}$) when walking without the exoskeleton after the two weeks of training. Participants significantly (${p} < {0}.{00025}$) improved the knee angle during the stance and swing phases when walking with the exoskeleton powered in the high Assistance mode in comparison to the No Exo and the Unpowered conditions. No clinically relevant differences were found between Assistance and Resistance training sessions. Participants improved their performance with the exoskeleton (24-55 %) for the peak knee flexion angle throughout the training sessions. Moreover, participants showed a high level of acceptability of the ABLE-KS (QUEST 2.0 score: 4.5 ± 0.3 out of 5). Our preliminary findings suggest that the proposed training approach can produce similar or larger improvements in post-stroke individuals than other studies with knee exoskeletons that used higher training intensities. [ABSTRACT FROM AUTHOR]

Fabric-based pneumatic actuators (FPAs) are extensively employed in the design of lightweight and compliant soft wearable assistive gloves. However, conventional FPAs typically exhibit limited output force, thereby restricting the applications of such gloves. This paper presents the development of a novel honeycomb pneumatic actuator (HPA) constructed using flexible thermoplastic polyurethane (TPU) coating through hot pressing or ultrasonic welding techniques. Compared to the previously utilized double-layer fabric-based pneumatic actuators (DLFPAs), the HPAs yields a remarkable 862% increase in end output force. It can produce a tip force of 13.57 N at a pressure of 150 kPa. The integration of HPAs onto a soft pneumatic glove enables the facilitation of various activities of daily living. A series of trials involving nine patients were conducted to assess the effectiveness of the soft glove. The experimental results indicate that when assisted by the glove, the patients’ finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints achieved angles of 87.67 ± 19.27° and 64.2 ± 30.66°, respectively. Additionally, the average fingertip force reached 10.16 ± 4.24 N, the average grip force reached 26.04 ± 15.08 N, and the completion rate of daily functions for the patients increased from 39% to 76%. These outcomes demonstrate that the soft glove effectively aids in finger movements and significantly enhances the patients’ daily functioning. [ABSTRACT FROM AUTHOR]