Older adults often experience a decline in functional abilities, affecting their independence and mobility at home. Wearable lower-limb exoskeletons (LLEs) have the potential to serve as both assistive devices to support mobility and training tools to enhance physical capabilities. However, active end-user involvement is crucial to ensure LLEs align with users’ needs and preferences. This study employed a co-design methodology to explore home-based LLE requirements from the perspectives of older adults with mobility impairments and physiotherapists. Four older adults with self-reported mobility limitations participated by creating personas to represent different user needs and experiences (i.e., PERCEPT methodology), alongside four experienced physiotherapists who contributed their professional insights. As assistive devices, LLEs were seen as valuable for promoting independence, supporting mobility, and facilitating social participation, with essential activities including shopping, toileting, and outdoor walking. Physiotherapists expressed enthusiasm for integrating LLEs into remote rehabilitation programs, particularly to improve strength, balance, coordination, and walking speed. Key design considerations included a lightweight, discreet device that is easy to don and doff and comfortable for extended wear. Physiotherapists highlighted the potential of digital monitoring to assess physical parameters and personalize therapy. Fatigue emerged as a significant challenge for older adults, reinforcing the need for assistive LLEs to alleviate exhaustion and enhance functional independence. A shortlist of LLE features was drafted and scored, covering activity and design applications. These findings provide valuable insights into the design and usability of home-based LLEs, offering a foundation for developing devices that improve acceptance, usability, and long-term impact on healthy ageing.

Designing optimal assistive wearable devices is a complex task, often addressed using human-in-the-loop optimization and biomechanical modeling approaches. However, as the number of design parameters increases, the growing complexity and dimensionality of the design space make identifying optimal solutions more challenging. Predictive simulation, which models movement without relying on experimental data, provides a powerful tool for anticipating the effects of assistive devices on the human body and guiding the design process. This study aims to introduce a design optimization platform that leverages predictive simulation of movement to identify the optimal parameters for assistive wearable devices. The proposed approach is specifically capable of dealing with the challenges posed by high-dimensional design spaces. The proposed framework employs a two-layered optimization approach, with the inner loop solving the predictive simulation of movement and the outer loop identifying the optimal design parameters of the device. It is utilized for designing a knee exoskeleton with a damper to assist level-ground and downhill gait, achieving a significant reduction in normalized knee load peak value by $ 37\% $ for level-ground and by $ 53\% $ for downhill walking, along with a decrease in the cost of transport. The results indicate that the optimal device applies damping torques to the knee joint during the Stance phase of both movement scenarios, with different optimal damping coefficients. The optimization framework also demonstrates its capability to reliably and efficiently identify the optimal solution. It offers valuable insight for the initial design of assistive wearable devices and supports designers in efficiently determining the optimal parameter set.

Specialists globally employ various clinical scales and instruments to assess balance, gait, and motor functions in children with cerebral palsy (CP). Selecting appropriate assessment tools is essential for planning studies, developing effective treatment strategies, and tracking clinical outcomes. Given the diversity in assessment needs – whether evaluating dynamic, functional, or static balance – there is a need to identify the most suitable tools for each aspect. Therefore, the primary objective of this review is to critically analyze current clinical and instrument-based assessment methods in the literature to determine the most effective approaches for pediatric CP. This systematic review retrieved 1,812 papers, of which only 23 met the inclusion criteria and presented assessment methods for evaluating balance and motor functions in pediatric CP. These methods were further organized into clinical and instrument-based assessment groups. Among clinical examinations, the Pediatric Balance Scale and Gross Motor Function Measures were considered gold standards and featured in eight studies. In contrast, postural sway measured with the Biodex Balance System, Gait Stability Indices from the GAITRite system, and EMG sensing were the predominant instrument-based observations. Despite this variety, a consensus on the best assessment methods remains lacking. This review highlights the potential of integrating AI-driven metrics that combine clinical and instrument-based data to enhance precision and individualized care. Future research should focus on creating integrated, individualized profiles to better capture the unique capabilities of children with CP, enabling more personalized and effective intervention strategies.

This study addresses challenges in sensor fusion for accurate and robust joint orientation estimation in human movement analysis using wearable inertial measurement units (IMUs). A magnetometer-free refined Kalman filter (KF) approach is presented and validated to address various indoor environmental constraints and challenges posed by human movement. These include variability in motion and dynamics, as well as magnetic disturbances caused by ferromagnetic materials or electronic interferences. Our proposed approach utilizes a Kalman-filter-based framework that analyzes the accelerometer’s alignment with the Earth’s frame to estimate orientation and correct gyroscope readings, eliminating reliance on magnetometer inputs. The algorithm was tested on both controlled robotic movements and real-world upper-limb-motion-monitoring scenarios. First, a comparative analysis was conducted on the double-stage Kalman filter (DSKF) and complementary filter using the collected robot motion encoder data. The results demonstrated superior performance in orientation estimation, particularly in yaw measurements, where the proposed method significantly improved accuracy. It achieved a lower root mean square error (RMSE = $ {2.447}^{\circ } $) and mean absolute error (MAE = $ {2.006}^{\circ } $), outperforming both the DSKF and complementary filter approaches. Additionally, the study’s findings were validated against a standard motion capture system, revealing error metrics within generally acceptable ranges ($ \le 12.4\% $ of the joint range of motion [ROM]) and strong correlation coefficients ($ {r}^2>0.89 $). However, some deviations were observed during complex motion cycle intervals, highlighting opportunities for further refinement. These findings suggest that the proposed approach presents a promising alternative for human joint orientation estimation in industrial settings with magnetic distortions.

Posture-related musculoskeletal issues among office workers are a significant health concern, mainly due to long periods spent in static positions. This research presents a Posture Lab which is a workplace-based solution through an easy-to-use posture monitoring system, allowing employees to assess their posture. The Posture Lab focuses on two key aspects: Normal Head Posture (NHP) versus Forward Head Posture (FHP) measurement and thoracic spine kyphosis. Craniovertebral (CA) and Shoulder Angles (SA) quantify NHP and FHP. The Kyphosis Angle (KA) is for measuring normal thoracic spine and kyphosis. To measure these angles, the system uses computer vision technology with ArUco markers detection via a webcam to analyze head positions. Additionally, wearable accelerometer sensors measure kyphosis by checking the angles of inclination. The framework includes a web-based user interface for registration and specialized desktop applications for different measurement protocols. A RESTful API enables system communication and centralized data storage for reporting. The Posture Lab serves as an effective tool for organizations to evaluate employee postures and supports early intervention strategies, allowing timely referrals to healthcare providers if any potential musculoskeletal issues are identified. The Posture Lab has also shown medium to very high correlations with standard 2D motion analysis methods – Kinovea – for CA, SA, and KA in FHP with kyphosis measurements (r = 0.607, 0.704, and 0.992) and shown high to very high correlations in NHP with normal thoracic spine measurements (r = 0.809, 0.748, and 0.778), with significance at p < .01, utilizing the Pearson correlation coefficient.

Limb salvage surgery (LSS) with megaprosthesis is a common treatment for distal femur tumors, but its impact on gait remains poorly understood. Traditional gait analysis methods are costly and require specialized equipment. This study aims to compare spatiotemporal gait parameters between patients with distal femur megaprosthesis and healthy controls using an inertial measurement unit (IMU). We conducted a case–control study with 79 participants: 31 patients with distal femur megaprosthesis and 48 healthy controls. Gait data were collected using an IMU placed at L5-S1, capturing metrics such as gait quality index (GQI), pelvic kinematics, propulsion index, and gait speed. Statistical analysis included Student’s t-test, Mann–Whitney U test, and one-way ANOVA to compare gait parameters across groups. Patients with megaprosthesis exhibited significantly lower gait speed, propulsion index and anteroposterior acceleration symmetry index compared to controls (p < .05). GQI was reduced in the healthy legs of the cases (92.3%) compared to control legs (96.6%). Adaptations included prolonged stance phases in healthy legs and decreased single support phases in prosthetic legs. Despite these changes, gait patterns remained within functional ranges. IMU-based gait analysis reveals significant but functional alterations in gait mechanics among patients with distal femoral megaprosthesis. These findings underscore the need for tailored rehabilitation strategies to address compensatory mechanisms, optimize mobility, and enhance long-term outcomes. The use of IMU technology offers a cost-effective and portable alternative for clinical gait assessments.

The human need for rehabilitation, assistance, and augmentation has led to the development and use of wearable exoskeletons. Upper limb exoskeletons under research and development are tested on human volunteers to gauge performance and usability. Direct testing can often cause straining of the joints, especially the shoulder joint, which is the most important and flexible joint in the upper extremity of the human body. The misalignment of joint axes between the exoskeleton and the human body causes straining. To avoid this, we propose designing and developing a novel human shoulder phantom mimicking the shoulder complex motion and the humeral head translation that can help in the real-time testing of exoskeletons without the need for human volunteers. The device can be used to test the interaction forces and the maximum reachable position of the exoskeleton. It consists of three degrees of freedom (DOF) passive shoulder girdle mechanism and seven DOF glenohumeral joint mechanisms, of which six are passive revolute joints and one is an active prismatic joint mimicking the humeral head translation. All the passive joints are spring-loaded and are incorporated with joint angle sensors. A custom-made, three-axis force sensor measures the human–exoskeleton interaction forces. The design details, selection of joint springs, linear actuation mechanism, and the analysis of the phantom’s reachable workspace are presented. The device is validated by comparing the interaction forces produced during the conventional exoskeleton-assisted and human-assisted phantom arm elevation.

Upper-limb occupational exoskeletons reduce injuries during overhead work. Previous studies focused on muscle activation with and without exoskeletons, but their impact on shoulder fatigue remains unclear. Additionally, no studies have explored how exoskeleton support levels affect fatigue. This study investigates the effects of assistive profiles on muscular and cardiovascular fatigue. Electromyographic (EMG) and electrocardiographic signals were collected to compute EMG median frequency (MDF), heart rate (HR), and heart rate variability (HRV). Fatigue was assessed using three MDF and HR metrics: relative change ($ {\mathrm{MDF}}_{\Delta} $,$ {\mathrm{HR}}_{\Delta} $), slope ($ {\mathrm{MDF}}_{\mathrm{slope}} $,$ \mathrm{H}{\mathrm{R}}_{\mathrm{slope}} $), and intercept ($ {\mathrm{MDF}}_{\mathrm{intercept}} $,$ \mathrm{H}{\mathrm{R}}_{\mathrm{intercept}} $) of the linear regression. Results showed$ {\mathrm{MDF}}_{\Delta} $decreased 64% (p = 0.0020) with higher assistance compared to no exoskeleton; $ {\mathrm{HR}}_{\Delta} $ decreased 40% (p < 0.0273) with lower assistance, $ {\mathrm{MDF}}_{\mathrm{slope}} $ decreased up to 67% (p = 0.0039) and $ \mathrm{H}{\mathrm{R}}_{\mathrm{slope}} $ by 43% (p < 0.0098) with higher and medium assistance. HRV metrics included root mean square of successive differences (RMSSD) and low-frequency to high-frequency power ratio (LF/HF). RMSSD indicated parasympathetic dominance, while rising LF/HF ratio suggested physiological strain. Findings support occupational exoskeletons as ergonomic tools for reducing fatigue.

The human hand is an intricate anatomical structure essential for daily activities, yet replicating its full functionality in upper-limb prostheses remains a significant challenge. Despite advances in mechanical design leading to more sophisticated and dexterous artificial hands, difficulties persist in effectively controlling these prostheses due to the limitations posed by the muscle conditions of their users. These constraints result in a limited number of control inputs and a lack of sensory feedback. To address these issues, various semi-autonomous control strategies have been proposed, which integrate sensing technologies to complement traditional myoelectric control. Inspired by human grasping physiology, we propose a shared control strategy that divides grasp control into two levels: a high-level controller, operated by the user to initiate the grasp action, and a low-level controller, which ensures stability throughout the task. This work focuses specifically on slip detection methods, introducing improvements to the low-level controller to enable more autonomous grasping behavior during object holding. The proposed slip module uses distributed 3D force sensors across the artificial hand and integrates a friction cone strategy to ensure an appropriate shear-to-normal force ratio with bandpass filtering for establishing an initial stable grasp model without prior knowledge. Experimental evaluations consist of the comparison of this novel controller with conventional state-of-the-art approaches. Results demonstrate its efficacy in preventing slippage while requiring less grasping force than previous methods. Additionally, a qualitative validation was conducted to assess its responsiveness compared to human grasping reactions to unexpected weight changes, yielding positive outcomes.

Spurred by the global pandemic, research in health monitoring has pivoted towards the development of smart garments, enabling long-term tracking of individuals’ cardiovascular health by continuously monitoring the electrocardiogram (ECG) and detecting any abnormality in the signal morphology. Many types of dry electrodes have been proposed as alternatives to gold standard Ag/AgCl wet electrodes, and they have been integrated into clothes capable of acquiring only a limited number of the different ECG traces. This limitation severely diminishes the diagnostic utility of the collected ECG data and obstructs the garment’s potential for clinical-level evaluation. Here, we demonstrate a special ECG upper armband with a glove component which houses graphene-textile electrodes, where a fully mobile, exploring electrode located at the index finger enables the user to strategically position the electrode on-demand to desired body areas and measure the different ECG traces that are bipolar limb and unipolar chest leads. Based on measurements with and without employing the well-known Wilson Central Terminal (WCT) arrangement, the correlation ratio of unipolar ECG chest leads acquired with the graphene textile-based armband and Ag/AgCl electrodes both in “WCT-less” configuration reach up to %99.65; and up to %99.54 when Ag/AgCl electrodes are utilized “with WCT” while the graphene-based armband in “WCT-less” configuration. To the authors’ best knowledge, this study reports the first multilead on-demand “touch-and-measure” ECG recording from a fully wearable textile garment. Moreover, owing to the human-centered armband design, we achieved a more than three-fold reduction in electrode count from 10 in clinical ECG practice down to 3.

The integration of wearable smart garments with multiple sensors has gained momentum, enabling real-time monitoring of users’ vital parameters across various domains. This study presents the development and validation of an instrumented smart shirt for risk prevention in workplaces designed to enhance worker safety and well-being in occupational settings. The proposed smart shirt is equipped with sensors for collecting electrocardiogram, respiratory waveform, and acceleration data, with signal conditioning electronics and Bluetooth transmission to the mobile application. The mobile application sends the data to the cloud platform for subsequent Preventive Risk Index (PRI) extraction. The proposed SenseRisc system was validated with eight healthy participants during the execution of different physically exerting activities to assess the capability of the system to capture physiological parameters and estimate the PRI of the worker, and user subjective perception of the instrumented intelligent shirt.

Adjusting the assistive torque of upper limb occupational exoskeletons is essential to optimize their effectiveness and user acceptance in companies. This adjustment enables a balance to be struck between the expected benefits and potential undesirable effects associated with their use, particularly for the shoulder joint, which is sensitive to the balance of forces. Despite this, no study has yet evaluated these assistive torques in static and dynamic conditions representative of work situations. The aim of this article is therefore to evaluate these assistive torques under these two conditions, using an isokinetic dynamometer. Angular velocities ranging from 0 to 240°/s and four levels of assistance were investigated. The results showed that the maximum assistive torques in flexion (energy restitution phase) were lower than those in extension (tensioning phase) by 20 to 36% and were median in static conditions. It was also observed that the level of assistance and the exoskeleton opening angles had a strong impact on the assistive torques, unlike the angular velocity in dynamic conditions, which had a minimal effect. Quantifying these assistive torques is crucial for assessing their biomechanical impact and adjusting the exoskeleton’s assistance to the operator and the task performed.

Electromyogram (EMG)-controlled prosthetic hands have advanced significantly during the past two decades. However, most of the currently available prosthetic hands fail to replicate human hand functionality and controllability. To measure the emulation of the human hand by a prosthetic hand, it is important to evaluate the functional characteristics. Moreover, incorporating feedback from end users during clinical testing is crucial for the precise assessment of a prosthetic hand. The work reported in this manuscript unfolds the functional characteristics of an EMG-CoNtrolled PRosthetIC Hand called ENRICH. ENRICH is a real-time EMG controlled prosthetic hand that can grasp objects in 250.8$ \pm $1.1 ms, fulfilling the neuromuscular constraint of a human hand. ENRICH is evaluated in comparison to 26 laboratory prototypes and 10 commercial variants of prosthetic hands. The hand was evaluated in terms of size, weight, operation time, weight lifting capacity, finger joint range of motion, control strategy, degrees of freedom, grasp force, and clinical testing. The box and block test and pick and place test showed ENRICH’s functionality and controllability. The functional evaluation reveals that ENRICH has the potential to restore functionality to hand amputees, improving their quality of life.

Wearable exoskeletons hold the potential to provide valuable physical assistance across a range of tasks, with applications steadily expanding across different scenarios. However, the lack of universally accepted testbeds and standardized protocols limits the systematic benchmarking of these devices. In response, the STEPbySTEP project, funded within the Eurobench framework, proposes a modular, sensorized, reconfigurable staircase testbed designed as a novel evaluation approach within the first European benchmarking infrastructure for robotics. This testbed, to be incorporated into the Eurobench testing facility, focuses on stairs as common yet challenging obstacles in daily life that provide a unique benchmark for exoskeleton assessment.

The primary aim of STEPbySTEP is to propose a modular framework – including a specialized staircase design, tentative metrics, and testing protocols – to aid in evaluating and comparing exoskeleton performance. Here, we present the testbed and protocols developed and validated in preliminary trials using three exoskeletons: two lower-limb exoskeletons (LLEs) and one back-support exoskeleton. The results offer initial insights into the adaptability of the staircase testbed across devices, showcasing example metrics and protocols that underscore its benchmarking potential.

The muscular restructuring and loss of function that occurs during a transfemoral amputation surgery has a great impact on the gait and mobility of the individual. The hip of the residual limb adopts a number of functional roles that would previously be controlled by lower joints. In the absence of active plantar flexors, swing initiation must be achieved through an increased hip flexion moment. The high activity of the residual limb is a major contributor to the discomfort and fatigue experienced by individuals with transfemoral amputations during walking. In other patient populations, both passive and active hip exosuits have been shown to positively affect gait mechanics. We believe an exosuit configured to aid with hip flexion could be well applied to individuals with transfemoral amputation. In this article, we model the effects of such a device during whole-body, subject-specific kinematic simulations of level ground walking. The device is simulated for 18 individuals of K2 and K3 Medicare functional classification levels. A user-specific device profile is generated via a three-axis moment-matching optimization using an interior-point algorithm. We employ two related cost functions that reflect an active and passive form of the device. We hypothesized that the optimal device configuration would be highly variable across subjects but that variance within mobility groups would be lower. From the results, we partially accept this hypothesis, as some parameters had high variance across subjects. However, variance did not consistently trend down when dividing into mobility groups, highlighting the need for user-specific design.

This article presents a bioinspired pneumatic soft actuator designed to mimic the flexo-extension movement of the human finger, with a particular focus on stiffness modulation through granular jamming. Three-chamber geometries – honeycomb, rectangular, and half-round – were evaluated to optimize curvature performance, utilizing Mold Star 15 Slow elastomer for actuator fabrication. Granular jamming, both passive and active, was implemented within the inextensible layer using chia and quinoa grains to enhance stiffness modulation. Experimental results revealed that the honeycomb geometry most closely aligned with the natural index finger trajectory. Stiffness evaluations demonstrated a range of 0–0.47 N/mm/° for quinoa and 0–0.9 N/mm/° for chia. The actuator’s force output increased by 16% for quinoa and 71% for chia compared to the nonjammed configuration. This enhanced performance is particularly beneficial for applications such as hand rehabilitation, where adaptive stiffness and force modulation are critical. Granular jamming, especially with active chia, provided superior adaptability for tasks requiring variable stiffness and resistance, making it a promising candidate for wearable robotic applications in rehabilitation.

This study introduces a novel method for gait analysis using a single inertial measurement unit placed on the sacrum. This method is valid not only on level ground but also on incline and decline conditions. The method leverages the “crackle” function, the third derivative of the sacral resultant acceleration, to identify right and left gait events. This approach is particularly effective in capturing the initial peak in acceleration data during foot impact with the ground, often overlooked by other methods. The study aimed to demonstrate the method’s accuracy in identifying the right- and left-side impacts during level ground, incline, and decline runs across a range of speeds. Additionally, the algorithm was applied in outdoor running scenarios, where it performed very well, further validating its robustness and reliability. The results are compared with other existing methods to highlight the effectiveness of this approach.

Eye gaze tracking is increasingly popular due to improved technology and availability. In the domain of assistive device control, however, eye gaze tracking is often used in discrete ways (e.g., activating buttons on a screen), and does not harness the full potential of the gaze signal. In this article, we present a method for collecting both reactionary and controlled eye gaze signals, via screen-based tasks designed to isolate various types of eye movements. The resulting data allows us to build an individualized characterization for eye gaze interface use. Results from a study conducted with participants with motor impairments are presented, offering insights into maximizing the potential of eye gaze for assistive device control. Importantly, we demonstrate the potential for incorporating direct continuous eye gaze inputs into gaze-based interface designs; generally seen as intractable due to the ‘Midas touch’ problem of differentiating between gaze movements for perception versus for interface operation. Our key insight is to make use of an individualized measure of smooth pursuit characteristics to differentiate between gaze for control and gaze for environment scanning. We also present results relating to gaze-based metrics for mental workload and show the potential for the concurrent use of eye gaze for control input as well as assessing a user’s mental workload both offline and in real-time. These findings might inform the development of continuous control paradigms using eye gaze, as well as the use of eye tracking as the sole input modality to systems that share control between human-generated and autonomy-generated inputs.

The wide adoption of occupational shoulder exoskeletons in industrial settings remains limited. Passive exoskeletons were proved effective in a limited amount of application scenarios, such as (quasi-)static overhead handling tasks. Quasi-active devices, albeit representing an improved version of their passive predecessors, do not allow full modulation of the amount of assistance delivered to the user, lacking versatility and adaptability in assisting various dynamic tasks. Active occupational shoulder exoskeletons could overcome these limitations by controlling the shape of the delivered torque profile according to the task they aim to assist. However, most existing active devices lack compactness and wearability. This prevents their implementation in working environments. In this work, we present a new active shoulder exoskeleton, named Active Exo4Work (AE4W). It features a new flexible shaft-driven remote actuation unit that allows the positioning of the motors close to the wearer’s center of mass while it maintains a kinematic structure that is compatible with the biological motion of the shoulder joint. in vitro and in vivo experiments have been conducted to investigate the performance of AE4W. Experimental results show that the exoskeleton is kinematically compatible with the user’s workspace since it does not constrain the natural range of motion of the shoulder joint. Moreover, this device can effectively provide different types of assistance while the user executes various dynamic tasks, without altering perceived comfort.