Clara Beatriz Sanz-Morère

Static force plates (FP) are the gold standard for measuring ground reaction forces (GRF) and computing joint moments through inverse dynamics in gait analysis. However, they are restricted to controlled environments, and the number of steps analyzed is limited by the plates embedded in the floor. To address these limitations, portable solutions such as sensorized insoles, socks, or shoes have emerged. Yet, creating wearable systems capable of measuring three-dimensional GRF in real-world conditions remains challenging. Current sensorized shoes often incorporate thick sensors (up to 2 cm), reducing usability and limiting their application in pathological populations or dynamic tasks like running. This study evaluates the usability of ShokacShoes, a novel sensorized shoe integrating three thin, three-dimensional force sensors, and explores its potential as a Wearable Force Plate (WFP). Eight healthy participants performed slow, natural, and fast walking using two insole configurations. Force and temporal metrics were derived from WFP and FP data. Results indicate that WFP enables accurate step segmentation and detects significant effects of speed and insole type on temporal and force metrics, confirming its reliability under different walking conditions. Comparisons with FP revealed differences in force metrics and signal morphology, though temporal parameters remained consistent. These results are likely due to sensor quantity and positioning. Thereby, ShokacShoes represent a valid solution capable of measuring three-dimensional forces within commercial footwear. Future work will focus on validating the applicability of a new version of ShokacShoes against gold-standard FP in a comprehensive validation study involving diverse real-world scenarios and pathological conditions.

Gait recovery in patients with incomplete spinal cord injury exhibits high inter-individual variability, which is difficult to characterize using conventional clinical metrics. The integration of clinical, biomechanical, and neurophysiological variables enables an objective and multidimensional characterization of motor recovery, capturing both functional performance and the underlying mechanisms of motor control. However, this global view generates high-dimensional feature spaces that require specific computational tools for exploration. This study proposes an unsupervised dimensionality reduction using Uniform Manifold Approximation and Projection (UMAP), applied to longitudinal multimodal data from four patients with similar levels of functional independence. Results show subject-specific groupings in the two-dimensional projection with no common longitudinal pattern, reflecting the heterogeneity of the recovery process. This work represents a first exploratory step towards the development of machine learning models for individualized classification and prediction of gait recovery.

Stroke affects over 101 million individuals worldwide, leaving many to cope with long-term consequences. These often include physical and cognitive impairments such as muscle weakness, loss of coordination, and challenges in performing daily activities. Several quantitative indices have been developed to objectively quantify gait deviations with a focus on ensuring ease of use and accessibility within clinical settings. Among those, the most cited one is the Gait Deviation Index (GDI), originally developed with data from a population of children with cerebral palsy. This characteristic probably reduces the ability of the GDI to interpret stroke-specific deviations. To overcome this limitation, one possibility is to derive a GDI for each specific population, as demonstrated for spinal cord injury. In this study, we developed a stroke-specific GDI (STR-GDI) considering a database of 22 healthy controls and 69 post-stroke subjects. The STR-GDI with a 17-feature basis provided a more reliable reconstruction of non-native data compared to the 15-feature original GDI basis. Both GDI and STR-GDI showed excellent reliability across limbs and datasets (ICC = 0.99), although STR-GDI showed higher ICCs in the test set for the non-paretic limbs (0.95 compared to 0.91 for the GDI). Regression models between GDI and STR-GDI yielded R ² values of 0.76 and 0.81, respectively for the paretic and non-paretic limbs. The linear regressions between indexes and clinical and gait variables were less consistent but still meaningful, with R ² values lower than 0.23. These results may indicate that these metrics offer complementary information, and their combined use could provide a more comprehensive understanding of post-stroke gait impairments. STR-GDI showed slightly higher correlations than GDI with the lower-limb Fugl-Meyer Assessment, the percentage of stance phase, step length, and cadence. In conclusion, in this study we successfully adapted the original GDI methodology to create a STR-GDI to capture gait deviations specific to post-stroke individuals. This study makes a meaningful methodological contribution by developing and validating a complete automatic pipeline that could be adapted to generate other condition-specific GDIs for other neurological or musculoskeletal disorders, provided that datasets are available. Future work will expand the STR-GDI using a larger and more diverse stroke population, assess its inter-session reliability, and develop a compatible version for inertial measurement units and markerless motion capture systems, facilitating broader clinical and real-world applications.

Most individuals who experience a stroke exhibit several sensorimotor impairments that limit their independence in everyday activities. Hemiparetic gait is frequently characterized by reduced knee flexion in swing due to knee stiffness or muscle weakness and knee hyperextension or knee buckling in the stance phase. Recently, unilateral-powered orthoses have been designed to overcome the limitations of the passive knee-ankle-foot orthoses. This study presents a unilateral Active Knee Orthosis Exoskeleton, AKO-$\beta$, endowed with a series elastic actuator and designed to assist the knee in flexion and extension movements. The paper describes the system mechatronic design and its characterization on the bench, the control system, and pilot experiments with three post-stroke participants. The device has a weight of 1.78 kg on the user's leg, with a lateral encumbrance of 76 mm. The pilot experiments aimed to verify the effects of the exoskeleton assistance in hemiparetic gait patterns. When walking with the device, participants on average increased the knee flexion on the paretic side by 18.70 deg (+44.9%) during swing and decreased knee hyperextension in stance by 4.50 deg, compared to walking without it. Overall, when walking with the exoskeleton, subjects showed improved Gait Variable Score of the paretic knee profile by 37.5% compared to walking without it. The temporal and spatial gait symmetry indexes did not show clear changes, although an improvement in symmetry was observed in two of the three participants. These preliminary results suggest the potential benefits of the unilateral Active Knee Orthosis exoskeleton to enhance and restore mobility in individuals with hemiparetic gait.

Arm swing is an inherent aspect of human locomotion that enhances lower limb (LL) muscle activation, which may explain its benefits for stroke rehabilitation over fixed-arm approaches. This study analyzed how restricting arm movement affects LL muscle coordination by comparing treadmill walking with arms (WWA) and walking with no arms (WNA) through muscle synergy analysis. Surface electromyography was recorded from eight LL muscles in ten healthy participants. Significant differences were found in muscle activity envelopes at 50% of the gait cycle (GC) for the Gluteus Medius, 0% and 100% GC for the Vastus Lateralis and Semitendinosus, and 25% GC for the Semitendinosus, Gastrocnemius Medialis, and Soleus. The Rectus Femoris and Vastus Lateralis showed higher variability and activation in WNA compared to WWA. Synergy analysis revealed four muscle synergies, with a median global variance of 95%. While spatial components were similar, temporal differences emerged at 0% GC for Synergy 1, 5% and 90% GC for Synergy 2, and 95% GC for Synergy 3 (p < 0.05). Our results suggest that arm swing influences LL muscle activity and coordination during walking. Future studies will aim at understanding the effects of arm swing in stroke rehabilitation, which could help design more effective gait rehabilitation protocols including arm swing.

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination.We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH’s protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human–exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community.

Background: Transfemoral amputation is a serious intervention that alters the locomotion pattern, leading to secondary disorders and reduced quality of life. The outcomes of current gait rehabilitation for TFAs seem to be highly dependent on factors such as the duration and intensity of the treatment and the age or etiology of the patient. Although the use of robotic assistance for prosthetic gait rehabilitation has been limited, robotic technologies have demonstrated positive rehabilitative effects for other mobility disorders and may thus offer a promising solution for the restoration of healthy gait in TFAs. This study therefore explored the feasibility of using a bilateral powered hip orthosis (APO) to train the gait of community-ambulating TFAs and the effects on their walking abilities. Methods: Seven participants (46–71 years old with different mobility levels) were included in the study and assigned to one of two groups (namely Symmetry and Speed groups) according to their prosthesis type, mobility level, and prior experience with the exoskeleton. Each participant engaged in a maximum of 12 sessions, divided into one Enrollment session, one Tuning session, two Assessment sessions (conducted before and after the training program), and eight Training sessions, each consisting of 20 minutes of robotically assisted overground walking combined with additional tasks. The two groups were assisted by different torque-phase profiles, aiming at improving symmetry for the Symmetry group and at maximizing the net power transferred by the APO for the Speed group. During the Assessment sessions, participants performed two 6-min walking tests (6mWTs), one with (Exo) and one without (NoExo) the exoskeleton, at either maximal (Symmetry group) or self-selected (Speed group) speed. Spatio-temporal gait parameters were recorded by commercial measurement equipment as well as by the APO sensors, and metabolic efficiency was estimated via the Cost of Transport (CoT). Additionally, kinetic and kinematic data were recorded before and after treatment in the NoExo condition. Results: The one-month training protocol was found to be a feasible strategy to train TFAs, as all participants smoothly completed the clinical protocol with no relevant mechanical failures of the APO. The walking performance of participants improved after the training. During the 6mWT in NoExo, participants in the Symmetry and Speed groups respectively walked 17.4% and 11.7% farther and increased walking speed by 13.7% and 17.9%, with improved temporal and spatial symmetry for the former group and decreased energetic expenditure for the latter. Gait analysis showed that ankle power, step width, and hip kinematics were modified towards healthy reference levels in both groups. In the Exo condition metabolic efficiency was reduced by 3% for the Symmetry group and more than 20% for the Speed group. Conclusions: This study presents the first pilot study to apply a wearable robotic orthosis (APO) to assist TFAs in an overground gait rehabilitation program. The proposed APO-assisted training program was demonstrated as a feasible strategy to train TFAs in a rehabilitation setting. Subjects improved their walking abilities, although further studies are required to evaluate the effectiveness of the APO compared to other gait interventions. Future protocols will include a lighter version of the APO along with optimized assistive strategies.