Musculoskeletal models lack in vivo variability because their muscle parameters are scaled from limited dissection studies. Magnetic resonance imaging (MRI) could provide in vivo data, but its validation against dissection is challenged: the lengthy duration of dissection requires fixation to prevent tissue decay, yet fixation itself possibly introduces unquantified artifacts. The aim was two-fold; (1) to understand the effects of fixation on MRI-derived muscle volume, and (2) to evaluate the feasibility of handheld 3D scanning, for measurement of muscle fibers, origins, and insertions, to accelerate dissection studies, thereby potentially eliminating the need for fixation. MRI and handheld 3D scanning were verified against measurements of muscle weight, volume, and 3D digitizer measurements. We performed MRI on one fresh-frozen specimen, before and after AnubiFIX™ fixation. Followed by a dissection of 20 thigh muscles, with 3D handheld scanning to capture muscle surfaces, while muscle fibers, origins and insertions were measured with a 3D digitizer. Fixation caused a substantial 31.5% (SD 23.3%) muscle volume increase; separately, a methodological bias of MRI volumes systematically exceeding dissected volumes (+48.1 cm3), likely due to tissue dehydration during dissection. While handheld scanning reduced measurement time by 15-20 hours, it provided only partial visibility of muscle fibers (50%), origins (40%) and insertions (35%). By highlighting the volumetric effects of fixation and dehydration in muscles, and assessing handheld 3D scanning during dissection, this work provides a foundational framework for more meaningful comparisons between MRI and dissection for musculoskeletal models.

Background and research objective - Approximately 80\% of stroke patients experience upper limb motor impairments, including spasticity, muscle weakness, and abnormal synergies, which complicate daily activities. Accurate quantification of motor impairments is essential for optimizing rehabilitation strategies after a stroke. Objective and automatic assessment can be achieved with robotic devices. The Shoulder Elbow Perturbator (SEP) applies controlled mechanical perturbations to assess elbow and shoulder impairments. During these measurements, the wrist is fixated using plastic clamps with foam padding. But these clamps cause discomfort, positioning inconsistencies, instability, and unintended hand movemen. This study aims to design and evaluate an alternative fixation method for securing the arm in the SEP.

Method and results - A design thinking approach was applied. During brainstorming, concepts focused on arm conformity, rigidity, load distribution, and unrestricted elbow rotation. Based on a Harris profile, a lightweight vacuum brace was developed into a functional prototype, and clamps were redesigned to fit the brace. Validation experiments were performed with eight healthy participants tested in the SEP with both the vacuum brace and original rigid clamps. Comfort was assessed via questionnaire. Additionally, SEP angle and torque, and arm motion capture data were collected. The vacuum brace significantly reduced discomfort from severe to slight. SEP and motion capture data showed comparable fixation stability during multisine tasks. During passive stretch trials, lower intraclass correlation coefficients for stiffness estimation increased elbow displacement, and occasional movement within the clamps were observed with the brace, indicating reduced fixation performance.

Conclusions - The vacuum brace improved participant comfort during robotic assessment of upper limb motor impairments. Fixation stability was comparable during multisine perturbation tasks but reduced during stretch tasks, likely due to the current clamp design.

Background: Spinal cord injury (SCI) disrupts brain–peripheral nervous system communication, causing total or partial loss of motor, sensory, and autonomic functions below the lesion. Although functional electrical stimulation (FES) cycling rehabilitation can improve cardiopulmonary function, muscle mass, and locomotion, its clinical adoption is hindered by complex parameter tuning and a lack of standardized and personalized protocols.

Objective: The goal of this work is to first develop a methodology for the creation of FES patterns from electromyography (EMG), specifically from muscle synergy analysis. Then, to study how the obtained patterns compare to a standard one. We hypothesized that (1) the standard FES pattern would diverge from healthy muscle-activation timing, (2) it was designed for intermediate cadences, and (3) synergy-based patterns would yield smoother pedaling and better user ratings.

Methods: During data acquisition, we recorded EMG of eight leg muscles from eight healthy controls and two SCI patients while cycling at 30, 50, and 70 revolutions per minute (rpm) on a recumbent ergometer. Non-negative matrix factorization extracted muscle synergies and reconstructed EMG envelopes, which defined personalized stimulation ranges and amplitude profiles for each muscle. We quantified inter-limb symmetry and deviations of the personalized pattern from the standard one to characterize how each FES parameter set differed across trials. In the evaluation phase, eight healthy participants tested three patterns in random order for six minutes: the standard pattern, a fixed-50-rpm synergy-based pattern, and a synergy-based pattern adapting to the real-time cadence. Outcome measures were rpm variability and user perception ratings.

Results: Two of our three hypotheses were confirmed: (1) the standard FES pattern diverged significantly from healthy muscle-activation timing, and (2) it appeared to have been indeed designed for mid-range cadences (50 rpm approx.). However, the synergy-based personalization did not yield clear improvements over the standard pattern, and subjective preferences did not consistently align with objective metrics. Since the statistical tests yielded no significant difference between trials, two illustrative cases were shown, highlighting variability.

Conclusion: A practical workflow is recommended to first generate candidate patterns from muscle synergy analysis, conduct brief comparative trials using application-specific measures and user feedback, and then select the pattern that best balances these criteria for the intended rehabilitation protocol.

Purpose: Parkinson's Disease (PD) is the second most common neurodegenerative disease with a still increasing incidence. The implementation of new medical technology also increases yearly, to achieve better and a more efficient healthcare. One implementation of such a corresponding medical technology is Medtronic's sensing technology, which allows for reading of Local Field Potentials (LFPs). Furthermore, new assessment options are also investigated, with Markerless Motion Tracking (MMT) programs as interesting option for assessment of the Unified Parkinson's Disease Rate Scale (UDPRS). This study aims to investigate correlations between these LFP signals and parameters extracted from MMT programs during gait.
Methods: Pose estimation in this study was performed using MMT programs, while simultaneously recording LFP data in PD patients implanted with a Deep Brain Stimulation (DBS) device. LFP activity was filtered to only include beta activity, while this is primarily correlated with motor impairment. Normalisation methods were then applied on pose estimation data for allowance of distance calculation and extraction of the arm-swing parameters: velocity, acceleration and jerk.
Results: Results indicate a negative trend between LFP data and among almost all examined parameters. This applies for both trends observed: beta power analysis, as well as the UPDRS analysis. Left hemisphere shows significant correlation for the velocity (rho = -0.356, p = 0.046), acceleration (rho = -0.456, p = 0.01) and jerk (rho = -0.465, p = 0.01). While right hemisphere does not show this significance. Whereas, amplitude calculations even show contrary outcomes.
Conclusion: This study shows multiple connections between LFP data and gait parameters. Furthermore, it confirms the importance of arm-swing as indication for gait abnormalities. Finally, these findings suggest the need for more research on other parameters originated from different UPDRS tasks.

This thesis presents the development of a bidirectional, twisted-string actuated 3D-printed metamaterial hand orthosis aimed at supporting patients with impaired hand function in performing activities of daily living (ADL). Building upon a hybrid orthosis concept developed in previous work, the design was improved to address limitations such as mechanical inefficiency, spring buckling, and user discomfort, as well as actuate the device for future ADL support application. A novel actuation strategy using a one to one gear system with pre-wound wires, allowing for bidirectional motion and enhanced responsiveness. The actuation system was designed to deliver at least 120 𝑁 of linear force at 80 𝑚𝑚 of displacement, meeting the 15 𝑁 fingertip force requirement for ADL assistance. A closed-loop control system based on PID feedback was integrated, enabling the orthosis to track position targets.
In parallel, the orthosis design was refined to reduce internal friction, improve the input-output force gradient, and minimize twitching during actuation. The redesigned prototype demonstrated a 23.7% improvement in mechanical efficiency compared to the original version. Testing revealed that the system could perform a full hand closing/opening motion within 4 seconds and accurately replicate natural finger trajectories. Retesting the original orthosis under synchronized input/output conditions produced a reliable baseline
dataset, enabling a clear comparison between the legacy and updated systems. While the redesigned prototype encountered minor issues such as spring buckling under high loads due to fabrication tolerances, the overall performance met the core design goals. This work demonstrates the feasibility of integrating the novel bidirectional twisted-string actuation
system with 3D-printed metamaterial structures for wearable assistive devices. It provides a validated platform for further development toward user-ready robotic rehabilitation gloves with improved comfort, responsiveness, and usability.

Abstract - Background Most widely used musculoskeletal models are predominantly based on male anatomy. This limits accurate biomechanical analysis in women, despite notable sex differences in occurrence of musculoskeletal pathologies. Aim This study aimed to develop a female musculoskeletal model of the lower extremity (YONI). The YONI is compared to the generic (male-based) model in simulation with a female participant. Methods The YONI model was developed in OpenSim Creator based on MR images. Comparisons were done between the YONI model and a scaled RAJAG model and a personalized model of using motion capture data in simulations. Results For comparison between YONI and RAJAG with another female subject, mean RMS error for the personalized model was 0.0096 m (SD = 0.0013), for the scaled RAJAG model 0.0247 m (SD = 0.0268) and for the scaled YONI model 0.0097 m (SD = 0.0010). Although SPM paired t-test showed significant differences for both YONI and RAJAG compared to the personalized model for all joint angles, the YONI model showed lower t-values compared to RAJAG. Joint moments reveal larger differences between YONI and scaled RAJAG models in the hip angles during the swing phase. Reserve moments were low in hip flexion and hip adduction, but higher in knee flexion and ankle flexion. Conclusion While observed kinematic and dynamic differences require cautious interpretation due to model limitations and data constraints, this work represents a crucial step toward the development of a female musculoskeletal model, essential for advancing biomechanical research and clinical applications for women.

Work-related musculoskeletal disorders (WRMSDs) are a leading cause of work leave in the construc tion industry. As Strukton experiences a shortage in workers for rail catenary construction, minimizing the occurance of WRMSDs is important. This is done by the implementation of new working methods or new worker aids, such as boom lifts and exoskeletons. Strukton has experienced that not all worker aids are, however, as helpful as expected. In order to find the right tools, a better understanding of the work and physical load is needed. This thesis aims to identify which parts of the catenary construction workarethemostdemandingbycombininganergonomicriskassessment(ERA)withthedevelopment of an in situ biomechanical analysis tool. The research consists of two major components. First, a qualitative ergonomic risk assessment was conducted to identify the most physically demanding tasks in rail catenary construction. Methods in cluded site visits to Strukton’s rail construction projects, unstructured and semi-structured interviews with workers and experts, and a questionnaire administered to 12 workers. These data were used to develop a Work Breakdown Structure (WBS), categorize tasks based on their physical demand, dura tion, and frequency, and identify prevalent ergonomic risks. Tasks such as wire tensioning, removing wires, and task related to the support portal were identified as high-risk activities. Back, shoulder, and ankle complaints are the most commonly reported by workers and might be related to these tasks. Fu ture research should expand the worker sample size, investigate the causes of WRMSDs further, and enhancethe reliability of task scoring. Recommendations for Strukton include adding sidewalks on site, redesigning boom lift platforms, introducing ergonomic tool bags, and using electric tools for tasks that require high force. The second component of the research involved designing and validating an in-situ biomechanical analysis tool. The tool leverages pose detection technology from widely available mobile devices and integrates it with musculoskeletal modeling software to capture and analyze joint kinematics and mo ments during construction tasks. This approach allows for task-specific quantification of physical loads experienced by workers, bridging the gap between qualitative insights and quantitative measurements. A pilot validation study demonstrated the feasibility of the tool in providing kinematic and joint moment data for biomechanical analysis, though further validation is needed to generalize its application. Poten tial uses of the tool include automating ERAs and validating conceptual worker aids. Future research should focus on deploying the tool in real-world working environments and refining the implementation of external force data in the modeling process. The findings of this thesis highlight the critical need for task-specific ergonomic interventions in the construction of rail catenaries. The combination of qualitative ERA and biomechanical analysis offers a comprehensive framework to identify risks and design targeted solutions. This work provides a foun dation for future research into ergonomic improvements in dynamic and physically intensive industries

This research investigates methodologies to reduce and implement negative inertia in robots for upper extremity diagnostics and rehabilitation. The robot’s responsiveness is enhanced by integrating accelerometers and Kalman filters into the control scheme, ensuring smoother physical human-robot interactions. A force gain that mimics negative inertia significantly improves system dynamics within the admittance control framework. Introducing dead zones for force and acceleration stabilizes responses at lower rendered inertia, crucial for handling spastic conditions. However, this research identifies a lack of standardized evaluation methods for negative inertia and highlights hardware constraints, such as bandwidth limitations, that restrict performance. Future research should focus on establishing evaluation standards and optimizing hardware to refine control precision. This work demonstrates the potential of advanced control strategies to optimize robotic rehabilitation, paving the way for more effective diagnostic and therapeutic interventions.

This paper aims to explore innovative fabrication methods for assistive gloves using origami design principles. The study addresses the limitations of current assistive gloves, such as bulkiness and lack of customisation, by developing a novel fabrication method that improves ergonomic design and manufacturing flexibility. The proposed method integrates 3D printing and welding techniques to create lightweight, customisable gloves that enhance rehabilitation for individuals with hand impairments, particularly stroke survivors. The paper details the design process, and testing methods, concluding with successfully creating a new fabrication approach for origami-based assistive gloves.