Robust estimation of lumbar joint forces in symmetric and asymmetric lifting tasks via large-scale electromyography-driven musculoskeletal models

Low back joint compression forces have been linked to the development of chronic back pain. Back-support exoskeletons controllers based on low back compression force estimates could potentially reduce the incidence of chronic pain. However, progress has been hampered by the lack of robust and accurate methods for compression force estimation. Electromyography (EMG)-driven musculoskeletal models have been proposed to estimate lumbar compression forces. Nonetheless, they commonly underrepresented trunk musculoskeletal geometries or activation–contraction dynamics, preventing validation across large sets of conditions. Here, we develop and validate a subject-specific large-scale (238 muscle–tendon units) EMG-driven musculoskeletal model for the estimation of lumbosacral moments and compression forces, under eight box-lifting conditions. Ten participants performed symmetric and asymmetric box liftings under 5 and 15 kg weight conditions. EMG-driven model-based estimates of L5/S1 flexion–extension moments displayed high correlation, R2 (mean range: 0.88–0.94), and root mean squared errors between 0.21 and 0.38 Nm/kg, with respect to reference inverse dynamics moments. Model-derived muscle forces were utilized to compute lumbosacral compression forces, which reached eight times participants body weight in 15 kg liftings. For conditions involving stooped postures, model-based analyses revealed a predominant decrease in peak lumbar EMG amplitude during the lowering phase of liftings, which did not translate into a decrease in muscle–tendon forces. During eccentric contraction (box-lowering), our model employed the muscle force–velocity relationship to preserve muscle force despite significant EMG reduction. Our modeling methodology can inherently account for EMG-to-force non-linearities across subjects and lifting conditions, a crucial requirement for robust real-time control of back-support exoskeletons.Support Biomechanical Engineerin

A Muscle Model Incorporating Fiber Architecture Features for the Estimation of Joint Stiffness During Dynamic Movement

Quantifying human joint stiffness in vivo during movement remains challenging. Well established stiffness estimation methods include system identification and the notion of quasi-stiffness, with experimental and conceptual limitations, respectively. Joint stiffness computation via biomechanical models is an emerging solution to overcome such limitations. However, these models make assumptions that hamper their generalization across muscle architectures. Here we present a stiffness formulation that considers the muscle’s pennation angle, and its comparison to a simpler formulation that does not. Model-based stiffness estimates are evaluated against joint-perturbation-based system identification. Results on muscles with different pennation angle show that our formulation seamlessly adjusts the muscle-tendon units’ stiffness depending on their architecture. At the joint level, our new model improved the stiffness estimations. Our study’s relevance is the creation and validation of a modeling formulation that does not require joint perturbation. This will enable better estimations and understanding of stiffness properties and human movement.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine Contro

Identification of Time-Varying Ankle Joint Impedance During Periodic Torque Experiments Using Kernel-Based Regression

Joint impedance is a common way of representing human joint dynamics. Since ankle joint impedance varies within the gait cycle, time-varying system identification techniques can be used to estimate it. Commonly, time-varying system identification techniques assume repeatably of joint impedance over cyclic motions, without taking into consideration the inherent variability of human behavior. In this paper, a method that assumes smooth, cyclic joint impedance, yet allows for cycle-to-cycle variability, is proposed. The method was tested on isometric, cyclic experimental data from the ankle under conditions with a time variation comparable to the expected one during the gait cycle. The estimated model could describe the data with high accuracy (VAF of 94.96%) and retrieve realistic inertia, damping and stiffness parameters. The results provide motivation to further apply the method on experiments under dynamic conditions and to employ the proposed method as a tool for investigating the human joint dynamics during cyclic movements.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Biomechatronics & Human-Machine Contro

Real-time lumbosacral joint loading estimation in exoskeleton-assisted lifting conditions via electromyography-driven musculoskeletal models

Lumbar joint compression forces have been linked to the development of chronic low back pain, which is specially present in occupational environments. Offline methodologies for lumbosacral joint compression force estimation are not commonly integrated in occupational or medical applications due to the highly time-consuming and complex post-processing procedures. Hence, applications such as real-time adjustment of assistive devices (i.e., back-support exoskeletons) for optimal modulation of compression forces remains unfeasible. Here, we present a real-time electromyography (EMG)-driven musculoskeletal model, capable of estimating accurate lumbosacral joint moments and plausible compression forces. Ten participants performed box-lifting tasks (5 and 15 kg) with and without the Laevo Flex back-support exoskeleton using squat and stoop lifting techniques. Lumbosacral kinematics and EMGs from abdominal and thoracolumbar muscles were used to drive, in real-time, subject-specific EMG-driven models, and estimate lumbosacral joint moments and compression forces. Real-time EMG-model derived moments showed high correlations (R2 = 0.76 - 0.83) and estimation errors below 30% with respect to reference inverse dynamic moments. Compared to unassisted lifting conditions, exoskeleton liftings showed mean lumbosacral joint moments and compression forces reductions of 11.9 - 18.7 Nm (6 - 12% of peak moment) and 300 - 450 N (5 - 10%), respectively. Our modelling framework was capable of estimating in real-time, valid lumbosacral joint moments and compression forces in line with in vivo experimental data, as well as detecting the biomechanical effects of a passive back-support exoskeleton. Our presented technology may lead to a new class of bio-protective robots in which personalized assistance profiles are provided based on subject-specific musculoskeletal variables.Support Biomechanical Engineerin

Laser-induced Periodic Surface Structures (LIPSS) on heavily boron-doped diamond for electrode applications

Diamond is known as a promising electrode material in the fields of cell stimulation, energy storage (e.g., supercapacitors), (bio)sensing, catalysis, etc. However, engineering its surface and electrochemical properties often requires costly and complex procedures with addition of foreign material (e.g., carbon nanotube or polymer) scaffolds or cleanroom processing. In this work, we demonstrate a novel approach using laser-induced periodic surface structuring (LIPSS) as a scalable, versatile, and cost-effective technique to nanostructure the surface and tune the electrochemical properties of boron-doped diamond (BDD). We study the effect of LIPSS on heavily doped BDD and investigate its application as electrodes for cell stimulation and energy storage. We show that quasi-periodic ripple structures formed on diamond electrodes laser-textured with a laser accumulated fluence of 0.325 kJ/cm2 (800 nm wavelength) displayed a much higher double-layer capacitance of 660 μF/cm2 than the as-grown BDD (20 μF/cm2) and that an increased charge-storage capacity of 1.6 mC/cm2 (>6-fold increase after laser texturing) and a low impedance of 2.74 ω cm2 turn out to be appreciable properties for cell stimulation. Additional morphological and structural characterization revealed that ripple formation on heavily boron-doped diamond (2.8 atom % [B]) occurs at much lower accumulated fluences than the 2 kJ/cm2 typically reported for lower doping levels and that the process involves stronger graphitization of the BDD surface. Finally, we show that the exposed interface between sp2 and sp3 carbon layers (i.e. the laser-ablated diamond surface) revealed faster kinetics than the untreated BDD in both ferrocyanide and RuHex mediators, which can be used for electrochemical (bio)sensing. Overall, our work demonstrates that LIPSS is a powerful single-step tool for the fabrication of surface-engineered diamond electrodes with tunable material, electrochemical, and charge-storage properties.Micro and Nano Engineerin

Dynamic building stock modelling: Application to 11 European countries to support the energy efficiency and retrofit ambitions of the EU

A dynamic building stock model is applied to simulate the development of dwelling stocks in 11 European countries, over half of all European dwellings, between 1900 and 2050. The model uses time series of population and number of persons per dwelling, as well as demolition and renovation probability functions that have been derived for each country. The model performs well at simulating the long-term changes in dwelling stock composition and expected annual renovation activities. Despite differences in data collection and reporting, the modelled future trends for construction, demolition and renovation activities lead to similar patterns emerging in all countries. The model estimates future renovation activity due to the stock’s need for maintenance as a result of ageing. The simulations show only minor future increases in the renovation rates across all 11 countries to between 0.6–1.6%, falling short of the 2.5–3.0% renovation rates that are assumed in many decarbonisation scenarios. Despite this, 78% of all dwellings could benefit from energy efficiency measures by 2050, either as they are constructed (31%) or undergo deep renovation (47%). However, as no more than one deep renovation cycle is likely on this timeframe, it is crucial to install the most energy efficient measures available at these opportunities.OLD Housing Quality and Process Innovatio

Design, fabrication and performance of the 10-in TOM HPD

The first sealed TOM Hybrid Photon Detector (HPD) with 10-in. diameter has been fabricated and successfully tested at CERN. This HPD has a spherical entrance window and a bialkali photocathode. The fountain focusing optics produces a demagnified image (D = 4) on the round segmented silicon sensor. The signals of the 2048 cells are read out through analog front-end electronics encapsulated in the vacuum envelope. We report on the design, fabrication technique and the experimental results obtained with laboratory test benches. The large TOM HPD is a prototype tube developed for the CLUE cosmic ray experiment. The final tubes, now under development, will be equipped with a solar-blind Rb//2Te photocathode and self triggering front-end electronics

Demographic and clinical data in acquired hemophilia A: results from the European Acquired Haemophilia Registry (EACH2).

Background: Acquired hemophilia A (AHA) is a rare autoimmune disease caused by autoantibodies against coagulation factor VIII and characterized by spontaneous hemorrhage in patients with no previous family or personal history of bleeding. Although data on several AHA cohorts have been collected, limited information is available on the optimal management of AHA. Objectives: The European Acquired Hemophilia Registry (EACH2) was established to generate a prospective, large-scale, pan-European database on demographics, diagnosis, underlying disorders, bleeding characteristics, treatment and outcome of AHA patients. Results: Five hundred and one (266 male, 235 female) patients from 117 centers and 13 European countries were included in the registry between 2003 and 2008. In 467 cases, hemostasis investigations and AHA diagnosis were triggered by a bleeding event. At diagnosis, patients were a median of 73.9years. AHA was idiopathic in 51.9%; malignancy or autoimmune diseases were associated with 11.8% and 11.6% of cases. Fifty-seven per cent of the non-pregnancy-related cases were male. Four hundred and seventy-four bleeding episodes were reported at presentation, and hemostatic therapy initiated in 70.5% of patients. Delayed diagnosis significantly impacted treatment initiation in 33.5%. Four hundred and seventy-seven patients underwent immunosuppression, and 72.6% achieved complete remission. Conclusions: Representing the largest collection of consecutive AHA cases to date, EACH2 facilitates the analysis of a variety of open questions in AHA