Biology subjects

Seyfarth, A.

Publications and source records attributed to Seyfarth, A..

4 recordsLinked to original sources

bioRxiv2026

More Efficient Walking via Temporal and Spatial Energy Transfer in a Passive Biarticular Exosuit

Evaluating bioinspired design principles in wearable assistive devices provides a unique opportunity to interrogate our understanding of the critical factors that enable agile, stable, and economical human movement. We introduce the BiArticular Thigh EXosuit (BATEX), a wearable device integrating two morphological features found in biological legged systems: biarticular muscles and elastic tissues. BATEX employs two biarticular springs spanning the hip and knee to emulate the human rectus femoris and hamstring muscles, creating beneficial synergy to enhance walking economy. This design enables two energy-shuffling mechanisms: temporal (spring-like storage/return at a joint) and spatial (strut-like transfer across joints). In walking experiments at 1.3 m/s with N = 9 participants, a single compliant biarticular spring yielded a 7% metabolic cost reduction compared to walking without BATEX. Individually optimized configurations further improved metabolic reduction to 9%. BATEX morphology allowed users not only to off-load biological joint power (Assist) but also to increase total power (Augment). Across all exosuit configurations, the mechanical impact of the exosuit was reflected by a significant correlation between changes in users biarticular muscles activity and changes in net metabolic rate. In sum, compliant-biarticular exosuit architectures can concurrently assist and augment human lower-limb joint function, providing significant metabolic savings during walking.

bioengineering↗

bioRxiv2026

Can predictive simulations provide insights for personalizing assistive wearable device design?

Optimizing assistive wearable devices is crucial for their efficacy and user adoption, yet state-of-the-art methods like Human-in-the-Loop Optimization (HILO) and biomechanical modeling face limitations. HILO is time-consuming and often restricted to optimizing control parameters, while inverse dynamics assumes invariant kinematics, which is unreliable for adaptive human-device interaction. Predictive simulation offers a powerful alternative, enabling computational exploration of design spaces. However, existing approaches often lack systematic optimization frameworks and rigorous validation against experimental data. To address this, we developed a Design Optimization Platform that integrates predictive simulations within a two-level optimization structure for personalizing assistive device design. This paper primarily validates the platforms predictive simulations against a publicly available dataset of the passive Biarticular Thigh Exosuit (BATEX), assessing its reliability. Our findings show that the model can sufficiently predict the kinematics and major muscle activations, except for the pelvis tilt and some biarticular muscles. The key finding is that successful identification of personalized optimal BATEX stiffness parameters needs acceptable prediction of metabolic cost trends, not their precise values. Our analysis further reveals that the models accuracy in predicting Vasti muscle activation in the baseline condition is a significant indicator of its success in predicting metabolic cost trends. This demonstrates that accurate prediction of performance trends is more important for effective simulation-based design optimization than perfect biomechanical accuracy, advancing targeted and efficient assistive device development.

bioengineering↗

bioRxiv2026

Integrating Virtual Pivot Point and Trunk Dynamics to Understand Human Walking on Slopes: Insights from Experiments and Modeling

Walking on sloped terrain requires substantial mechanical and control adaptations for effective energy management compared to level ground locomotion. The Virtual Pivot Point (VPP) hypothesis explains sagittal plane angular momentum regulation during level walking, but its validity in slope walking remains unexplored. This study combines human experiments with template-model simulations to investigate how the VPP strategy is modulated during slope walking. Participants walked on an instrumented ramp at various inclinations (0{degrees}, {+/-} 7.5{degrees}, {+/-} 10{degrees}), while a 2D spring-loaded inverted-pendulum model with a trunk segment simulated the task. Experimental results confirmed that the VPP is a robust feature of slope walking (R2 > 0.975). The simulation reproduced the change in hip torque and trunk adaptations by modulating VPP position. Results of this study indicate that VPP position and trunk dynamics could afford stability and energy management on gentle slopes, but to robustly navigate steeper ramps, humans recruit a multi-joint strategy where the knee and ankle joints play a crucial role in managing the energetic demands of sloped terrain. Beyond advancing our understanding of locomotor control, these insights have practical implications for the design of exoskeletons that adapt to uneven terrain.

bioengineering↗

bioRxiv2021

The dynamics of touch sensing studied in a mass-spring-damper model of the skin

The mammalian skin is a densely innervated soft tissue where embedded neural mechanoreceptors report to the brain the mechanical events arising at its surface. Up to now, models of the transformations of these events into neural signals relied on quasistatic or viscoelastic mechanical models of the skin. Here, we employed a model which, in addition to elasticity and viscosity, accounted for mass to accurately reproduce the propagation of mechanical waves observed in vivo. Skin dynamics converted sensory inputs into rapidly evolving spatiotemporal patterns that magnified the information made available to a population of mechanoreceptors. Accounting for dynamics greatly enhanced the separability of tactile inputs and was efficient for a large range of mechanical parameter values. This advantage vanished when these parameters were set to approximate the quasistatic or viscoelastic cases.

neuroscience↗