Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Kinematics and muscle activity of pectoral fins in rainbow trout (Oncorhynchus mykiss) station holding in turbulent flow

Pectoral fins play a crucial role in fish locomotion. Despite fishes living in complex fluid environments that exist in rivers and tidal flows, the role of the pectoral fins in navigating turbulent flows is not well understood. This study investigated the kinematics and muscle activity of pectoral fins in rainbow trout as they held station in the unsteady flows behind a D-section cylinder. We observed two distinct pectoral fin behaviors, one during braking and the other during Kármán gaiting. These behaviors were correlated to whole-body movements in response to the hydrodynamic conditions of specific regions in the cylinder wake. Sustained fin extensions during braking, where the fin was held out to maintain its position away from the body and against the flow, were associated with the cessation of forward body velocity, where the fish avoided the suction region directly downstream of the cylinder. Transient fin extensions and retractions during Kármán gaiting controlled body movements in the cross-stream direction. These two fin behaviors had different patterns of muscle activity. All braking events required recruitment from both the abductor and adductor musculature to actively extend a pectoral fin. In contrast, over 50% of fin extension movements during Kármán gaiting proceed in the absence of muscle activity. We reveal that in unsteady fluid environments, pectoral fin movements are the result of a complex combination of passive and active mechanisms that deviate substantially from canonical labriform locomotion, the implications of which await further work on the integration of sensory and motor systems.

Why are biting flies attracted to blue objects?

Diurnal biting flies are strongly attracted to blue objects. This behaviour is widely exploited for fly control, but its functional significance is debated. It is hypothesized that blue objects resemble animal hosts; blue surfaces resemble shaded resting places; and blue attraction is a by-product of attraction to polarized light. We computed the fly photoreceptor signals elicited by a large sample of leaf and animal integument reflectance spectra, viewed under open/cloudy illumination and under woodland shade. We then trained artificial neural networks (ANNs) to distinguish animals from leaf backgrounds, and shaded from unshaded surfaces, in order to find the optimal means of doing so based upon the sensory information available to a fly. After training, we challenged ANNs to classify blue objects used in fly control. Trained ANNs could make both discriminations with high accuracy. They discriminated animals from leaves based upon blue-green photoreceptor opponency and commonly misclassified blue objects as animals. Meanwhile, they discriminated shaded from unshaded stimuli using achromatic cues and never misclassified blue objects as shaded. We conclude that blue-green opponency is the most effective means of discriminating animals from leaf backgrounds using a fly's sensory information, and that blue objects resemble animal hosts through such mechanisms.

Robot Programming from Fish Demonstrations

Fish are capable of learning complex relations found in their surroundings, and harnessing their knowledge may help to improve the autonomy and adaptability of robots. Here, we propose a novel learning from demonstration framework to generate fish-inspired robot control programs with as little human intervention as possible. The framework consists of six core modules: (1) task demonstration, (2) fish tracking, (3) analysis of fish trajectories, (4) acquisition of robot training data, (5) generating a perception-action controller, and (6) performance evaluation. We first describe these modules and highlight the key challenges pertaining to each one. We then present an artificial neural network for automatic fish tracking. The network detected fish successfully in 85% of the frames, and in these frames, its average pose estimation error was less than 0.04 body lengths. We finally demonstrate how the framework works through a case study focusing on a cue-based navigation task. Two low-level perception-action controllers were generated through the framework. Their performance was measured using two-dimensional particle simulations and compared against two benchmark controllers, which were programmed manually by a researcher. The fish-inspired controllers had excellent performance when the robot was started from the initial conditions used in fish demonstrations (>96% success rate), outperforming the benchmark controllers by at least 3%. One of them also had an excellent generalisation performance when the robot was started from random initial conditions covering a wider range of starting positions and heading angles (>98% success rate), again outperforming the benchmark controllers by 12%. The positive results highlight the utility of the framework as a research tool to form biological hypotheses on how fish navigate in complex environments and design better robot controllers on the basis of biological findings.

Fish-inspired segment models for undulatory steady swimming

Many aquatic animals swim by undulatory body movements and understanding the diversity of these movements could unlock the potential for designing better underwater robots. Here, we analyzed the steady swimming kinematics of a diverse group of fish species to investigate whether their undulatory movements can be represented using a series of interconnected multi-segment models, and if so, to identify the key factors driving the segment configuration of the models. Our results show that the steady swimming kinematics of fishes can be described successfully using parsimonious models, 83% of which had fewer than five segments. In these models, the anterior segments were significantly longer than the posterior segments, and there was a direct link between segment configuration and swimming kinematics, body shape, and Reynolds number. The models representing eel-like fishes with elongated bodies and fishes swimming at high Reynolds numbers had more segments and less segment length variability along the body than the models representing other fishes. These fishes recruited their anterior bodies to a greater extent, initiating the undulatory wave more anteriorly. Two shape parameters, related to axial and overall body thickness, predicted segment configuration with moderate to high success rate. We found that head morphology was a good predictor of its segment length. While there was a large variation in head segments, the length of tail segments was similar across all models. Given that fishes exhibited variable caudal fin shapes, the consistency of tail segments could be a result of an evolutionary constraint tuned for high propulsive efficiency. The bio-inspired multi-segment models presented in this study highlight the key bending points along the body and can be used to decide on the placement of actuators in fish-inspired robots, to model hydrodynamic forces in theoretical and computational studies, or for predicting muscle activation patterns during swimming.

Body Caudal Undulation measured by Soft Sensors and emulated by Soft Artificial Muscles

We propose the use of bio-inspired robotics equipped with soft sensor technologies to gain a better understanding of the mechanics and control of animal movement. Soft robotic systems can be used to generate new hypotheses and uncover fundamental principles underlying animal locomotion and sensory capabilities, which could subsequently be validated using living organisms. Physical models increasingly include lateral body movements, notably back and tail bending, which are necessary for horizontal plane undulation in model systems ranging from fish to amphibians and reptiles. We present a comparative study of the use of physical modeling in conjunction with soft robotics and integrated soft and hyperelastic sensors to monitor local pressures, enabling local feedback control, and discuss issues related to understanding the mechanics and control of undulatory locomotion. A parallel approach combining live animal data with biorobotic physical modeling promises to be beneficial for gaining a better understanding of systems in motion.

Automatic segmentation of fish midlines for optimizing robot design

While fish use continuous and flexible bodies to propel themselves, fish robots are often made from interconnected segments. How many segments do robots need to represent fish movements accurately? We propose a new method to automatically determine parsimonious robot models from actual fish data. We first identify key bending points (i.e., joint positions) along the body and then study the concerted movement of the segments so that the difference between actual fish and modelled bending kinematics is minimized. To demonstrate the utility of our method, we analyse the steady swimming kinematics of 10 morphologically distinct fish species. Broadly classified as sub-carangiform (e.g., rainbow trout) and carangiform (e.g., crevalle jack) swimmers, these species exhibit variations in the way they undulate when traditional parameters (including head and tail beat amplitudes, body wavelength and maximum curvature along the body) are considered. We show that five segments are sufficient to describe the kinematics with at least 99% accuracy. For optimal performance, segments should progressively get shorter towards the tail. We also show that locations where bending moments are applied vary among species, possibly because of differences in morphology. More specifically, we find that wider fish have shorter head segments. We discover that once bending points are factored in, the kinematics differences observed in these species collapse into a single undulatory pattern. The amplitude and timing of how body segments move entirely depend on their respective joint positions along the body. Head and body segments are also coupled in a timely manner, which depends on the position of the most anterior joint. Our findings provide a mechanistic understanding of how morphology relates to kinematics and highlight the importance of head control, which is often overlooked in current robot designs.

Oxygen consumption of drift-feeding rainbow trout: the energetic tradeoff between locomotion and feeding in flow

To forage in fast, turbulent flow environments where prey is abundant, fishes must deal with the high associated costs of locomotion. Prevailing theory suggests that many species exploit hydrodynamic refuges to minimize the cost of locomotion while foraging. Here, we challenge this theory based on direct oxygen consumption measurements of drift-feeding trout (Oncorhynchus mykiss) foraging in the freestream and from behind a flow refuge at velocities up to 100 cm s^-1 We demonstrate that refuging is not energetically beneficial when foraging in fast flows because of a high attack cost and low prey capture success associated with leaving a station-holding refuge to intercept prey. By integrating optimum foraging theory with empirical data from respirometry and video tracking, we developed a mathematical model to predict when drift-feeding fishes should exploit or avoid refuges based on prey density, size and flow velocity. Our optimum foraging and refuging model provides new mechanistic insights into locomotor costs, habitat use and prey choice of fish foraging in current-swept habitats.

Behavior, Electrophysiology, and Robotics Experiments to Study Lateral Line Sensing in Fishes

The lateral line system is a sensory system unique to fishes and amphibians. It is composed of distributed mechanosensory hair cell organs on the head and body (neuromasts), which are sensitive to pressure gradients and water movements. Over the last decade, we have pursued an interdisciplinary approach by combining behavioral, electrophysiology, and robotics experiments to study this fascinating sensory system. In behavioral and electrophysiology experiments, we have studied the larval lateral line system in the model genetic organism, zebrafish (Danio rerio). We found that the lateral line system, even in 5-day-old larvae, is involved in an array of behaviors that are critical to survival, and the deflection of a single neuromast can elicit a swimming response. In robotics experiments, we used a range of physical models with distributed pressure sensors to better understand the hydrodynamic environments from the local perspective of a fish or robot. So far, our efforts have focused on extracting control-related information for a range of application scenarios including characterizing unsteady flows such as Kármán vortex streets for station holding. We also used robot models to test biological hypotheses on how morphology and movement of fishes affect lateral line sensing. Overall, with this review we aim to increase the visibility and accessibility of this multi-disciplinary research approach.

Head width influences flow sensing by the lateral line canal system in fishes

The architecture of the cephalic lateral line canal system, with distinct lines for the supraorbital, infraorbital and mandibular canals, is highly conserved among fish species. Because these canals lie on a cranial platform, the sensory input they receive is expected to change based on how flow interacts with the head and how the canal pores are spatially distributed. In this study, we explored how head width, a trait that can vary greatly between species and across ontogeny, affects flow sensing. We inserted pressure sensors into physical fish head models of varying widths (narrow, intermediate and wide) and placed these models in steady and vortical flows. We measured sensory performance in terms of detecting flow parameters (flow speed, vortex shedding frequency and cylinder diameter), sensitivity (change in pressure gradient as a function of flow speed) and signal-to-noise ratio (SNR; strength of vortex shedding frequency with respect to background). Our results show that in all model heads the amount of hydrodynamic information was maximized at the anterior region regardless of what metric we used to evaluate the sensory performance. In addition, we discovered that all model heads had the highest SNR for vortices at the intermediate flow speeds but that each head width passively optimized the SNR for different sized vortices, which may have implications for refuge and prey seeking. Our results provide insight into the sensory ecology of fishes and have implications for the design of autonomous underwater vehicles.

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

In recent years, there has been a growing interest in designing multi-robot systems (hereafter MRSs) to provide cost effective, fault-tolerant and reliable solutions to a variety of automated applications. Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position to a final destination. To achieve cooperative object transport, a wide range of transport, coordination and control strategies have been proposed. Our goal is to provide a comprehensive summary for this relatively heterogeneous and fast-growing body of scientific literature. While distilling the information, we purposefully avoid using hierarchical dichotomies, which have been traditionally used in the field of MRSs. Instead, we employ a coarse-grain approach by classifying each study based on the transport strategy used; pushing-only, grasping and caging. We identify key design constraints that may be shared among these studies despite considerable differences in their design methods. In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs. Overall, we hope to increasethe visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectively.

Fish Swimming in a Kármán Vortex Street: Kinematics, Sensory Biology and Energetics

Fishes often live in environments characterized by complex flows. To study the mechanisms of how fishes interact with unsteady flows, the periodic shedding of vortices behind cylinders has been employed to great effect. In particular, fishes that hold station in a vortex street (i.e., Kármán gaiting) show swimming kinematics that are distinct from their patterns of motion during freestream swimming in uniform flows, although both behaviors can be modeled as an undulatory body wave. Kármán gait kinematics are largely preserved across flow velocities. Larger fish have a shorter body wavelength and slower body wave speed than smaller fish, in contrast to freestream swimming where body wavelength and wave speed increases with size. The opportunity for Kármán gaiting only occurs under specific conditions of flow velocity and depends on the length of the fish; this is reflected in the highest probability of Kármán gaiting at intermediate flow velocities. Fish typically Kármán gait in a region of the cylinder wake where the velocity deficit is about 40% of the nominal flow. The lateral line plays a role in tuning the kinematics of the Kármán gait, since blocking it leads to aberrant kinematics. Vision allows fish to maintain a consistent position relative to the cylinder. In the dark, fish do not show the same preference to hold station behind a cylinder though Kármán gait kinematics are the same. When oxygen consumption level is measured, it reveals that Kármán gaiting represents about half of the cost of swimming in the freestream.

Refuging rainbow trout selectively exploit flows behind tandem cylinders

Fishes may exploit environmental vortices to save in the cost of locomotion. Previous work has investigated fish refuging behind a single cylinder in current, a behavior termed the Kármán gait. However, current-swept habitats often contain aggregations of physical objects, and it is unclear how the complex hydrodynamics shed from multiple structures affect refuging in fish. To begin to address this, we investigated how the flow fields produced by two D-shaped cylinders arranged in tandem affect the ability of rainbow trout (Oncorhynchus mykiss) to Kármán gait. We altered the spacing of the two cylinders from l/D of 0.7 to 2.7 (where l=downstream spacing of cylinders and D=cylinder diameter) and recorded the kinematics of trout swimming behind the cylinders with high-speed video at Re=10,000-55,000. Digital particle image velocimetry showed that increasing l/D decreased the strength of the vortex street by an average of 53% and decreased the frequency that vortices were shed by ∼20% for all speeds. Trout were able to Kármán gait behind all cylinder treatments despite these differences in the downstream wake; however, they Kármán gaited over twice as often behind closely spaced cylinders (l/D=0.7, 1.1, and 1.5). Computational fluid dynamics simulations show that when cylinders are widely spaced, the upstream cylinder generates a vortex street that interacts destructively with the downstream cylinder, producing weaker, more widely spaced and less-organized vortices that discourage Kármán gaiting. These findings are poised to help predict when fish may seek refuge in natural habitats based on the position and arrangement of stationary objects.

V67L Mutation Fills an Internal Cavity To Stabilize RecA Mtu Intein

Inteins mediate protein splicing, which has found extensive applications in protein science and biotechnology. In the Mycobacterium tuberculosis RecA mini-mini intein (ΔΔIhh), a single valine to leucine substitution at position 67 (V67L) dramatically increases intein stability and activity. However, crystal structures show that the V67L mutation causes minimal structural rearrangements, with a root-mean-square deviation of 0.2 Å between ΔΔIhh-V67 and ΔΔIhh-L67. Thus, the structural mechanisms for V67L stabilization and activation remain poorly understood. In this study, we used intrinsic tryptophan fluorescence, high-pressure nuclear magnetic resonance (NMR), and molecular dynamics (MD) simulations to probe the structural basis of V67L stabilization of the intein fold. Guanidine hydrochloride denaturation monitored by fluorescence yielded free energy changes (ΔG_f°) of -4.4 and -6.9 kcal mol^-1 for ΔΔIhh-V67 and ΔΔIhh-L67, respectively. High-pressure NMR showed that ΔΔIhh-L67 is more resistant to pressure-induced unfolding than ΔΔIhh-V67 is. The change in the volume of folding (ΔV_f) was significantly larger for V67 (71 ± 2 mL mol^-1) than for L67 (58 ± 3 mL mol^-1) inteins. The measured difference in ΔV_f (13 ± 3 mL mol^-1) roughly corresponds to the volume of the additional methylene group for Leu, supporting the notion that the V67L mutation fills a nearby cavity to enhance intein stability. In addition, we performed MD simulations to show that V67L decreases side chain dynamics and conformational entropy at the active site. It is plausible that changes in cavities in V67L can also mediate allosteric effects to change active site dynamics and enhance intein activity.

Synaptic Ribbons Require Ribeye for Electron Density, Proper Synaptic Localization, and Recruitment of Calcium Channels

Synaptic ribbons are structures made largely of the protein Ribeye that hold synaptic vesicles near release sites in non-spiking cells in some sensory systems. Here, we introduce frameshift mutations in the two zebrafish genes encoding for Ribeye and thus remove Ribeye protein from neuromast hair cells. Despite Ribeye depletion, vesicles collect around ribbon-like structures that lack electron density, which we term "ghost ribbons." Ghost ribbons are smaller in size but possess a similar number of smaller vesicles and are poorly localized to synapses and calcium channels. These hair cells exhibit enhanced exocytosis, as measured by capacitance, and recordings from afferent neurons post-synaptic to hair cells show no significant difference in spike rates. Our results suggest that Ribeye makes up most of the synaptic ribbon density in neuromast hair cells and is necessary for proper localization of calcium channels and synaptic ribbons.

Fish optimize sensing and respiration during undulatory swimming

Previous work in fishes considers undulation as a means of propulsion without addressing how it may affect other functions such as sensing and respiration. Here we show that undulation can optimize propulsion, flow sensing and respiration concurrently without any apparent tradeoffs when head movements are coupled correctly with the movements of the body. This finding challenges a long-held assumption that head movements are simply an unintended consequence of undulation, existing only because of the recoil of an oscillating tail. We use a combination of theoretical, biological and physical experiments to reveal the hydrodynamic mechanisms underlying this concerted optimization. Based on our results we develop a parsimonious control architecture that can be used by both undulatory animals and machines in dynamic environments.

A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow

For underwater vehicles to successfully detect and navigate turbulent flows, sensing the fluid interactions that occur is required. Fish possess a unique sensory organ called the lateral line. Sensory units called neuromasts are distributed over their body, and provide fish with flow-related information. In this study, a three-dimensional fish-shaped head, instrumented with pressure sensors, was used to investigate the pressure signals for relevant hydrodynamic stimuli to an artificial lateral line system. Unsteady wakes were sensed with the objective to detect the edges of the hydrodynamic trail and then explore and characterize the periodicity of the vorticity. The investigated wakes (Kármán vortex streets) were formed behind a range of cylinder diameter sizes (2.5, 4.5 and 10 cm) and flow velocities (9.9, 19.6 and 26.1 cm s(-1)). Results highlight that moving in the flow is advantageous to characterize the flow environment when compared with static analysis. The pressure difference from foremost to side sensors in the frontal plane provides us a useful measure of transition from steady to unsteady flow. The vortex shedding frequency (VSF) and its magnitude can be used to differentiate the source size and flow speed. Moreover, the distribution of the sensing array vertically as well as the laterally allows the Kármán vortex paired vortices to be detected in the pressure signal as twice the VSF.

Frequency response properties of primary afferent neurons in the posterior lateral line system of larval zebrafish

The ability of fishes to detect water flow with the neuromasts of their lateral line system depends on the physiology of afferent neurons as well as the hydrodynamic environment. Using larval zebrafish (Danio rerio), we measured the basic response properties of primary afferent neurons to mechanical deflections of individual superficial neuromasts. We used two types of stimulation protocols. First, we used sine wave stimulation to characterize the response properties of the afferent neurons. The average frequency-response curve was flat across stimulation frequencies between 0 and 100 Hz, matching the filtering properties of a displacement detector. Spike rate increased asymptotically with frequency, and phase locking was maximal between 10 and 60 Hz. Second, we used pulse train stimulation to analyze the maximum spike rate capabilities. We found that afferent neurons could generate up to 80 spikes/s and could follow a pulse train stimulation rate of up to 40 pulses/s in a reliable and precise manner. Both sine wave and pulse stimulation protocols indicate that an afferent neuron can maintain their evoked activity for longer durations at low stimulation frequencies than at high frequencies. We found one type of afferent neuron based on spontaneous activity patterns and discovered a correlation between the level of spontaneous and evoked activity. Overall, our results establish the baseline response properties of lateral line primary afferent neurons in larval zebrafish, which is a crucial step in understanding how vertebrate mechanoreceptive systems sense and subsequently process information from the environment.

Afferent and motoneuron activity in response to single neuromast stimulation in the posterior lateral line of larval zebrafish

The lateral line system of fishes contains mechanosensory receptors along the body surface called neuromasts, which can detect water motion relative to the body. The ability to sense flow informs many behaviors, such as schooling, predator avoidance, and rheotaxis. Here, we developed a new approach to stimulate individual neuromasts while either recording primary sensory afferent neuron activity or swimming motoneuron activity in larval zebrafish (Danio rerio). Our results allowed us to characterize the transfer functions between a controlled lateral line stimulus, its representation by primary sensory neurons, and its subsequent behavioral output. When we deflected the cupula of a neuromast with a ramp command, we found that the connected afferent neuron exhibited an adapting response which was proportional in strength to deflection velocity. The maximum spike rate of afferent neurons increased sigmoidally with deflection velocity, with a linear range between 0.1 and 1.0 μm/ms. However, spike rate did not change when the cupula was deflected below 8 μm, regardless of deflection velocity. Our findings also reveal an unexpected sensitivity in the larval lateral line system: stimulation of a single neuromast could elicit a swimming response which increased in reliability with increasing deflection velocities. At high deflection velocities, we observed that lateral line evoked swimming has intermediate values of burst frequency and duty cycle that fall between electrically evoked and spontaneous swimming. An understanding of the sensory capabilities of a single neuromast will help to build a better picture of how stimuli are encoded at the systems level and ultimately translated into behavior.

A kinematic model of Kármán gaiting in rainbow trout

A mechanistic understanding of how fishes swim in unsteady flows is challenging despite its prevalence in nature. Previous kinematic studies of fish Kármán gaiting in a vortex street behind a cylinder only report time-averaged measurements, precluding our ability to formally describe motions on a cycle-by-cycle basis. Here we present the first analytical model that describes the swimming kinematics of Kármán gaiting trout with 70-90% accuracy. We found that body bending kinematics can be modelled with a travelling wave equation, which has also been shown to accurately model free-stream swimming kinematics. However, free-stream swimming and Kármán gaiting are separated in the parameter space; the amplitude, wavelength and frequency values of the traveling wave equation are substantially different for each behavior. During Kármán gaiting, the wave is initiated at the body center, which is 0.2L (where L is total body length) further down the body compared with the initiation point in free-stream swimming. The wave travels with a constant speed, which is higher than the nominal flow speed just as in free-stream swimming. In addition to undulation, we observed that Kármán gaiting fish also exhibit substantial lateral translations and body rotations, which can constitute up to 75% of the behavior. These motions are periodic and their frequencies also match the vortex shedding frequency. There is an inverse correlation between head angle and body angle: when the body rotates in one direction, the head of the fish turns into the opposite direction. Our kinematic model mathematically describes how fish swim in vortical flows in real time and provides a platform to better understand the effects of flow variations as well as the contribution of muscle activity during corrective motions.

The effect of flow speed and body size on Kármán gait kinematics in rainbow trout

We have little understanding of how fish hold station in unsteady flows. Here, we investigated the effect of flow speed and body size on the kinematics of rainbow trout Kármán gaiting behind a 5 cm diameter cylinder. We established a set of criteria revealing that not all fish positioned in a vortex street are Kármán gaiting. By far the highest probability of Kármán gaiting occurred at intermediate flow speeds between 30 and 70 cm s(-1). We show that trout Kármán gait in a region of the cylinder wake where the velocity deficit is about 40% of the nominal flow. We observed that the relationships between certain kinematic and flow variables are largely preserved across flow speeds. Tail-beat frequency matched the measured vortex shedding frequency, which increased linearly with flow speed. Body wave speed was about 25% faster than the nominal flow velocity. At speeds where fish have a high probability of Kármán gaiting, body wavelength was about 25% longer than the cylinder wake wavelength. Likewise, the lateral (i.e. cross-stream) amplitude of the tail tip was about 50% greater than the expected lateral spacing of the cylinder vortices, while the body center amplitude was about 70% less. Lateral body center acceleration increased quadratically with speed. Head angle decreased with flow speed. While these values are different from those found in fish swimming in uniform flow, the strategy for locomotion is the same; fish adjust to increasing flow by increasing their tail-beat frequency. Body size also played a role in Kármán gaiting kinematics. Tail-beat amplitudes of Kármán gaiting increased with body size, as in freestream swimming, but were almost three times larger in magnitude. Larger fish had a shorter body wavelength and slower body wave speed than smaller fish, which is a surprising result compared with freestream swimming, where body wavelength and wave speed increased with size. In contrast to freestream swimming, tail-beat frequency for Kármán gaiting fish did not depend on body size and was a function of the vortex shedding frequency.

Self-motion effects on hydrodynamic pressure sensing: part I. forward-backward motion

In underwater locomotion, extracting meaningful information from local flows is as desirable as it is challenging, due to complex fluid-structure interaction. Sensing and motion are tightly interconnected; hydrodynamic signals generated by the external stimuli are modified by the self-generated flow signals. Given that very little is known about self-generated signals, we used onboard pressure sensors to measure the pressure profiles over the head of a fusiform-shape craft while moving forward and backward harmonically. From these measurements we obtained a second-order polynomial model which incorporates the velocity and acceleration of the craft to estimate the surface pressure within the swimming range up to one body length/second (L s(-1)). The analysis of the model reveals valuable insights into the temporal and spatial changes of the pressure intensity as a function of craft's velocity. At low swimming velocities (<0.2 L s(-1)) the pressure signals are more sensitive to the acceleration of the craft than its velocity. However, the inertial effects gradually become less important as the velocity increases. The sensors on the front part of the craft are more sensitive to its movements than the sensors on the sides. With respect to the hydrostatic pressure measured in still water, the pressure detected by the foremost sensor reaches values up to 300 Pa at 1 L s(-1) swimming velocity, whereas the pressure difference between the foremost sensor and the next one is less than 50 Pa. Our results suggest that distributed pressure sensing can be used in a bimodal sensing strategy. The first mode detects external hydrodynamic events taking place around the craft, which requires minimal sensitivity to the self-motion of the craft. This can be accomplished by moving slowly with a constant velocity and by analyzing the pressure gradient as opposed to absolute pressure recordings. The second mode monitors the self-motion of the craft. It is shown here that distributed pressure sensing can be used as a speedometer to measure the craft's velocity.

Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows

With the overall goal being a better understanding of the sensing environment from the local perspective of a situated agent, we studied uniform flows and Kármán vortex streets in a frame of reference relevant to a fish or swimming robot. We visualized each flow regime with digital particle image velocimetry and then took local measurements using a rigid body with laterally distributed parallel pressure sensor arrays. Time and frequency domain methods were used to characterize hydrodynamically relevant scenarios in steady and unsteady flows for control applications. Here we report that a distributed pressure sensing mechanism has the capability to discriminate Kármán vortex streets from uniform flows, and determine the orientation and position of the platform with respect to the incoming flow and the centre axis of the Kármán vortex street. It also enables the computation of hydrodynamic features which may be relevant for a robot while interacting with the flow, such as vortex shedding frequency, vortex travelling speed and downstream distance between vortices. A Kármán vortex street was distinguished in this study from uniform flows by analysing the magnitude of fluctuations present in the sensor measurements and the number of sensors detecting the same dominant frequency. In the Kármán vortex street the turbulence intensity was 30% higher than that in the uniform flow and the sensors collectively sensed the vortex shedding frequency as the dominant frequency. The position and orientation of the sensor platform were determined via a comparative analysis between laterally distributed sensor arrays; the vortex travelling speed was estimated via a cross-correlation analysis among the sensors.

What information do Kármán streets offer to flow sensing?

In this work, we focus on biomimetic lateral line sensing in Kármán vortex streets. After generating a Kármán street in a controlled environment, we examine the hydrodynamic images obtained with digital particle image velocimetry (DPIV). On the grounds that positioning in the flow and interaction with the vortices govern bio-inspired underwater locomotion, we inspect the fluid in the swimming robot frame of reference. We spatially subsample the flow field obtained using DPIV to emulate the local flow around the body. In particular, we look at various sensor configurations in order to reliably identify the vortex shedding frequency, wake wavelength and downstream flow speed. Moreover, we propose methods that differentiate between being in and out of the Kármán street with >70% accuracy, distinguish right from left with respect to Kármán vortex street centreline (>80%) and highlight when the sensor system enters the vortex formation zone (>75%). Finally, we present a method that estimates the relative position of a sensor array with respect to the vortex formation point within 15% error margin.