Understanding the influence of context on real-world walking energetics.

Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in a variety of contexts that can elicit different walking strategies, and may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N=17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Gross and net cost of transport were calculated for each participant, and were used to identify energetically optimal walking speed ranges for each participant. The proportion of real-world steady-state stride speeds within these ranges (gross and net) were identified for all data and for each context. We found that energetically optimal speeds predicted by gross cost of transport were more predictive of walking speeds used during daily life than speeds that would minimize net cost of transport. On average, 82.2% of all steady-state stride speeds were energetically optimal for gross cost of transport for all contexts and participants, while only 45.6% were energetically optimal for net cost of transport. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.

Classification of human walking context using a single-point accelerometer.

Real-world walking data offers rich insights into a person's mobility. Yet, daily life variations can alter these patterns, making the data challenging to interpret. As such, it is essential to integrate context for the extraction of meaningful information from real-world movement data. In this work, we leveraged the relationship between the characteristics of a walking bout and context to build a classification algorithm to distinguish between indoor and outdoor walks. We used data from 20 participants wearing an accelerometer on the thigh over a week. Their walking bouts were isolated and labeled using GPS and self-reporting data. We trained and validated two machine learning models, random forest and ensemble Support Vector Machine, using a leave-one-participant-out validation scheme on 15 subjects. The 5 remaining subjects were used as a testing set to choose a final model. The chosen model achieved an accuracy of 0.941, an F1-score of 0.963, and an AUROC of 0.931. This validated model was then used to label the walks from a different dataset with 15 participants wearing the same accelerometer. Finally, we characterized the differences between indoor and outdoor walks using the ensemble of the data. We found that participants walked significantly faster, longer, and more continuously when walking outdoors compared to indoors. These results demonstrate how movement data alone can be used to obtain accurate information on important contextual factors. These factors can then be leveraged to enhance our understanding and interpretation of real-world movement data, providing deeper insights into a person's health.

Subtractive Patterning of Nanoscale Thin Films Using Acid-Based Electrohydrodynamic-Jet Printing.

As an alternative to traditional photolithography, printing processes are widely explored for the patterning of customizable devices. However, to date, the majority of high-resolution printing processes for functional nanomaterials are additive in nature. To complement additive printing, there is a need for subtractive processes, where the printed ink results in material removal, rather than addition. In this study, a new subtractive patterning approach that uses electrohydrodynamic-jet (e-jet) printing of acid-based inks to etch nanoscale zinc oxide (ZnO) thin films deposited using atomic layer deposition (ALD) is introduced. By tuning the printing parameters, the depth and linewidth of the subtracted features can be tuned, with a minimum linewidth of 11 µm and a tunable channel depth with ≈5 nm resolution. Furthermore, by tuning the ink composition, the volatility and viscosity of the ink can be adjusted, resulting in variable spreading and dissolution dynamics at the solution/film interface. In the future, acid-based subtractive patterning using e-jet printing can be used for rapid prototyping or customizable manufacturing of functional devices on a range of substrates with nanoscale precision.

Dynamics and energetics of bottlenose dolphin (Tursiops truncatus) fluke-and-glide gait.

Intermittent locomotion composed of periods of active flapping/stroking followed by inactive gliding has been observed with species that inhabit both aerial and marine environments. However, studies on the energetic benefits of a fluke-and-glide (FG) gait during horizontal locomotion are limited for dolphins. This work presents a physics-based model of FG gait and an analysis of the associated cost of transport for bottlenose dolphins (Tursiops truncatus). New gliding drag coefficients for the model were estimated using measured data from free-swimming bottlenose dolphins. The data-driven approach used kinematic measurement from 84 h of biologging tag data collected from three animals to estimate the coefficients. A set of 532 qualifying gliding events were automatically extracted for estimation of the gliding drag coefficient. Next, data from 783 FG bouts were parameterized and used with the model-based dynamic analysis to investigate the cost benefits of FG gait. Experimental results indicate that FG gait was preferred at speeds of ∼2.2-2.7 m s-1. Observed FG bouts had an average duty factor of 0.45 and a gliding duration of 5 s. The average associated metabolic cost of transport (COT) and mechanical cost of transport (MECOT) of FG gait are 2.53 and 0.35 J m-1 kg-1, respectively, at the preferred speeds. This corresponded to a respective 18.9% and 27.1% reduction in cost when compared with model predictions of continuous fluking gait at the same average bout speed. Average thrust was positively correlated with fluking frequency and amplitude as animals accelerated during the FG bouts, whereas fluking frequency and amplitude were negatively correlated for a given thrust range. These results suggest that FG gait enhances the horizontal swimming efficiency of bottlenose dolphins and provides new insights into the gait dynamics of these animals.

Overcoming Challenges Associated with Developing Industrial Prognostics and Health Management Solutions.

The development of prognostics and health management solutions in the manufacturing industry has lagged behind academic advances due to a number of practical challenges. This work proposes a framework for the initial development of industrial PHM solutions that is based on the system development life cycle commonly used for software-based applications. Methodologies for completing the planning and design stages, which are critical for industrial solutions, are presented. Two challenges that are inherent to health modeling in manufacturing environments, data quality and modeling systems that experience trend-based degradation, are then identified and methods to overcome them are proposed. Additionally included is a case study documenting the development of an industrial PHM solution for a hyper compressor at a manufacturing facility operated by The Dow Chemical Company. This case study demonstrates the value of the proposed development process and provides guidelines for utilizing it in other applications.

Three-Dimensional Arenas for the Assessment of Caenorhabditis elegans Behavior.

Caenorhabditis elegans nematode is a well-established model organism in numerous fields of experimental biology. In nature, C. elegans live in a rich three-dimensional (3D) environment. However, their behavior has been assessed almost exclusively on the open, flat surface of nematode growth medium (NGM) plates, the golden standard for C. elegans culture in the laboratory. We present two methods to build 3D behavioral arenas for C. elegans, by casting and by directly 3D-printing NGM hydrogel. The latter is achieved using a highly customized fused deposition modeling (FDM) 3D printer, modified to employ NGM hydrogel as ink. The result is the advancement of 3D complexity of behavioral assays. To demonstrate the potential of our method, we use the 3D-printed arenas to assess C. elegans physical barriers crossing. C. elegans decision to cross physical obstacles is affected by aging, physiological status (i.e., starvation), and prior experience. The 3D-printed structures can be used to spatially confine C. elegans behaviors, that is, egg laying. We consider these findings a decisive step toward characterizing C. elegans 3D behavior, an area long overlooked due to technical constrains. We envision our method of 3D-printing NGM arenas as a powerful tool in behavioral neurogenetics, neuroethology, and invertebrate model organisms' neurobiology.

Tag-based estimates of bottlenose dolphin swimming behavior and energetics.

Current estimates of marine mammal hydrodynamic forces tend to be made using camera-based kinematic data for a limited number of fluke strokes during a prescribed swimming task. In contrast, biologging tag data yield kinematic measurements from thousands of strokes, enabling new insights into swimming behavior and mechanics. However, there have been limited tag-based estimates of mechanical work and power. In this work, we investigated bottlenose dolphin (Tursiops truncatus) swimming behavior using tag-measured kinematics and a hydrodynamic model to estimate propulsive power, work and cost of transport. Movement data were collected from six animals during prescribed straight-line swimming trials to investigate swimming mechanics over a range of sustained speeds (1.9-6.1 m s-1). Propulsive power ranged from 66 W to 3.8 kW over 282 total trials. During the lap trials, the dolphins swam at depths that mitigated wave drag, reducing overall drag throughout these mid- to high-speed tasks. Data were also collected from four individuals during undirected daytime (08:30-18:00 h) swimming to examine how self-selected movement strategies are used to modulate energetic efficiency and effort. Overall, self-selected swimming speeds (individual means ranging from 1.0 to 1.96 m s-1) tended to minimize cost of transport, and were on the lower range of animal-preferred speeds reported in literature. The results indicate that these dolphins moderate propulsive effort and efficiency through a combination of speed and depth regulation. This work provides new insights into dolphin swimming behavior in both prescribed tasks and self-selected swimming, and presents a path forward for continuous estimates of mechanical work and power from wild animals.

Pose-gait analysis for cetacean biologging tag data.

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations, but how best to characterize gait from tag data remains an open question. Further, the location and orientation of a tag on an animal in the field are variable and can change multiple times during a deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined for analysis. Currently, custom scripts that involve species-specific heuristics tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. Swimming gait is composed of a sequence of body poses that have a specific spatial pattern, and tag-based measurements of this pattern can be utilized to determine the relative orientation of the tag. This work presents an automated data processing pipeline (and software) that takes advantage of these patterns to 1) Identify relative motion between the tag and animal; 2) Estimate the relative orientation of the tag wrt the animal using a data-driven approach; and 3) Calculate gait parameters that are stable and invariant to animal pose. Validation results from bottlenose dolphin tag data show that the average relative orientation error (tag wrt the body) after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for detecting instances of relative motion in the dolphin data were 0.87 and 0.89, respectively. Tag data from humpback and beluga whales were then used to demonstrate how the gait analysis can be used to enhance tag-based investigations of movement and behavior. The MATLAB source code and data presented in the paper are publicly available (https://github.com/ding-z/cetacean-pose-gait-analysis.git), along with suggested best practices.

Investigating walking speed variability of young adults in the real world.

BACKGROUND: Walking speed strongly correlates with health outcomes, making accurate assessment essential for clinical evaluations. However, assessments tend to be conducted over short distances, often in a laboratory or clinical setting, and may not capture natural walking behavior. To address this gap, the following questions are investigated in this work: Is walking speed significantly influenced by the continuity and duration of a walking bout? Can preferred walking speed be inferred by grouping walking bouts using duration and continuity? METHODS: We collected two weeks of continuous data from fifteen healthy young adults using a thigh-worn accelerometer and a heart rate monitor. Walking strides were identified and grouped into walking periods. We quantified the duration and the continuity of each walking period. Continuity is used to parameterize changes in stepping rate related to pauses during a bout of walking. Finally, we analyzed the influence of duration and continuity on estimates of stride speed, and examined how the distribution of walking speed varies depending on different walking modes (defined by duration and continuity). RESULTS: We found that continuity and duration can be used to explain some of the variability in real-world walking speed (p<0.001). Speeds estimated from long continuous walks with many strides (42% of all recorded strides) had the lowest standard deviation. Walking speed during these bouts was 1.41ms-1 (SD = 0.26ms-1). SIGNIFICANCE: Walking behavior in the real world is largely variable. Features of real-world walks, like duration and continuity, can be used to explain some of the variability observed in walking speed. As such, we recommend using long continuous walks to confidently isolate the preferred walking behavior of an individual.

Integrating Structural Colors with Additive Manufacturing Using Atomic Layer Deposition.

We demonstrate tunable structural color patterns that span the visible spectrum using atomic layer deposition (ALD). Asymmetric metal-dielectric-metal structures were sequentially deposited with nickel, zinc oxide, and a thin copper layer to form an optical cavity. The color response was precisely adjusted by tuning the zinc oxide (ZnO) thickness using ALD, which was consistent with model predictions. Owing to the conformal nature of ALD, this allows for uniform and tunable coloration of non-planar three-dimensional (3D) objects, as exemplified by adding color to 3D-printed parts produced by metal additive manufacturing. Proper choice of inorganic layered structures and materials allows the structural color to be stable at elevated temperatures, in contrast to traditional paints. To print multiple colors on a single sample, polymer inhibitors were patterned in a desired geometry using electrohydrodynamic jet (e-jet) printing, followed by area-selective ALD in the unpassivated regions. The ability to achieve 3D color printing, both at the micro- and macroscales, provides a new pathway to tune the optical and aesthetic properties during additive manufacturing.

Computer-vision object tracking for monitoring bottlenose dolphin habitat use and kinematics.

This research presents a framework to enable computer-automated observation and monitoring of bottlenose dolphins (Tursiops truncatus) in a zoo environment. The resulting approach enables detailed persistent monitoring of the animals that is not possible using manual annotation methods. Fixed overhead cameras were used to opportunistically collect ∼100 hours of observations, recorded over multiple days, including time both during and outside of formal training sessions, to demonstrate the viability of the framework. Animal locations were estimated using convolutional neural network (CNN) object detectors and Kalman filter post-processing. The resulting animal tracks were used to quantify habitat use and animal kinematics. Additionally, Kolmogorov-Smirnov analyses of the swimming kinematics were used in high-level behavioral mode classification. The object detectors achieved a minimum Average Precision of 0.76, and the post-processed results yielded 1.24 × 107 estimated dolphin locations. Animal kinematic diversity was found to be lowest in the morning and peaked immediately before noon. Regions of the zoo habitat displaying the highest activity levels correlated to locations associated with animal care specialists, conspecifics, or enrichment. The work presented here demonstrates that CNN object detection is viable for large-scale marine mammal tracking, and results from the proposed framework will enable future research that will offer new insights into dolphin behavior, biomechanics, and how environmental context affects movement and activity.

The effect of rotational speed on ankle-foot orthosis properties.

Ankle-foot orthoses (AFOs) are devices that support ankle motion. An AFO's sagittal plane rotational stiffness can affect gait kinematics. Because AFOs are often made from viscoelastic materials, their properties may vary at different walking speeds. The influence of rotational speed on AFO properties has not been thoroughly investigated. Therefore, the purpose of this study was to determine the impact of rotational speed on AFO stiffness about the ankle. We tested a sample of one thermoplastic off-the-shelf AFO and two 3-D printed carbon fiber enforced nylon AFOs. Each AFO's dynamic resistance torque was measured as it was flexed at five speeds (5-100 °/s) using a custom-built measurement apparatus. We compared loading stiffness, neutral angle, and energy dissipation parameters for each AFO across speeds. Parameter values were generally greater at higher speeds. These effects were statistically significant for all AFOs (p≤0.002). However, differences in AFO stiffness and neutral angle across speeds were quite small (<0.6 Nm/° and <2.2 °). Changes in the thermoplastic AFO's stiffness were lower than the minimum detectable difference. Energy dissipation, as indicated by hysteresis area, increased by up to 6.3 J (about 250%) at the highest speed. This demonstrates that AFO flexion speed can influence the properties of different AFOs over the range typically achieved in human walking. Future work should assess whether the observed small variations of stiffness and neutral angle have a clinically meaningful impact on user performance, as well as explore effects of angular speed on a variety of AFO materials and designs.

Estimating Walking Speed in the Wild.

An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s -1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.

Area-Selective Atomic Layer Deposition Patterned by Electrohydrodynamic Jet Printing for Additive Manufacturing of Functional Materials and Devices.

There is an increasing interest in additive nanomanufacturing processes, which enable customizable patterning of functional materials and devices on a wide range of substrates. However, there are relatively few techniques with the ability to directly 3D print patterns of functional materials with sub-micron resolution. In this study, we demonstrate the use of additive electrohydrodynamic jet (e-jet) printing with an average line width of 312 nm, which acts as an inhibitor for area-selective atomic layer deposition (AS-ALD) of a range of metal oxides. We also demonstrate subtractive e-jet printing with solvent inks that dissolve polymer inhibitor layers in specific regions, which enables localized AS-ALD within those regions. The chemical selectivity and morphology of e-jet patterned polymers towards binary and ternary oxides of ZnO, Al2O3, and SnO2 were quantified using X-ray photoelectron spectroscopy, atomic force microscopy, and Auger electron spectroscopy. This approach enables patterning of functional oxide semiconductors, insulators, and transparent conducting oxides with tunable composition, Å-scale control of thickness, and sub-µm resolution in the x-y plane. Using a combination of additive and subtractive e-jet printing with AS-ALD, a thin-film transistor was fabricated using zinc-tin-oxide for the semiconductor channel and aluminum-doped zinc oxide as the source and drain electrical contacts. In the future, this technique can be used to print integrated electronics with sub-micron resolution on a variety of substrates.

Medication Adherence and Liquid Level Tracking System for Healthcare Provider Feedback.

A common problem for healthcare providers is accurately tracking patients' adherence to medication and providing real-time feedback on the management of their medication regimen. This is a particular problem for eye drop medications, as the current commercially available monitors focus on measuring adherence to pills, and not to eye drops. This work presents an intelligent bottle sleeve that slides onto a prescription eye drop medication bottle. The intelligent sleeve is capable of detecting eye drop use, measuring fluid level, and sending use information to a healthcare team to facilitate intervention. The electronics embedded into the sleeve measure fluid level, dropper orientation, the state of the dropper top (on/off), and rates of angular motion during an application. The sleeve was tested with ten patients (age ≥65) and successfully identified and timestamped 94% of use events. On-board processing enabled event detection and the measurement of fluid levels at a 0.4 mL resolution. These data were communicated to the healthcare team using Bluetooth and Wi-Fi in real-time, enabling rapid feedback to the subject. The healthcare team can therefore monitor a log of medication use behavior to make informed decisions on treatment or support for the patient.

The impact of ankle-foot orthosis stiffness on gait: A systematic literature review.

BACKGROUND: Ankle-foot orthoses (AFOs) are commonly prescribed to provide ankle support during walking. Current prescription standards provide general guidelines for choosing between AFO types, but are limited in terms of guiding specific design parameter choices. These design parameters affect the ankle stiffness of the AFO. RESEARCH QUESTION: The aim of this review was to investigate the impact of AFO stiffness on walking mechanics. METHODS: A literature search was conducted using three databases: Pubmed, Engineering Village, and Web of Science. RESULTS: After applying the exclusion criteria, 25 of 287 potential articles were included. The included papers tested a range of stiffnesses (0.02-8.17 Nm/deg), a variety of populations (e.g. healthy, post-stroke, cerebral palsy) and various gait outcome measures. Ankle kinematics were the most frequently reported measures and the most consistently affected by stiffness variations. Greater stiffnesses generally resulted in reduced peak ankle plantarflexion, dorsiflexion, and total range of motion, as well as increased dorsiflexion at initial contact. At the knee, a few studies reported increased flexion at initial contact, and decreased peak extension and increased peak flexion during stance when stiffness was increased. Stiffness did not affect hip kinetics and there was low evidence for its effects on hip or pelvis kinematics, ankle and knee kinetics, muscle activity, metabolic cost, ground reaction forces and spatiotemporal parameters. There were no generalizable trends for the impact of stiffness on user preference. SIGNIFICANCE: AFO stiffness is a key factor influencing ankle movement. Clear reporting standards for AFO design parameters, as well as additional high quality research is needed with larger sample sizes and different clinical populations to ascertain the true effect of stiffness on gait.

Low-back electromyography (EMG) data-driven load classification for dynamic lifting tasks.

OBJECTIVE: Numerous devices have been designed to support the back during lifting tasks. To improve the utility of such devices, this research explores the use of preparatory muscle activity to classify muscle loading and initiate appropriate device activation. The goal of this study was to determine the earliest time window that enabled accurate load classification during a dynamic lifting task. METHODS: Nine subjects performed thirty symmetrical lifts, split evenly across three weight conditions (no-weight, 10-lbs and 24-lbs), while low-back muscle activity data was collected. Seven descriptive statistics features were extracted from 100 ms windows of data. A multinomial logistic regression (MLR) classifier was trained and tested, employing leave-one subject out cross-validation, to classify lifted load values. Dimensionality reduction was achieved through feature cross-correlation analysis and greedy feedforward selection. The time of full load support by the subject was defined as load-onset. RESULTS: Regions of highest average classification accuracy started at 200 ms before until 200 ms after load-onset with average accuracies ranging from 80% (±10%) to 81% (±7%). The average recall for each class ranged from 69-92%. CONCLUSION: These inter-subject classification results indicate that preparatory muscle activity can be leveraged to identify the intent to lift a weight up to 100 ms prior to load-onset. The high accuracies shown indicate the potential to utilize intent classification for assistive device applications. SIGNIFICANCE: Active assistive devices, e.g. exoskeletons, could prevent back injury by off-loading low-back muscles. Early intent classification allows more time for actuators to respond and integrate seamlessly with the user.

Patterned hydrogel substrates for cell culture with electrohydrodynamic jet printing.

Cells respond to and are directed by physiochemical cues in their microenvironment, including geometry and substrate stiffness. The development of substrates for cell culture with precisely controlled physiochemical characteristics has the potential to advance the understanding of cell biology considerably. In this communication, E-jet printing is introduced as a method for creating high-resolution protein patterns on substrates with controlled elasticity. It is the first application of E-jet printing on a soft surface. Protein spots as small as 5 µm in diameter on polyacrylamide are demonstrated. The patterned hydrogels are shown to support cell attachment and spreading. Polyacrylamide substrates patterned by E-jet printing may be applied to further the study of cellular mechanobiology.

High-resolution electrohydrodynamic jet printing.

Efforts to adapt and extend graphic arts printing techniques for demanding device applications in electronics, biotechnology and microelectromechanical systems have grown rapidly in recent years. Here, we describe the use of electrohydrodynamically induced fluid flows through fine microcapillary nozzles for jet printing of patterns and functional devices with submicrometre resolution. Key aspects of the physics of this approach, which has some features in common with related but comparatively low-resolution techniques for graphic arts, are revealed through direct high-speed imaging of the droplet formation processes. Printing of complex patterns of inks, ranging from insulating and conducting polymers, to solution suspensions of silicon nanoparticles and rods, to single-walled carbon nanotubes, using integrated computer-controlled printer systems illustrates some of the capabilities. High-resolution printed metal interconnects, electrodes and probing pads for representative circuit patterns and functional transistors with critical dimensions as small as 1 mum demonstrate potential applications in printed electronics.