Reliability of patient-specific gait profiles with inertial measurement units during the 2-min walk test in incomplete spinal cord injury.

Most established clinical walking tests assess specific aspects of movement function (velocity, endurance, etc.) but are generally unable to determine specific biomechanical or neurological deficits that limit an individual's ability to walk. Recently, inertial measurement units (IMU) have been used to collect objective kinematic data for gait analysis and could be a valuable extension for clinical assessments (e.g., functional walking measures). This study assesses the reliability of an IMU-based overground gait analysis during the 2-min walk test (2mWT) in individuals with spinal cord injury (SCI). Furthermore, the study elaborates on the capability of IMUs to distinguish between different gait characteristics in individuals with SCI. Twenty-six individuals (aged 22-79) with acute or chronic SCI (AIS: C and D) completed the 2mWT with IMUs attached above each ankle on 2 test days, separated by 1 to 7 days. The IMU-based gait analysis showed good to excellent test-retest reliability (ICC: 0.77-0.99) for all gait parameters. Gait profiles remained stable between two measurements. Sensor-based gait profiling was able to reveal patient-specific gait impairments even in individuals with the same walking performance in the 2mWT. IMUs are a valuable add-on to clinical gait assessments and deliver reliable information on detailed gait pathologies in individuals with SCI.Trial registration: NCT04555759.

Data-driven characterization of walking after a spinal cord injury using inertial sensors.

BACKGROUND: An incomplete spinal cord injury (SCI) refers to remaining sensorimotor function below the injury with the possibility for the patient to regain walking abilities. However, these patients often suffer from diverse gait deficits, which are not objectively assessed in the current clinical routine. Wearable inertial sensors are a promising tool to capture gait patterns objectively and started to gain ground for other neurological disorders such as stroke, multiple sclerosis, and Parkinson's disease. In this work, we present a data-driven approach to assess walking for SCI patients based on sensor-derived outcome measures. We aimed to (i) characterize their walking pattern in more depth by identifying groups with similar walking characteristics and (ii) use sensor-derived gait parameters as predictors for future walking capacity. METHODS: The dataset analyzed consisted of 66 SCI patients and 20 healthy controls performing a standardized gait test, namely the 6-min walking test (6MWT), while wearing a sparse sensor setup of one sensor attached to each ankle. A data-driven approach has been followed using statistical methods and machine learning models to identify relevant and non-redundant gait parameters. RESULTS: Clustering resulted in 4 groups of patients that were compared to each other and to the healthy controls. The clusters did differ in terms of their average walking speed but also in terms of more qualitative gait parameters such as variability or parameters indicating compensatory movements. Further, using longitudinal data from a subset of patients that performed the 6MWT several times during their rehabilitation, a prediction model has been trained to estimate whether the patient's walking speed will improve significantly in the future. Including sensor-derived gait parameters as inputs for the prediction model resulted in an accuracy of 80%, which is a considerable improvement of 10% compared to using only the days since injury, the present 6MWT distance, and the days until the next 6MWT as predictors. CONCLUSIONS: In summary, the work presented proves that sensor-derived gait parameters provide additional information on walking characteristics and thus are beneficial to complement clinical walking assessments of SCI patients. This work is a step towards a more deficit-oriented therapy and paves the way for better rehabilitation outcome predictions.

Accuracy and comparison of sensor-based gait speed estimations under standardized and daily life conditions in children undergoing rehabilitation.

BACKGROUND: Gait speed is a widely used outcome measure to assess the walking abilities of children undergoing rehabilitation. It is routinely determined during a walking test under standardized conditions, but it remains unclear whether these outcomes reflect the children's performance in daily life. An ankle-worn inertial sensor provides a usable opportunity to measure gait speed in the children's habitual environment. However, sensor-based gait speed estimations need to be accurate to allow for comparison of the children's gait speed between a test situation and daily life. Hence, the first aim of this study was to determine the measurement error of a novel algorithm that estimates gait speed based on data of a single ankle-worn inertial sensor in children undergoing rehabilitation. The second aim of this study was to compare the children's gait speed between standardized and daily life conditions. METHODS: Twenty-four children with walking impairments completed four walking tests at different speeds (standardized condition) and were monitored for one hour during leisure or school time (daily life condition). We determined accuracy by comparing sensor-based gait speed estimations with a reference method in both conditions. Eventually, we compared individual gait speeds between the two conditions. RESULTS: The measurement error was 0.01 ± 0.07 m/s under the standardized and 0.04 ± 0.06 m/s under the daily life condition. Besides, the majority of children did not use the same speed during the test situation as in daily life. CONCLUSION: This study demonstrates an accurate method to measure children's gait speed during standardized walking tests and in the children's habitual environment after rehabilitation. It only requires a single ankle sensor, which potentially increases wearing time and data quality of measurements in daily life. We recommend placing the sensor on the less affected side, unless the child wears one orthosis. In this latter case, the sensor should be placed on the side with the orthosis. Moreover, this study showed that most children did not use the same speed in the two conditions, which encourages the use of wearable inertial sensors to assess the children's walking performance in their habitual environment following rehabilitation.

Using Wearable Inertial Sensors to Estimate Clinical Scores of Upper Limb Movement Quality in Stroke.

Neurorehabilitation is progressively shifting from purely in-clinic treatment to therapy that is provided in both clinical and home-based settings. This transition generates a pressing need for assessments that can be performed across the entire continuum of care, a need that might be accommodated by application of wearable sensors. A first step toward ubiquitous assessments is to augment validated and well-understood standard clinical tests. This route has been pursued for the assessment of motor functioning, which in clinical research and practice is observation-based and requires specially trained personnel. In our study, 21 patients performed movement tasks of the Action Research Arm Test (ARAT), one of the most widely used clinical tests of upper limb motor functioning, while trained evaluators scored each task on pre-defined criteria. We collected data with just two wrist-worn inertial sensors to guarantee applicability across the continuum of care and used machine learning algorithms to estimate the ARAT task scores from sensor-derived features. Tasks scores were classified with approximately 80% accuracy. Linear regression between summed clinical task scores (across all tasks per patient) and estimates of sum task scores yielded a good fit (R 2 = 0.93; range reported in previous studies: 0.61-0.97). Estimates of the sum scores showed a mean absolute error of 2.9 points, 5.1% of the total score, which is smaller than the minimally detectable change and minimally clinically important difference of the ARAT when rated by a trained evaluator. We conclude that it is feasible to obtain accurate estimates of ARAT scores with just two wrist worn sensors. The approach enables administration of the ARAT in an objective, minimally supervised or remote fashion and provides the basis for a widespread use of wearable sensors in neurorehabilitation.

Turning in Circles: Understanding Manual Wheelchair Use Towards Developing User-Friendly Steering Systems.

For people with physical disabilities, manual wheelchairs are essential enablers of mobility, participation in society, and a healthy lifestyle. Their most general design offers great flexibility and direct feedback, but has been described to be inefficient and demands good coordination of the upper extremities while critically influencing users' actions. Multiple research groups have used Inertial Measurement Units (IMUs) to quantify physical activities in wheelchairs arguing that knowledge over behavioural patterns in manual wheelchair usage can guide technological development and improved designs. The present study investigates turning behaviour among fulltime wheelchair users, laying the foundation of the development of novel steering systems that allow directing kinetic energy by means other than braking. Three wearable sensors were installed on the wheelchairs of 14 individuals for tracking movement over an entire week. During detected "moving windows", phases where the velocities of the two rear wheels differed by more than 0.05 m/s were considered as turns. Kinematic characteristics for both turns-on-the-spot as well as for moving turns were then derived from the previously reconstructed wheeled path. For the grand total of 334 km of recorded wheelchair movement, a turn was detected every 3.6 m, which equates to about 900 turns per day on average and shows that changing and adjusting direction is fundamental in wheelchair practice. For moving turns, a median turning radius of 1.09 m and a median turning angle of 39° were found. With a median of 89°, typical turning angles were considerably larger for turns-on-the-spot, which accounted for roughly a quarter of the recognised turns and often started from a standstill. These results suggest that a frequent pattern in daily wheelchair usage is to initiate movement with an orienting turn-on-the-spot, and cover distances with short, straightforward sections while adjusting direction in small and tight moving turns. As large bends often require simultaneous pushing and breaking, this is, perhaps, the result of users intuitively optimising energy efficiency, but more research is needed to understand how the design of the assistive devices implicitly directs users' movement.

Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds.

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.

Complementing Clinical Gait Assessments of Spinal Cord Injured Individuals using Wearable Movement Sensors.

Today's standard clinical practice to assess the walking ability of patients with neurological disorders during rehabilitation is based on simple gait tests such as the six-minute walking test (6MWT). Since the outcome of these tests is the average walking speed only, the aim of this work was to show that the application of movement sensors during a standardized walking test for the population of spinal cord injured (SCI) patients provides additional information on gait quality not directly described by the average speed. Hence, gait features that are related to quantitative and qualitative aspects of gait were extracted from the ankle sensor recordings of 29 SCI subjects and 19 healthy controls performing the 6MWT. The subjects were clustered into groups based on these gait features, and six gait features were selected to demonstrate the key differences between the clusters. The correlation of these features to the outcome of the 6MWT is discussed with their implications on gait quality.

Predicting upper limb compensation during prehension tasks in tetraplegic spinal cord injured patients using a single wearable sensor.

Upper limb (UL) compensation is a common strategy of patients with a high spinal cord injury (SCI), i.e., tetraplegic patients, to perform activities of daily living (ADLs) despite their sensorimotor deficits. Currently, an objective and sensitive tool to assess UL compensation, which is applicable in the clinical routine and in the daily life of patients, is missing. In this work, we propose a metric to quantify this compensation using a single inertial measurement unit (IMU). The spread of forearm pitch angles of an IMU attached to the wrist of 17 SCI patients and 18 healthy controls performing six prehension tasks of the graded redefined assessment of strength, sensibility and prehension (GRASSP) was extracted. Using the spread of the forearm pitch angles, a classification of UL compensation was possible with very good to excellent accuracies in all six different prehension tasks. Furthermore, the spread of forearm pitch angles correlated moderately to very strongly with qualitative and quantitative GRASSP prehension scores and the task duration. Therefore, we conclude that our proposed method has a high potential to classify compensation accurately and objectively and might be used to quantify the degree of UL compensation in ADLs. Thus, this method could be implemented in clinical trials investigating the effectiveness of interventions targeting UL functions.

Predictive Model for the Electrical Transport within Nanowire Networks.

Thin networks of high aspect ratio conductive nanowires can combine high electrical conductivity with excellent optical transparency, which has led to a widespread use of nanowires in transparent electrodes, transistors, sensors, and flexible and stretchable conductors. Although the material and application aspects of conductive nanowire films have been thoroughly explored, there is still no model which can relate fundamental physical quantities, like wire resistance, contact resistance, and nanowire density, to the sheet resistance of the film. Here, we derive an analytical model for the electrical conduction within nanowire networks based on an analysis of the parallel resistor network. The model captures the transport characteristics and fits a wide range of experimental data, allowing for the determination of physical parameters and performance-limiting factors, in sharp contrast to the commonly employed percolation theory. The model thus constitutes a useful tool with predictive power for the evaluation and optimization of nanowire networks in various applications.

Modular microstructure design to build neuronal networks of defined functional connectivity.

Theoretical and in vivo neuroscience research suggests that functional information transfer within neuronal networks is influenced by circuit architecture. Due to the dynamic complexities of the brain, it remains a challenge to test the correlation between structure and function of a defined network. Engineering controlled neuronal networks in vitro offers a way to test structural motifs; however, no method has achieved small, multi-node networks with stable, unidirectional connections. Here, we screened ten different microchannel architectures within polydimethylsiloxane (PDMS) devices to test their potential for axonal guidance. The most successful design had a 92% probability of achieving strictly unidirectional connections between nodes. Networks built from this design were cultured on multielectrode arrays and recorded on days in vitro 9, 12, 15 and 18 to investigate spontaneous and evoked bursting activity. Transfer entropy between subsequent nodes showed up to 100 times more directional flow of information compared to the control. Additionally, directed networks produced a greater amount of information flow, reinforcing the importance of directional connections in the brain being critical for reliable communication. By controlling the parameters of network formation, we minimized response variability and achieved functional, directional networks. The technique provides us with a tool to probe the spatio-temporal effects of different network motifs.

Reliability of Wearable-Sensor-Derived Measures of Physical Activity in Wheelchair-Dependent Spinal Cord Injured Patients.

Physical activity (PA) has been shown to have a positive influence on functional recovery in patients after a spinal cord injury (SCI). Hence, it can act as a confounder in clinical intervention studies. Wearable sensors are used to quantify PA in various neurological conditions. However, there is a lack of knowledge about the inter-day reliability of PA measures. The objective of this study was to investigate the single-day reliability of various PA measures in patients with a SCI and to propose recommendations on how many days of PA measurements are required to obtain reliable results. For this, PA of 63 wheelchair-dependent patients with a SCI were measured using wearable sensors. Patients of all age ranges (49.3 ± 16.6 years) and levels of injury (from C1 to L2, ASIA A-D) were included for this study and assessed at three to four different time periods during inpatient rehabilitation (2 weeks, 1 month, 3 months, and if applicable 6 months after injury) and after in-patient rehabilitation in their home-environment (at least 6 months after injury). The metrics of interest were total activity counts, PA intensity levels, metrics of wheeling quantity and metrics of movement quality. Activity counts showed consistently high single-day reliabilities, while measures of PA intensity levels considerably varied depending on the rehabilitation progress. Single-day reliabilities of metrics of movement quantity decreased with rehabilitation progress, while metrics of movement quality increased. To achieve a mean reliability of 0.8, we found that three continuous recording days are required for out-patients, and 2 days for in-patients. Furthermore, the results show similar weekday and weekend wheeling activity for in- and out-patients. To our knowledge, this is the first study to investigate the reliability of an extended set of sensor-based measures of PA in both acute and chronic wheelchair-dependent SCI patients. The results provide recommendations for sensor-based assessments of PA in clinical SCI studies.

Local Chemical Stimulation of Neurons with the Fluidic Force Microscope (FluidFM).

Physiological communication between neurons is dependent on the exchange of neurotransmitters at the synapses. Although this chemical signal transmission targets specific receptors and allows for subtle adaptation of the action potential, in vitro neuroscience typically relies on electrical currents and potentials to stimulate neurons. The electric stimulus is unspecific and the confinement of the stimuli within the media is technically difficult to control and introduces large artifacts in electric recordings of the activity. Here, we present a local chemical stimulation platform that resembles in vivo physiological conditions and can be used to target specific receptors of synapses. Neurotransmitters were dispensed using the force-controlled fluidic force microscope (FluidFM) nanopipette, which provides exact positioning and precise liquid delivery. We show that controlled release of the excitatory neurotransmitter glutamate induces spiking activity in primary rat hippocampal neurons, as measured by concurrent electrical and optical recordings using a microelectrode array and a calcium-sensitive dye, respectively. Furthermore, we characterized the glutamate dose response of neurons by applying stimulation pulses of glutamate with concentrations from 0 to 0.5 mm. This new stimulation approach, which combines FluidFM for gentle and precise positioning with a microelectrode array read-out, makes it possible to modulate the activity of individual neurons chemically and simultaneously record their induced activity across the entire neuronal network. The presented platform not only offers a more physiological alternative compared with electrical stimulation, but also provides the possibility to study the effects of the local application of neuromodulators and other drugs.

Minimum toe clearance: probing the neural control of locomotion.

Minimum toe clearance (MTC) occurs during a highly dynamic phase of the gait cycle and is associated with the highest risk of unintentional contact with obstacles or the ground. Age, cognitive function, attention and visual feedback affect foot clearance but how these factors interact to influence MTC control is not fully understood. We measured MTC in 121 healthy individuals aged 20-80 under four treadmill walking conditions; normal walking, lower visual field restriction and two Stroop colour/word naming tasks of two difficulty levels. Competition for cognitive and attentional resources from the Stroop task resulted in significantly lower mean MTC in older adults, with the difficult Stroop task associated with a higher frequency of extremely low MTC values and subsequently an increased modelled probability of tripping in this group. While older adults responded to visual restriction by markedly skewing MTC distributions towards higher values, this condition was also associated with frequent, extremely low MTC values. We reveal task-specific, age-dependent patterns of MTC control in healthy adults. Age-related differences are most pronounced during heavy, distracting cognitive load. Analysis of critically-low MTC values during dual-task walking may have utility in the evaluation of locomotor control and fall risk in older adults and patients with motor control deficits.

Controlled single-cell deposition and patterning by highly flexible hollow cantilevers.

Single-cell patterning represents a key approach to decouple and better understand the role and mechanisms of individual cells of a given population. In particular, the bottom-up approach of engineering neuronal circuits with a controlled topology holds immense promises to perceive the relationships between connectivity and function. In order to accommodate these efforts, highly flexible SU-8 cantilevers with integrated microchannels have been fabricated for both additive and subtractive patterning. By directly squeezing out single cells onto adhesive surfaces, controlled deposition with a spatial accuracy of 5 µm could be achieved, while subtractive patterning has been realized by selective removal of targeted single cells. Complex cell patterns were created on substrates pre-patterned with cell-adhesive and repulsive areas, preserving the original pattern geometry for long-term studies. For example, a circular loop with a diameter of 530 µm has been realized using primary hippocampal neurons, which were fully connected to their respective neighbors along the loop. Using the same cantilevers, the versatility of the technique has also been demonstrated via in situ modification of already mature neuronal cultures by both detaching individual cells of the population and adding fresh ones, incorporating them into the culture.

Quantifying the effect of electric current on cell adhesion studied by single-cell force spectroscopy.

This study presents the effect of external electric current on the cell adhesive and mechanical properties of the C2C12 mouse myoblast cell line. Changes in cell morphology, viability, cytoskeleton, and focal adhesion structure were studied by standard staining protocols, while single-cell force spectroscopy based on the fluidic force microscopy technology provided a rapid, serial quantification and detailed analysis of cell adhesion and its dynamics. The setup allowed measurements of adhesion forces up to the µN range, and total detachment distances over 40 µm. Force-distance curves have been fitted with a simple elastic model including a cell detachment protocol in order to estimate the Young's modulus of the cells, as well as to reveal changes in the dynamic properties as functions of the applied current dose. While the cell spreading area decreased monotonously with increasing current doses, small current doses resulted only in differences related to cell elasticity. Current doses above 11 As/m(2), however, initiated more drastic changes in cell morphology, viability, cellular structure, as well as in properties related to cell adhesion. The observed differences, eventually leading to cell death toward higher doses, might originate from both the decrease in pH and the generation of reactive oxygen species.

Femtomolar oligonucleotide detection by a one-step gold nanoparticle-based assay.

A sequence-specific oligonucleotide detection method based on the tail-to-tail aggregation of functionalized gold nanoparticles in the presence of target analytes is presented together with its optimization and capabilities for detection of single nucleotide polymorphisms (SNPs). In this single-step method, capture probes are freely accessible for hybridization, resulting in an improved assay performance compared to substrate-based assays. The analytes bring the nanoparticles close to each other via hybridization, causing a red shift of the nanoparticle plasmon peak detected by a spectrophotometer or CCD camera coupled to a darkfield imaging system. Optimal conditions for the assay were found to be (i) use of capture probes complementary to the target without any gap, (ii) maximum possible probe density on the gold nanoparticles, and (iii) 1M ionic strength buffer. The optimized assay has a 1 fM limit of detection and fM to 10 pM dynamic range, with detection of perfect match sequences being three orders of magnitude more sensitive than targets with single nucleotide mismatches.

Local polymer replacement for neuron patterning and in situ neurite guidance.

By locally dispensing poly-L-lysine (PLL) molecules with a FluidFM onto a protein and cell resistant poly-L-lysine-graft-polyethylene glycol (PLL-g-PEG) coated substrate, the antifouling layer can be replaced under the tip aperture by the cell adhesive PLL. We used this approach for guiding the adhesion and axonal outgrowth of embryonic hippocampal neurons in situ. Cultures of hippocampal neurons were chosen because they mostly contain pyramidal neurons. The hippocampus is known to be involved in memory formation, and the stages of network development are well characterized, which is an asset to fundamental research. After fabricating diffuse PLL spots with 10-250 µm diameter, seeded hippocampal cells stick preferentially onto the spots migrating toward the spot center along the PLL gradient. Cell clusters were formed depending on the lateral size of the PLL dots and the density of seeded cells. In a second step of this protocol, the FluidFM is used to connect in situ the obtained clusters. The outgrowth of neurites, which are known to grow preferentially on adhesive substrates, is tailored by writing PLL lines. Antibody staining confirms that the outgrowing neurites are mostly axons, while the activity of the neurons is assessed by a calcium indicator, proving cell viability. The calcium signal intensity of two actively interconnected clusters showed to be correlated, corroborating the formation of vectored and polarized interconnections.

Cyclodextrin KnowledgeBase a web-based service managing CD-ligand complexation data.

Cyclodextrins are cyclic oligosaccharides that are able to form water-soluble inclusion complexes with small molecules. Because of their complexing ability, they are widely applied in food, pharmaceutical and chemical industries. In this paper we describe the development of a free web-service, Cyclodextrin KnowledgeBase: ( http://www.cyclodextrin.net ). The database contains four modules: the Publication, Interaction, Chirality and Analysis Modules. In the Publication Module, almost 50,000 publication details are collected that can be retrieved by text search. In the Interaction and Chirality Modules relevant literature data on cyclodextrin complexation and chiral recognition are collected that can be retrieved by both text and structural searches. Moreover, in the Analysis Module, the geometries of small molecule-cyclodextrin complexes can be predicted using molecular docking tools in order to explore the structures and interaction energies of the inclusion complexes. Complex geometry prediction is made possible by the built-in database of 95 cyclodextrin derivatives, where the 3D structures as well as the partial charges are calculated and stored for further utilization. The use of the database is demonstrated by several examples.

[DockingServer: molecular docking calculations online]. / DockingServer: molekuláris dokkolási számítások a böngészoben.

Over the last years, the use of bioinformatics tools such as molecular docking has become an essential part of research focused at prediction of the binding of small molecules to their target proteins. DockingServer offers a web-based, easy to use interface that handles all aspects of molecular docking from ligand and pro-tein set-up through results representation integrating a number of software frequently used in computational chemistry. While its user friendly interface enables docking calculation and results evaluation carried out by researchers coming from all fields of biochemistry, DockingServer also provides full control on the setting of specific parameters of ligand and protein set up and docking calculations for more advanced users. The application can be used for docking and analysis of single ligands as well as for high throughput docking of ligand libraries to target proteins. The use of "DockingServer" is illustrated by the formation of acetaminophene (paracetamol)-CYP2E1 complex.

Functional and structural characterization of a protein based on analysis of its hydrogen bonding network by hydrogen bonding plot.

Knowledge of the relationship between protein's structure and its dynamic behavior is essential for understanding protein function. In this study, the description of a protein three-dimensional structure as a network of hydrogen bonding interactions (HB plot) is introduced as a tool for exploring protein structure and function. HB plot offers a simple way of analyzing protein secondary and tertiary structure. Moreover, hydrogen bonds stabilizing secondary structural elements and those formed between distant amino residues--defined as tertiary hydrogen bonds--can be easily distinguished in HB plot, thus, amino acid residues involved in stabilizing protein structure and function can be easily identified. By analyzing the network of tertiary interactions the possible spread of information within a protein can be investigated as well. The alteration in tertiary hydrogen bonding network during conformational transitions were investigated through case studies; and showed the applicability of HB plot in exploring mechanistic details in proteins.