MRUNet-3D: A multi-stride residual 3D UNet for lung nodule segmentation.

Obtaining an accurate segmentation of the pulmonary nodules in computed tomography (CT) images is challenging. This is due to: (1) the heterogeneous nature of the lung nodules; (2) comparable visual characteristics between the nodules and their surroundings. A robust multi-scale feature extraction mechanism that can effectively obtain multi-scale representations at a granular level can improve segmentation accuracy. As the most commonly used network in lung nodule segmentation, UNet, its variants, and other image segmentation methods lack this robust feature extraction mechanism. In this study, we propose a multi-stride residual 3D UNet (MRUNet-3D) to improve the segmentation accuracy of lung nodules in CT images. It incorporates a multi-slide Res2Net block (MSR), which replaces the simple sequence of convolution layers in each encoder stage to effectively extract multi-scale features at a granular level from different receptive fields and resolutions while conserving the strengths of 3D UNet. The proposed method has been extensively evaluated on the publicly available LUNA16 dataset. Experimental results show that it achieves competitive segmentation performance with an average dice similarity coefficient of 83.47 % and an average surface distance of 0.35 mm on the dataset. More notably, our method has proven to be robust to the heterogeneity of lung nodules. It has also proven to perform better at segmenting small lung nodules. Ablation studies have shown that the proposed MSR and RFIA modules are fundamental to improving the performance of the proposed model.

Impaired dual-task gait in Parkinson's disease is associated with brain morphology changes.

In Parkinson's disease (PD), impaired gait and cognition affect daily activities, particularly in the more advanced stages of the disease. This study investigated the relationship between gait parameters, cognitive performance, and brain morphology in patients with early untreated PD. 64 drug-naive PD patients and 47 healthy controls (HC) participated in the study. Single- and dual-task gait (counting task) were examined using an expanded Timed Up & Go Test measured on a GaitRite walkway. Measurements included gait speed, stride length, and cadence. A brain morphometry analysis was performed on T1-weighted magnetic resonance (MR) images. In PD patients compared to HC, gait analysis revealed reduced speed (p < 0.001) and stride length (p < 0.001) in single-task gait, as well as greater dual-task cost (DTC) for speed (p = 0.007), stride length (p = 0.014) and cadence (p = 0.029). Based on the DTC measures in HC, PD patients were further divided into two subgroups with normal DTC (PD-nDTC) and abnormally increased DTC (PD-iDTC). For PD-nDTC, voxel-based morphometric correlation analysis revealed a positive correlation between a cluster in the left primary motor cortex and stride-length DTC (r = 0.57, p = 0.027). For PD-iDTC, a negative correlation was found between a cluster in the right lingual gyrus and the DTC for gait cadence (r=-0.35, pFWE = 0.018). No significant correlations were found in HC. The associations found between brain morphometry and gait performance with a concurrent cognitive task may represent the substrate for gait and cognitive impairment occurring since the early stages of PD.

IBD-PODCAST Spain: A Close Look at Current Daily Clinical Practice in IBD Management.

BACKGROUND: Crohn's disease (CD) and ulcerative colitis (UC) are inflammatory bowel diseases (IBD) that contributes in part to irreversible bowel damage and long-term complications, reduced quality of life, invalidity, and economic burden. Suboptimal control of IBD is associated with higher healthcare resource utilization (HCRU), impaired quality of life (QoL), and reduced work productivity. AIMS: The IBD-PODCAST study aimed to assess the proportion of IBD patients with suboptimal control and its associated impact. METHODS: IBD-PODCAST is a cross-sectional, multicenter study that aimed to characterize the CD and UC population with optimal or suboptimal control according to the STRIDE-II criteria and patient- and physician-reported measures. Here we present the results of the Spanish cohort (n = 396). RESULTS: A total of 104/196 (53.1%) CD and 83/200 (41.5%) UC patients were found to have suboptimal disease control. Long-term treatment targets according to STRIDE-II were applied in 172 (87.8%) CD and 181 (90.5%) UC patients. 125 of 172 (72.7%) CD and 74 of 181 (40.9%) UC patients were currently treated with targeted immunomodulators. Patients with CD and UC and suboptimal disease control showed impaired QoL, higher HCRU and direct costs, and also loss of work productivity compared to those with optimal control. CONCLUSION: Despite a high rate of targeted immunomodulator therapy, a substantial proportion of IBD patients show suboptimal disease control according to the STRIDE II criteria. Those patients with suboptimal disease control exhibit impaired QoL, less work productivity, and higher HCRU, suggesting that there is considerable need for better treatment approaches in IBD.

Dirt Track Surface Preparation and Associated Differences in Speed, Stride Length, and Stride Frequency in Galloping Horses.

In racehorses, the risk of musculoskeletal injury is linked to a decrease in speed and stride length (SL) over consecutive races prior to injury. Surface characteristics influence stride parameters. We hypothesized that large changes in stride parameters are found during galloping in response to dirt racetrack preparation. Harrowing of the back stretch of a half-mile dirt racetrack was altered in three individual lanes with decreasing depth from the inside to the outside. Track underlay compaction and water content were changed between days. Twelve horses (six on day 2) were sequentially galloped at a target speed of 16 ms-1 across the three lanes. Speed, stride frequency (SF), and SL were quantified with a GPS/GNSS logger. Mixed linear models with speed as covariate analyzed SF and SL, with track hardness and moisture content as fixed factors (p < 0.05). At the average speed of 16.48 ms-1, hardness (both p < 0.001) and moisture content (both p < 0.001) had significant effects on SF and SL. The largest difference in SL of 0.186 m between hardness and moisture conditions exceeded the 0.10 m longitudinal decrease over consecutive race starts previously identified as injury predictor. This suggests that detailed measurements of track conditions might be useful for refining injury prediction models.

The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability.

The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to determine the agreement of several measures of stride time variability across five wearable sensors (Opal APDM, Vicon Blue Trident, Axivity, Plantiga, Xsens DOT) and force plates during military load carriage. Nineteen Australian Army trainee soldiers (age: 24.8 ± 5.3 years, height: 1.77 ± 0.09 m, body mass: 79.5 ± 15.2 kg, service: 1.7 ± 1.7 years) completed three 12-min walking trials on an instrumented treadmill at 5.5 km/h, carrying 23 kg of an external load. Simultaneously, 512 stride time intervals were identified from treadmill-embedded force plates and each sensor where linear (standard deviation and coefficient of variation) and non-linear (detrended fluctuation analysis and sample entropy) measures were obtained. Sensor and force plate agreement was evaluated using Pearson's r and intraclass correlation coefficients. All sensors had at least moderate agreement (ICC > 0.5) and a strong positive correlation (r > 0.5). These results suggest wearable devices could be employed to quantify linear and non-linear measures of stride time variability during military load carriage.

A Novel Method for Identifying Frailty and Quantifying Muscle Strength Using the Six-Minute Walking Test.

The six-minute walking test (6MWT) is an essential test for evaluating exercise tolerance in many respiratory and cardiovascular diseases. Frailty and sarcopenia can cause rapid aging of the cardiovascular system in elderly people. Early detection and evaluation of frailty and sarcopenia are crucial for determining the treatment method. We aimed to develop a wearable measuring system for the 6MWT and propose a method for identifying frailty and quantifying walking muscle strength (WMS). In this study, 60 elderly participants were asked to wear accelerometers behind their left and right ankles during the 6MWT. The gait data were collected by a computer or smartphone. We proposed a method for analyzing walking performance using the stride length (SL) and step cadence (SC) instead of gait speed directly. Four regions (Range I-IV) were divided by cutoff values of SC = 2.0 [step/s] and SL = 0.6 [m/step] for a quick view of the frail state. There were 62.5% of frail individuals distributed in Range III and 72.4% of non-frail individuals in Range I. A concept of a WMS score was proposed for estimating WMS quantitatively. We found that 62.5% of frail individuals were scored as WMS1 and 41.4% of the non-frail elderly as WMS4. The average walking distances corresponding to WMS1-4 were 207 m, 370 m, 432 m, and 462 m, respectively. The WMS score may be a useful tool for quantitatively estimating sarcopenia or frailty due to reduced cardiopulmonary function.

The predominant stride-frequency for routine swimming in catsharks (Scyliorhinus canicula) generates high power at high efficiency in the red musculature.

Videos of free swimming of catsharks (Scyliorhinus canicula) were analysed to give values of swimming speed (units: FL (fish lengths) s-1), stride-length (forward movement in the direction of travel per cycle of body undulation (units: FL) and stride-frequency (units: s-1). Most of the swims (139 of 163, 85%) were at speeds less than 0.545 FL s-1 and were categorized as slow. The rest (24/163, 15%) were categorized as fast. Stride-lengths and stride-frequencies could be evaluated for 115 of the slow swims and 16 of the fast swims. We discuss the fast swim results, but there were so few fast swims that no firm conclusions could be made. As swim speed increased during slow swims, there was a strong increase stride-length [slope 0.965, P < 0.0001)] and a small increase in stride-frequency. Most stride-frequencies (70/115, 61%) were in the range 0.68-0.88 s-1. Previous experiments on red muscle isolated of catshark showed that in this range of frequencies of sinusoidal movement, high power was produced at high efficiency (Curtin and Woledge b). Lower frequencies gave less power and at higher frequencies the efficiency of energy conversion was lower. Thus, we conclude that during routine swimming catsharks choose a swimming speed that optimizes red muscle performance in terms of power and efficiency.

Cadence-based classification of moderate-intensity overground walking in 41- to 85-year-old adults.

BACKGROUND: Walking cadence (steps/min) has emerged as a valid proxy of physical activity intensity, with consensus across numerous laboratory-based treadmill studies that ≥100 steps/min approximates absolutely defined moderate intensity (≥3 metabolic equivalents; METs). We recently reported that this cadence threshold had a classification accuracy of 73.3% for identifying moderate intensity during preferred pace overground walking in young adults. The purpose of this study was to evaluate and compare the performance of a cadence threshold of ≥100 steps/min for correctly classifying moderate intensity during overground walking in middle- and older-aged adults. METHODS: Participants (N = 174, 48.3% female, 41-85 years of age) completed laboratory-based cross-sectional study involving an indoor 5-min overground walking trial at their preferred pace. Steps were manually counted and converted to cadence (total steps/5 min). Intensity was measured using indirect calorimetry and expressed as METs. Classification accuracy (sensitivity, specificity, accuracy) of a cadence threshold of ≥100 steps/min to identify individuals walking at ≥3 METs was calculated. RESULTS: The ≥100 steps/min threshold demonstrated accuracy of 74.7% for classifying moderate intensity. When comparing middle- vs. older-aged adults, similar accuracy (73.4% vs. 75.8%, respectively) and specificity (33.3% vs. 34.5%) were observed. Sensitivity was high, but was lower for middle- vs. older-aged adults (85.2% vs. 93.9%, respectively). CONCLUSION: A cadence threshold of ≥100 steps/min accurately identified moderate-intensity overground walking. Furthermore, accuracy was similar when comparing middle- and older-aged adults. These findings extend our previous analysis in younger adults and confirm the appropriateness of applying this cadence threshold across the adult lifespan.

The impact of neck pain on gait health: a systematic review and meta-analysis.

BACKGROUND: Evidence exists demonstrating the negative impacts of chronic musculoskeletal pain on key measures of gait. Despite neck pain being the second most common musculoskeletal pain condition, there is a paucity of evidence exploring the impacts of neck pain specifically on these outcomes. The aims of this work were to systematically review the current evidence of the associations between chronic neck pain and measures of gait health and to conduct meta-analysis for quantitative assessment of the effect sizes under different walking conditions. METHODS: Systematic review was conducted following PRISMA guidelines. Databases searched included MEDLINE, Embase, Web of Science, CINAHL, and PEDro. Eligible study designs included observational studies consisting of an exposure group with chronic neck pain and control group without chronic neck pain and primary outcomes relating to gait health. For outcomes amenable to meta-analysis, a random-effects model was used to derive summary estimates of Hedge's g depicted graphically with forest plots. Other gait outcomes were narratively summarized. Risk of bias was also assessed. RESULTS: The original search yielded 1918 articles; 12 met final eligibility criteria including 10 cross-sectional studies. Outcomes were grouped first by the five domains of gait: pace, rhythm, asymmetry, variability, and postural control; and second by the tested walking conditions. Meta-analyses for gait speed revealed large effect-sizes indicating that individuals with chronic neck pain had slower measures of gait and lower measures of cadence. Gait outcomes that were narratively summarized supported these findings. CONCLUSION: The quantitative and qualitative findings of this systematic review and meta-analysis suggest a negative impact of CNNP on measures of gait health, particularly gait speed, under various walking conditions. However, broad interpretation of these results should be cautious. Testing gait under dual task conditions may be particularly sensitive to the impact of CNNP, and future work is needed to better understand how pain disrupts this important functionality of the locomotor system. Additionally, consideration should be made to assess measures of variability and investigate these relationships in the older adult population.

Effect of stride length on the running biomechanics of healthy women of different statures.

BACKGROUND: Tibial stress fracture is a debilitating musculoskeletal injury that diminishes the physical performance of individuals who engage in high-volume running, including Service members during basic combat training (BCT) and recreational athletes. While several studies have shown that reducing stride length decreases musculoskeletal loads and the potential risk of tibial injury, we do not know whether stride-length reduction affects individuals of varying stature differently. METHODS: We investigated the effects of reducing the running stride length on the biomechanics of the lower extremity of young, healthy women of different statures. Using individualized musculoskeletal and finite-element models of women of short (N = 6), medium (N = 7), and tall (N = 7) statures, we computed the joint kinematics and kinetics at the lower extremity and tibial strain for each participant as they ran on a treadmill at 3.0 m/s with their preferred stride length and with a stride length reduced by 10%. Using a probabilistic model, we estimated the stress-fracture risk for running regimens representative of U.S. Army Soldiers during BCT and recreational athletes training for a marathon. RESULTS: When study participants reduced their stride length by 10%, the joint kinetics, kinematics, tibial strain, and stress-fracture risk were not significantly different among the three stature groups. Compared to the preferred stride length, a 10% reduction in stride length significantly decreased peak hip (p = 0.002) and knee (p < 0.001) flexion angles during the stance phase. In addition, it significantly decreased the peak hip adduction (p = 0.013), hip internal rotation (p = 0.004), knee extension (p = 0.012), and ankle plantar flexion (p = 0.026) moments, as well as the hip, knee, and ankle joint reaction forces (p < 0.001) and tibial strain (p < 0.001). Finally, for the simulated regimens, reducing the stride length decreased the relative risk of stress fracture by as much as 96%. CONCLUSIONS: Our results show that reducing stride length by 10% decreases musculoskeletal loads, tibial strain, and stress-fracture risk, regardless of stature. We also observed large between-subject variability, which supports the development of individualized training strategies to decrease the incidence of stress fracture.

Stride length mediates the correlation between movement coordination and sprint velocity.

In this study, we aimed to explore the correlation between movement coordination and sprint velocity and the mediating effects of stride length and frequency on this correlation. Thirty-two male college students (16 athletes and 16 non-athletes) participated in this study. Movement coordination was calculated using a vector coding method for intralimb (hip - knee, knee - ankle) and interlimb (hip - hip, knee - knee, ankle - ankle). There was a significant effect of group on hip - knee, hip - hip and ankle - ankle coupling angle during braking phase and knee - knee coupling angle during the propulsive phase. In all participants, the hip - hip coupling angle during the braking phase was positively correlated with sprint velocity, and the ankle - ankle coupling angle during the braking phase was negatively correlated with sprint velocity. Stride length mediated the relationship between hip - hip coupling angle and sprint velocity. In conclusion, the anti-phase of the hip - hip coupling angle and the swing phase of the ankle - ankle coupling angle may contribute to sprint velocity. Moreover, the correlation between hip - hip coupling angle and sprint velocity was related to stride length rather than stride frequency.

Gait Characteristics Associated with Fear of Falling in Hospitalized People with Parkinson's Disease.

BACKGROUND: Fear of falling (FOF) is common in Parkinson's disease (PD) and associated with distinct gait changes. Here, we aimed to answer, how quantitative gait assessment can improve our understanding of FOF-related gait in hospitalized geriatric patients with PD. METHODS: In this cross-sectional study of 79 patients with advanced PD, FOF was assessed with the Falls Efficacy Scale International (FES-I), and spatiotemporal gait parameters were recorded with a mobile gait analysis system with inertial measurement units at each foot while normal walking. In addition, demographic parameters, disease-specific motor (MDS-revised version of the Unified Parkinson's Disease Rating Scale, Hoehn & Yahr), and non-motor (Non-motor Symptoms Questionnaire, Montreal Cognitive Assessment) scores were assessed. RESULTS: According to the FES-I, 22.5% reported low, 28.7% moderate, and 47.5% high concerns about falling. Most concerns were reported when walking on a slippery surface, on an uneven surface, or up or down a slope. In the final regression model, previous falls, more depressive symptoms, use of walking aids, presence of freezing of gait, and lower walking speed explained 42% of the FES-I variance. CONCLUSION: Our study suggests that FOF is closely related to gait changes in hospitalized PD patients. Therefore, FOF needs special attention in the rehabilitation of these patients, and targeting distinct gait parameters under varying walking conditions might be a promising part of a multimodal treatment program in PD patients with FOF. The effect of these targeted interventions should be investigated in future trials.

The Influence of Stride Selection on Gait Parameters Collected with Inertial Sensors.

Different methods exist to select strides that represent preferred, steady-state gait. The aim of this study was to identify the effect of different stride-selection methods on spatiotemporal gait parameters to analyze steady-state gait. A total of 191 patients with hip or knee osteoarthritis (aged 38-85) wearing inertial sensors walked back and forth over 10 m for two minutes. After the removal of strides in turns, five stride-selection methods were compared: (ALL) include all strides, others removed (REFERENCE) two strides around turns, (ONE) one stride around turns, (LENGTH) strides <63% of median stride length, and (SPEED) strides that fall outside the 95% confidence interval of gait speed over the strides included in REFERENCE. Means and SDs of gait parameters were compared for each trial against the most conservative definition (REFERENCE). ONE and SPEED definitions resulted in similar means and SDs compared to REFERENCE, while ALL and LENGTH definitions resulted in substantially higher SDs of all gait parameters. An in-depth analysis of individual strides showed that the first two strides after and last two strides before a turn were significantly different from steady-state walking. Therefore, it is suggested to exclude the first two strides around turns to assess steady-state gait.

Gait Stride Length Estimation Using Embedded Machine Learning.

INTRODUCTION: Spatiotemporal gait parameters, e.g., gait stride length, are measurements that are classically derived from instrumented gait analysis. Today, different solutions are available for gait assessment outside the laboratory, specifically for spatiotemporal gait parameters. Such solutions are wearable devices that comprise an inertial measurement unit (IMU) sensor and a microcontroller (MCU). However, these existing wearable devices are resource-constrained. They contain a processing unit with limited processing and memory capabilities which limit the use of machine learning to estimate spatiotemporal gait parameters directly on the device. The solution for this limitation is embedded machine learning or tiny machine learning (tinyML). This study aims to create a machine-learning model for gait stride length estimation deployable on a microcontroller. MATERIALS AND METHOD: Starting from a dataset consisting of 4467 gait strides from 15 healthy people, measured by IMU sensor, and using state-of-the-art machine learning frameworks and machine learning operations (MLOps) tools, a multilayer 1D convolutional float32 and int8 model for gait stride length estimation was developed. RESULTS: The developed float32 model demonstrated a mean accuracy and precision of 0.23 ± 4.3 cm, and the int8 model demonstrated a mean accuracy and precision of 0.07 ± 4.3 cm. The memory usage for the float32 model was 284.5 kB flash and 31.9 kB RAM. The int8 model memory usage was 91.6 kB flash and 13.6 kB RAM. Both models were able to be deployed on a Cortex-M4F 64 MHz microcontroller with 1 MB flash memory and 256 kB RAM. CONCLUSIONS: This study shows that estimating gait stride length directly on a microcontroller is feasible and demonstrates the potential of embedded machine learning, or tinyML, in designing wearable sensor devices for gait analysis.

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait.

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the IMU-2-segment (I2S) pairing work properly only for a limited range of gait speeds or require a similar sensor configuration. Our goal was to propose an algorithm that works over a wide range of gait speeds with different sensor configurations while being robust to footwear type and generalizable to pathologic gait patterns. Eight IMU sensors were attached to both feet, shanks, thighs, sacrum, and trunk, and 12 healthy subjects (training dataset) and 22 patients (test dataset) with medial compartment knee osteoarthritis walked at different speeds with/without insole. First, the mean stride time was estimated and IMU signals were scaled. Using a decision tree, the body segment was recognized, followed by the side of the lower limb sensor. The accuracy and precision of the whole algorithm were 99.7% and 99.0%, respectively, for gait speeds ranging from 0.5 to 2.2 m/s. In conclusion, the proposed algorithm was robust to gait speed and footwear type and can be widely used for different sensor configurations.

Effects of upper arch expansion using clear aligners on different stride and torque: a three-dimensional finite element analysis.

BACKGROUND: During maxillary arch expansion with a clear aligner (CA), buccal tipping of the posterior teeth often occurs, resulting in an unsatisfactory arch expansion effect. The aim of this study was to analyze the appropriate maxillary arch expansion stride length and torque compensation angle for maxillary dentition to achieve an ideal moving state when a CA was used for upper arch expansion. METHODS: This study established a three-dimensional (3D) finite element model including a CA, maxilla, periodontal ligament (PDL), and maxillary dentition. The stress distribution, stress situation, expansion efficiency, and movement trends of the maxillary dentition during upper arch expansion of different stride (0.1 mm, 0.2 mm, and 0.3 mm) and torque compensation (0°, 0.5°, 1°, and 1.5°) were measured. RESULTS: Maxillary arch expansion lead to buccal tilt of the posterior teeth, lingual tilt of the anterior teeth, and extrusion of the incisors. As the angle of compensation increased, the degree of buccal tilt on the posterior teeth decreased, with this reducing the efficiency of upper arch expansion. When the stride length was 0.1 mm, the torque compensation was 1.2°, and when stride length was 0.2 mm and the torque compensation was approximately 2°, there was a tendency for the posterior teeth to move bodily. However, when the stride length was 0.3 mm, the increase in torque compensation could not significantly improve the buccal tilt phenomenon. In addition, the equivalent von-Mises stress values of the maxillary root, PDL, and alveolar bone were in the same order of magnitude. CONCLUSIONS: This study indicated that the posterior teeth cause a degree of buccal tilt when maxillary arch expansion is ensured. The specific torque compensation angle should be determined based on the patient's situation and the desired effect.

A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon.

A new group of marathon participants with minimal prior experience encounters the phenomenon known as "hitting the wall," characterized by a notable decline in velocity accompanied by the heightened perception of fatigue (rate of perceived exertion, RPE). Previous research has suggested that successfully completing a marathon requires self-pacing according to RPE rather than attempting to maintain a constant speed or heart rate. However, it remains unclear how runners can self-pace their races based on the signals received from their physiological and mechanical running parameters. This study aims to investigate the relationship between the amount of information conveyed in a message or signal, RPE, and performance. It is hypothesized that a reduction in physiological or mechanical information (quantified by Shannon Entropy) affects performance. The entropy of heart rate, speed, and stride length was calculated for each kilometer of the race. The results showed that stride length had the highest entropy among the variables, and a reduction in its entropy to less than 50% of its maximum value (H = 3.3) was strongly associated with the distance (between 22 and 40) at which participants reported "hard exertion" (as indicated by an RPE of 15) and their performance (p < 0.001). These findings suggest that integrating stride length's Entropy feedback into new cardioGPS watches could improve marathon runners' performance.

Spatial Evolution of Histologic and Endoscopic Healing in the Left and Right Colon in Patients With Ulcerative Colitis.

BACKGROUND AND AIMS: Despite increasing interest in histologic remission as a treatment target in ulcerative colitis (UC), the accuracy of histologic findings in left colon in detecting pancolonic histologic remission is unknown. METHODS: In a retrospective cohort study of patients with endoscopically active pancolitis undergoing treat-to-target interventions, we evaluated the diagnostic accuracy of left-sided (distal to splenic flexure) histologic and endoscopic findings on colonoscopy for detecting histologic and endoscopic healing elsewhere in the colon. RESULTS: Of 86 patients with moderate to severely active pancolitis who underwent 2 consecutive colonoscopies during treat-to-target interventions, 38% and 51% achieved histologic and endoscopic remission, respectively. Substantial agreement (kappa, 0.67; 95% confidence interval (CI), 0.51-0.83) was observed in histologic findings between left and right colon on follow-up colonoscopy. Histologic, and endoscopic, findings in left colon showed excellent accuracy in detecting pancolonic histologic remission (area under the curve (AUC), 0.96 [95% CI, 0.93-1.0]; misclassification rate, 5.9%), histologic normalization (AUC, 1.0, 0%), endoscopic improvement (AUC, 0.95 [0.96-1.0], 3.5%) and endoscopic remission (AUC, 0.98 [0.96-1.00], 5.8%), respectively. CONCLUSIONS: In patients with active pancolitis undergoing treat-to-target interventions, histologic and endoscopic findings in the left colon on colonoscopy have excellent accuracy for detecting pancolonic histologic remission, histologic normalization, endoscopic improvement, and endoscopic remission. Flexible sigmoidoscopy may suffice for monitoring histologic and endoscopic activity in patients with pancolitis.

Acute intense fatigue does not modify the effect of EVA and TPU custom foot orthoses on running mechanics, running economy and perceived comfort.

We determined whether fatigue modifies the effect of custom foot orthoses manufactured from ethyl-vinyl acetate (EVA) and expanded thermoplastic polyurethane (TPU) materials, both compared to standardized footwear (CON), on running mechanics, running economy, and perceived comfort. Eighteen well-trained, males ran on an instrumented treadmill for 6 min at the speed corresponding to their first ventilatory threshold (13.8 ± 1.1 km/h) in three footwear conditions (CON, EVA, and TPU). Immediately after completion of a repeated-sprints exercise (8 × 5 s treadmill sprints, rest = 25 s), these run tests were replicated. Running mechanics, running economy and perceived comfort were determined. Two-way repeated measures ANOVA [condition (CON, EVA, and TPU) × fatigue (fresh and fatigued)] were conducted. Flight time shortened (P = 0.026), peak braking (P = 0.016) and push-off (P = 0.032) forces decreased and vertical stiffness increased (P = 0.014) from before to after the repeated-sprint exercise, independent of footwear condition. There was a global fatigue-induced deterioration in running economy (- 1.6 ± 0.4%; P < 0.001). There was no significant condition × fatigue [except mean loading rate (P = 0.046)] for the large majority of biomechanical, cardio-respiratory [except minute ventilation (P = 0.020) and breathing frequency (P = 0.019)] and perceived comfort variables. Acute intense fatigue does not modify the effect of custom foot orthoses with different resilience characteristics on running mechanics, running economy and perceived comfort.

Adaptive Pedestrian Stride Estimation for Localization: From Multi-Gait Perspective.

Accurate and reliable stride length estimation modules play a significant role in Pedestrian Dead Reckoning (PDR) systems, but the accuracy of stride length calculation suffers from individual differences. This paper presents a stride length prediction strategy for PDR systems that can be adapted across individuals and broad walking velocity fields. It consists of a multi-gait division algorithm, which can divide a full stride into push-off, swing, heel-strike, and stance based on multi-axis IMU data. Additionally, based on the acquired gait phases, the correlation between multiple features of distinct gait phases and the stride length is analyzed, and multi regression models are merged to output the stride length value. In experimental tests, the gait segmentation algorithm provided gait phases division with the F-score of 0.811, 0.748, 0.805, and 0.819 for stance, push-off, swing, heel-strike, respectively, and IoU of 0.482, 0.69, 0.509 for push-off, swing, heel-strike, respectively. The root means square error (RMSE) of our proposed stride length estimation was 151.933, and the relative error for total distance in varying walking speed tests was less than 2%. The experimental results validated that our proposed gait phase segmentation algorithm can accurately recognize gait phases for individuals with wide walking speed ranges. With no need for parameter modification, the stride length method based on the fusion of multiple predictions from different gait phases can provide better accuracy than the estimations based on the full stride.