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Both monitors accurately counted steps during forward linear walking. StepWatch appears to be more accurate than FitBit during complex walking but a larger sample size may confirm these findings. FitBit consistently counted fewer steps than StepWatch during free-living walking. Clinical relevance The StepWatch and FitBit are acceptable tools for assessing forward, linear walking for individuals with transtibial amputation. Given the results' consistenty in the free-living enviorment, both tools may ultimiately be able to be used to count steps in the real world, but more research is needed to confirm these findings.

The study’s objective was to determine whether variations in the 2013 American College of Cardiology/American Heart Association 10-year risk for atherosclerotic cardiovascular disease (ASCVD) were associated with differences in food consumption and diet quality. Findings from the baseline wave of Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study 2004–2009, revealed participants consumed a Western diet. Diet quality measures, specifically the Healthy Eating Index (HEI)-2010, Dietary Approaches to Stop Hypertension (DASH) diet and the Mean Adequacy Ratio (MAR), based on two 24-h recalls collected during follow-up HANDLS studies from 2009–2013, were used. Reported foods were assigned to 27 groups. In this cross-sectional analysis, the participants (n = 2140) were categorized into tertiles based on their 10-year ASCVD risk. Lower and upper tertiles were used to determine significantly different consumption rates among the food groups. Ten groups were used in hierarchical case clustering to generate four dietary patterns (DPs) based on group energy contribution. The DP with the highest HEI-2010 score included sandwiches along with vegetables and cheese/yogurt. This DP, along with the pizza/sandwiches DP, had significantly higher DASH and MAR scores and a lower 10-year ASCVD risk, compared to the remaining two DPs–meats/sandwiches and sandwiches/bakery products; thus, Western dietary patterns were associated with different levels of ASCVD 10-year risk.

Functional electrical stimulation systems are used as neuroprosthetic devices in rehabilitative interventions such as gait training. Stimulator triggers, implemented to control stimulation delivery, range from open- to closed-loop controllers. Finite-state controllers trigger stimulators when specific conditions are met and utilize preset sequences of stimulation. Wearable sensors provide the necessary input to differentiate gait phases during walking and trigger stimulation. However, gait phase detection is associated with inherent system delays. In this study, five stimulator triggers designed to compensate for gait phase detection delays were tested to determine which trigger most accurately delivered stimulation at the desired times of the gait cycle. Motion capture data were collected on seven typically-developing children while walking on an instrumented treadmill. Participants wore one inertial measurement unit on each ankle and gyroscope data were streamed into the gait phase detection algorithm. Five triggers, based on gait phase detection, were used to simulate stimulation to five muscle groups, bilaterally. For each condition, stimulation signals were collected in the motion capture software via analog channels and compared to the desired timing determined by kinematic and kinetic data. Results illustrate that gait phase detection is a viable finite-state control, and appropriate system delay compensations, on average, reduce stimulation delivery delays by 6.7% of the gait cycle.

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Video- and sensor-based gait analysis systems are rapidly emerging for use in ‘real world’ scenarios outside of typical instrumented motion analysis laboratories. Unlike laboratory systems, such systems do not use kinetic data from force plates, rather, gait events such as initial contact (IC) and terminal contact (TC) are estimated from video and sensor signals. There are, however, detection errors inherent in kinematic gait event detection methods (GEDM) and comparative study between classic laboratory and video/sensor-based systems is warranted. For this study, three kinematic methods: coordinate based treadmill algorithm (CBTA), shank angular velocity (SK), and foot velocity algorithm (FVA) were compared to ‘gold standard’ force plate methods (GS) for determining IC and TC in adults (n = 6), typically developing children (n = 5) and children with cerebral palsy (n = 6). The root mean square error (RMSE) values for CBTA, SK, and FVA were 27.22, 47.33, and 78.41 ms, respectively. On average, GED was detected earlier in CBTA and SK (CBTA: −9.54 ± 0.66 ms, SK: −33.41 ± 0.86 ms) and delayed in FVA (21.00 ± 1.96 ms). The statistical model demonstrated insensitivity to variations in group, side, and individuals. Out of three kinematic GEDMs, SK GEDM can best be used for sensor-based gait event detection.

Both skipping breakfast and away-from-home (AFH) food consumption can influence diet quality. This study compared diet quality when breakfasts were eaten at home, eaten AFH, or skipped among adults (aged 32-70 years; 59% female, 62% African American) in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study who completed two 24-hour recalls (n = 2140). Individuals who ate breakfast at home had the highest diet quality (Healthy Eating Index-2010 score). Persons who ate breakfast AFH or skipped breakfast had diet quality scores that were 3.98 and 4.62 points lower. Dietitians could promote more at-home meals as an effective strategy to improve the diet quality for Americans' breakfast.

The Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (CTA) conducted an assessment and evaluation of multiple algorithms for real-time detection of pedestrians in Laser Detection and Ranging (LADAR) and video sensor data taken from a moving platform. The algorithms were developed by Robotics CTA members and then assessed in field experiments jointly conducted by the National Institute of Standards and Technology (NIST) and ARL. A robust, accurate and independent pedestrian tracking system was developed to provide ground truth. The ground truth was used to evaluate the CTA member algorithms for uncertainty and error in their results. A real-time display system was used to provide early detection of errors in data collection.