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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.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.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).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 Compendium of Physical Activities reports that walking at 2.5 mph associates with absolutely-defined moderate intensity (i.e., ≥3 metabolic equivalents [METs]). However, it is unclear whether this speed threshold is accurate during overground walking and/or across the adult age-span. This study aimed to identify optimal and heuristic speed thresholds associated with 3 METs during overground walking across age groups. Healthy adults (n = 248, 21-85 years old, 49% women) performed a 5-minute self-paced overground walking trial. Speed was measured using an electronic gait mat, and oxygen uptake was measured using indirect calorimetry and converted to METs. Optimal and heuristic thresholds and classification accuracy metrics were determined and compared using ROC curve analyses. Speed thresholds (95% CIs) associated with 3 METs for the whole sample, young (21-40 years), middle-aged (41-60 years) and older-aged (61-85 years) groups were 1.29 (1.25, 1.33), 1.30 (1,26, 1,35), and 1.25 (1.21, 1.29) m/s, respectively. Overall, 3 mph and 5 km/h performed better than 2.5 mph and 4.5 km/h in balancing both sensitivity and specificity (higher Youden's Indices). Overground walking speeds associated with 3 METs were similar across age groups. A heuristic threshold of 3 mph or 5 km/h may better identify absolutely-defined moderate intensity overground walking.

Step-based metrics provide simple measures of ambulatory activity, yet device software either includes undisclosed proprietary step detection algorithms or simply does not compute step-based metrics. We aimed to develop and validate a simple algorithm to accurately detect steps across various ambulatory and nonambulatory activities. Seventy-five adults (21–39 years) completed seven simulated activities of daily living (e.g., sitting, vacuuming, folding laundry) and an incremental treadmill protocol from 0.22 to 2.2 m/s. Directly observed steps were hand-tallied. Participants wore GENEActiv and ActiGraph accelerometers, one of each on their waist and on their nondominant wrist. Raw acceleration (g) signals from the anterior–posterior, medial–lateral, vertical, and vector magnitude directions were assessed separately for each device. Signals were demeaned across all activities and band-pass filtered (0.25, 2.5 Hz). Steps were detected via peak picking, with optimal thresholds (i.e., minimized absolute error from accumulated hand counted) determined by iterating minimum acceleration values to detect steps. Step counts were converted into cadence (steps/minute), and k-fold cross-validation quantified error (root mean squared error [RMSE]). We report optimal thresholds for use of either device on the waist (threshold = 0.0267g) and wrist (threshold = 0.0359g) using the vector magnitude signal. These thresholds yielded low error for the waist (RMSE

The natural transition from walking to running occurs in adults at ≅140 steps/min. It is unknown when this transition occurs in children and adolescents. The purpose of this study was to develop a model to predict age- and anthropometry-specific preferred transition cadences in individuals 6-20 years of age. Sixty-nine individuals performed sequentially faster 5-min treadmill walking bouts, starting at 0.22 m/s and increasing by 0.22 m/s until completion of the bout during which they freely chose to run. Steps accumulated during each bout were directly observed and converted to cadence (steps/min). A logistic regression model was developed to predict preferred transition cadences using the best subset of parameters. The resulting model, which included age, sex, height, and BMI z-score, produced preferred transition cadences that accurately classified gait behaviour (k-fold cross-validated prediction accuracy =97.02%). This transition cadence ranged from 136-161 steps/min across the developmental age range studied. The preferred transition cadence represents a simple and practical index to predict and classify gait behaviour from wearable sensors in children, adolescents, and young adults. Moreover, herein we provide an equation and an open access online R Shiny app that researchers, practitioners, or clinicians can use to predict individual-specific preferred transition cadences.

Background: The authors conducted a scoping review as a first step toward establishing harmonized (ie, consistent and compatible), empirically based best practices for validating step-counting wearable technologies. Purpose: To catalog studies validating step-counting wearable technologies during treadmill ambulation. Methods: The authors searched PubMed and SPORTDiscus in August 2019 to identify treadmill-based validation studies that employed the criterion of directly observed (including video recorded) steps and cataloged study sample characteristics, protocol details, and analytical procedures. Where reported, speed- and wear location–specific mean absolute percentage error (MAPE) values were tabulated. Weighted median MAPE values were calculated by wear location and a 0.2-m/s speed increment. Results: Seventy-seven eligible studies were identified: most had samples averaging 54% (SD = 5%) female and 27 (5) years of age, treadmill protocols consisting of 3 to 5 bouts at speeds of 0.8 (0.1) to 1.6 (0.2) m/s, and reported measures of bias. Eleven studies provided MAPE values at treadmill speeds of 1.1 to 1.8 m/s; their weighted median MAPE values were 7% to 11% for wrist-worn, 1% to 4% for waist-worn, and ≤1% for thigh-worn devices. Conclusions: Despite divergent study methodologies, the authors identified common practices and summarized MAPE values representing device step-count accuracy during treadmill walking. These initial empirical findings should be further refined to ultimately establish harmonized best practices for validating wearable technologies.

PURPOSE This study aimed to develop cadence-based metabolic equations (CME) for predicting the intensity of level walking and evaluate these CME against the widely adopted American College of Sports Medicine (ACSM) Metabolic Equation, which predicts walking intensity from speed and grade. METHODS Two hundred and thirty-five adults (21-84 yr of age) completed 5-min level treadmill walking bouts between 0.22 and 2.24 m·s, increasing by 0.22 m·s for each bout. Cadence (in steps per minute) was derived by dividing directly observed steps by bout duration. Intensity (oxygen uptake; in milliliters per kilogram per minute) was measured using indirect calorimetry. A simple CME was developed by fitting a least-squares regression to the cadence-intensity relationship, and a full CME was developed through best subsets regression with candidate predictors of age, sex, height, leg length, body mass, body mass index (BMI), and percent body fat. Predictive accuracy of each CME and the ACSM metabolic equation was evaluated at normal (0.89-1.56 m·s) and all (0.22-2.24 m·s) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL·kg·min). RESULTS On average, the simple CME predicted intensity within ~1.8 mL·kg·min (~0.5 METs) at normal walking speeds and with negligible (

Background The purpose of this study was to determine the dose–response association between habitual physical activity (PA) and cognitive function using a nationally representative data set of U.S. older adults aged ≥60 years. Methods We used data from the 2011–2014 National Health and Nutrition Examination Survey (n = 2 441, mean [SE] age: 69.1 [0.2] years, 54.7% females). Cognitive function was assessed using the digit symbol substitution test (DSST) and animal fluency test (AFT). Habitual PA was collected using a triaxial accelerometer worn on participants’ nondominant wrist. PA was expressed as 2 metrics using monitor-independent movement summary (MIMS) units: the average of Daily MIMS (MIMS/day) and peak 30-minute MIMS (Peak-30MIMS; the average of the highest 30 MIMS min/d). Sample weight-adjusted multivariable linear regression was performed to determine the relationship between each cognitive score and MIMS metric while adjusting for covariates. Results After controlling for covariates, for each 1 000-unit increase in Daily MIMS, DSST score increased (β-coefficient [95% CIs]) by 0.67 (0.40, 0.93), whereas AFT score increased by 0.13 (0.04, 0.22); for each 1-unit increase in Peak-30MIMS, DSST score increased by 0.56 (0.42, 0.70), whereas AFT score increased by 0.10 (0.05, 0.15), all p < .001. When including both MIMS metrics in a single model, the association between Peak-30MIMS and cognitive scores remained significant (p < .01), whereas Daily MIMS did not. Conclusions Our findings suggest that higher PA (both daily accumulated and peak effort) is associated with better cognitive function in the U.S. older adult population.

Background: A walking cadence of ≥100 steps/min corresponds to minimally moderate intensity, absolutely defined as ≥3 metabolic equivalents (METs). This threshold has primarily been calibrated during treadmill walking. There is a need to determine the classification accuracy of this cadence threshold to predict intensity during overground walking. Methods: In this laboratory-based cross-sectional investigation, participants (N = 75, 49.3% women, age 21–40 y) performed a single 5-minute overground (hallway) walking trial at a self-selected preferred pace. Steps accumulated during each trial were hand tallied and converted to cadence (steps/min). Oxygen uptake was measured using indirect calorimetry and converted to METs. The classification accuracy (sensitivity, specificity, overall accuracy, and positive predictive value) of ≥100 steps/min to predict ≥3 METs was calculated. Results: A cadence threshold of ≥100 steps/min yielded an overall accuracy (combined sensitivity and specificity) of 73.3% for predicting minimally moderate intensity. Moreover, for individuals walking at a cadence ≥100 steps/min, the probability (positive predictive value) of achieving minimally moderate intensity was 80.3%. Conclusions: Although primarily developed using treadmill-based protocols, a cadence threshold of ≥100 steps/min for young adults appears to be a valid heuristic value (evidence-based, rounded, practical) associated with minimally moderate intensity during overground walking performed at a self-selected preferred pace.

Background Heuristic cadence (steps/min) thresholds of ≥100 and ≥ 130 steps/min correspond with absolutely-defined moderate (3 metabolic equivalents [METs]; 1 MET = 3.5 mL O2·kg− 1·min− 1) and vigorous (6 METs) intensity, respectively. Scarce evidence informs cadence thresholds for relatively-defined moderate (≥ 64% heart rate maximum [HRmax = 220-age], ≥ 40%HR reserve [HRR = HRmax -HRresting, and ≥ 12 Rating of Perceived Exertion [RPE]); or vigorous intensity (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE). Purpose To identify heuristic cadence thresholds corresponding with relatively-defined moderate and vigorous intensity in 21–60-year-olds. Methods In this cross-sectional study, 157 adults (40.4 ± 11.5 years; 50.6% men) completed up to twelve 5-min treadmill bouts, beginning at 0.5 mph and increasing by 0.5 mph. Steps were directly observed, HR was measured with chest-worn monitors, and RPE was queried in the final minute of each bout. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds, stratified by age (21–30, 31–40, 41–50, and 51–60 years). Reconciliation of the two analytical models, including trade-offs between sensitivity, specificity, positive and negative predictive values, and overall accuracy, yielded final heuristic cadences. Results Across all moderate intensity indicators, the segmented regression models estimated optimal cadence thresholds ranging from 123.8–127.5 (ages 21–30), 120.2–126.0 (ages 31–40), 117.7–122.7 (ages 41–50), and 113.3–116.1 steps/min (ages 51–60). Corresponding values for vigorous intensity were 140.3–144.1, 139.6–142.6, 139.3–143.6, and 131.6–132.8 steps/min, respectively. ROC analysis estimated chronologically-arranged age groups’ cadence thresholds ranging from 114.5–118, 113.5–114.5, 104.6–112.9, and 103.6–106.0 across all moderate intensity indicators, and 124.5, 121.5, 117.2–122.2, and 113.0 steps/min, respectively, for vigorous intensity. Conclusions Heuristic cadence thresholds corresponding to relatively-defined moderate intensity for the chronologically-arranged age groups were ≥ 120, 120, 115, and 110 steps/min, regardless of the intensity indicator (i.e., % HRmax, %HRR, or RPE). Corresponding heuristic values for vigorous intensity indicators were ≥ 135, 130, 125, and 120 steps/min. These cadences are useful for predicting/programming intensity aligned with age-associated differences in physiological response to, and perceived experiences of, moderate and/or vigorous intensity. Trial registration Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

The purpose of this study was to explore the extent of multifractality in unperturbed and constrained locomotion, and to determine if multifractality predicted gait adaptability. Young, healthy participants (n = 15) walked at preferred and slow speeds, as well as asymmetrically (one leg at half speed) on a split-belt treadmill. Stride time multifractality was assessed via local detrended fluctuation analysis, which evaluates the evolution of fluctuations both spatially and temporally. Unperturbed walking exhibited monofractal behavior. Asymmetric walking displayed greater multifractality in the faster moving limb, indicating more intermittent periods of extreme high or low variance. Multifractality was not associated with adaptation to asymmetric walking. These findings further suggest that unperturbed locomotion is monofractal and establish that perturbed walking yields multifractal behavior.

Human locomotion is an inherently complex activity that requires the coordination and control of neurophysiological and biomechanical degrees of freedom across various spatiotemporal scales. Locomotor patterns must constantly be altered in the face of changing environmental or task demands, such as heterogeneous terrains or obstacles. Variability in stride times occurring at short time scales (e.g., 5–10 strides) is statistically correlated to larger fluctuations occurring over longer time scales (e.g., 50–100 strides). This relationship, known as fractal dynamics, is thought to represent the adaptive capacity of the locomotor system. However, this has not been tested empirically. Thus, the purpose of this study was to determine if stride time fractality during steady state walking associated with the ability of individuals to adapt their gait patterns when locomotor speed and symmetry are altered. Fifteen healthy adults walked on a split-belt treadmill at preferred speed, half of preferred speed, and with one leg at preferred speed and the other at half speed (2:1 ratio asymmetric walking). The asymmetric belt speed condition induced gait asymmetries that required adaptation of locomotor patterns. The slow speed manipulation was chosen in order to determine the impact of gait speed on stride time fractal dynamics. Detrended fluctuation analysis was used to quantify the correlation structure, i.e., fractality, of stride times. Cross-correlation analysis was used to measure the deviation from intended anti-phasing between legs as a measure of gait adaptation. Results revealed no association between unperturbed walking fractal dynamics and gait adaptability performance. However, there was a quadratic relationship between perturbed, asymmetric walking fractal dynamics and adaptive performance during split-belt walking, whereby individuals who exhibited fractal scaling exponents that deviated from 1/f performed the poorest. Compared to steady state preferred walking speed, fractal dynamics increased closer to 1/f when participants were exposed to asymmetric walking. These findings suggest there may not be a relationship between unperturbed preferred or slow speed walking fractal dynamics and gait adaptability. However, the emergent relationship between asymmetric walking fractal dynamics and limb phase adaptation may represent a functional reorganization of the locomotor system (i.e., improved interactivity between degrees of freedom within the system) to be better suited to attenuate externally generated perturbations at various spatiotemporal scales.

In human locomotion, the magnitude of gait variability is a strong predictor of fall risk and frailty due to aging and disease. Beyond variability magnitude, the past two decades have provided emerging alternative methodologies for studying biological variability. Specifically, coordination variability has been found to be critically important within a healthy, adaptive system. While many activities aim to minimize end-point variability, greater coordination variability indicates a more flexible system, and is greater in experts compared to novices, or healthy compared to diseased individuals. Finally, variability structure (i.e., fractal dynamics) may describe the overall adaptive capacity of the locomotor system. We provide empirical support that fractal dynamics are associated with step length symmetry during challenging split-belt treadmill walking. Individuals whose fractal scaling approached 1/f fractal scaling during constrained walking also exhibited the best gait adaptability performance. Importantly, this relation between fractality and gait adaptability was not observed in unperturbed preferred speed walking.

PurposeTo provide empirically-supported thresholds for step-based intensity (i.e., peak 30-min cadence; average of the top 30 steps/min in a day) and steps/day in relation to cardiometabolic health outcomes.MethodsReceiver operating characteristic curve analysis was applied to the National Health and Nutrition Examination Survey (NHANES) 2005-2006 accelerometer-derived step data to determine steps/day and peak 30-min cadence as risk screening values (i.e., thresholds) for fasting glucose, body mass index, waist circumference, high blood pressure, triglycerides, and HDL cholesterol. Thresholds for peak 30-min cadence and steps/day were derived that, when exceeded, classify the absence of each cardiometabolic risk factor. Additionally, logistic regression models that included the influence of age and smoking were developed using the sample weights, primary sampling units (PSUs), and stratification variables provided by the NHANES survey. Finally, a decision tree analysis was performed to delineate criteria for at-risk versus healthy populations using cadence bands.ResultsPeak 30-min cadence thresholds across cardiometabolic outcomes ranged from 66-72 steps/min. Steps/day thresholds ranged from 4325-6192 steps/day. Higher thresholds were observed in men compared to women. In men, higher steps/day thresholds were observed in age ranges of 30-39, while in women, higher thresholds were observed in the age-range 50-59 years. Decision trees for classifying being at low risk for metabolic syndrome contained one risk-free leaf at higher cadence bands, specifically for any time accumulated at ≥120 steps/min.ConclusionsMinimum thresholds representing absence of cardiometabolic risk range from 4325-6192 steps/day and 66-72 steps/min for peak 30-min cadence. Any time accumulated at ≥120 steps/min was associated with an absence of cardiometabolic risk. Although based on cross-sectional data, these thresholds represent potentially important and clinically interpretable daily physical activity goals.

The pickup of visual information is critical for controlling movement and maintaining situational awareness in dangerous situations. Altered coordination while wearing protective equipment may impact the likelihood of injury or death. This investigation examined the consequences of load magnitude and distribution on situational awareness, segmental coordination and head gaze in several protective equipment ensembles. Twelve soldiers stepped down onto force plates and were instructed to quickly and accurately identify visual information while establishing marksmanship posture in protective equipment. Time to discriminate visual information was extended when additional pack and helmet loads were added, with the small increase in helmet load having the largest effect. Greater head-leading and in-phase trunk-head coordination were found with lighter pack loads, while trunk-leading coordination increased and head gaze dynamics were more disrupted in heavier pack loads. Additional armour load in the vest had no consequences for Time to discriminate, coordination or head dynamics. This suggests that the addition of head borne load be carefully considered when integrating new technology and that up-armouring does not necessarily have negative consequences for marksmanship performance. Practitioner Summary: Understanding the trade-space between protection and reductions in task performance continue to challenge those developing personal protective equipment. These methods provide an approach that can help optimise equipment design and loading techniques by quantifying changes in task performance and the emergent coordination dynamics that underlie that performance.

Background Previous studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities. Purpose To establish definitive heuristic (i.e., evidence-based, practical, rounded) thresholds linking cadence with absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity. Methods In this laboratory-based cross-sectional study, 76 healthy adults (10 men and 10 women representing each 5-year age-group category between 21 and 40 years, BMI = 24.8 ± 3.4 kg/m2) performed a series of 5-min treadmill bouts separated by 2-min rests. Bouts began at 0.5 mph and increased in 0.5 mph increments until participants: 1) chose to run, 2) achieved 75% of their predicted maximum heart rate, or 3) reported a Borg rating of perceived exertion > 13. Cadence was hand-tallied, and intensity (METs) was measured using a portable indirect calorimeter. Optimal cadence thresholds for moderate and vigorous ambulatory intensities were identified using a segmented regression model with random coefficients, as well as Receiver Operating Characteristic (ROC) models. Positive predictive values (PPV) of candidate heuristic thresholds were assessed to determine final heuristic values. Results Optimal cadence thresholds for 3 METs and 6 METs were 102 and 129 steps/min, respectively, using the regression model, and 96 and 120 steps/min, respectively, using ROC models. Heuristic values were set at 100 steps/min (PPV of 91.4%), and 130 steps/min (PPV of 70.7%), respectively. Conclusions Cadence thresholds of 100 and 130 steps/min can serve as reasonable heuristic thresholds representative of absolutely-defined moderate and vigorous ambulatory intensity, respectively, in 21–40 year olds. These values represent useful proxy values for recommending and modulating the intensity of ambulatory behavior and/or as measurement thresholds for processing accelerometer data. Trial registration Clinicaltrials.gov (NCT02650258). Electronic supplementary material The online version of this article (10.1186/s12966-019-0769-6) contains supplementary material, which is available to authorized users.

Step length and cadence (i.e., step frequency or steps/minute) maintain an invariant proportion across a range of walking speeds, known as the walk ratio (WR = step length/cadence). While step length is a difficult parameter to manipulate, cadence is readily modifiable using rhythmic auditory cuing (RAC; e.g., synchronizing step timing to a metronome or music tempo).The purpose of this study was to determine the effects of RAC-guided cadences on enacted cadence, step length, WR, and gait speed during overground walking.Sixteen healthy young adults repeatedly crossed a GAITRite electronic walkway while attempting to synchronize step timing to RAC-guided (metronome) tempos of 80 to 140 beats per minute. Mean absolute percent error (MAPE) was used to compare RAC tempos to enacted cadence. Repeated-measures analyses of variance were performed to test for the effects of RAC on cadence, step length, WR, and gait speed. Moreover, simple linear regressions were used to determine the precise stepwise relationship between RAC conditions and each variable.Participants successfully matched their cadence to RAC beats (MAPE1.1%). Cadence increased proportionally to RAC (linear regression slope = 1.02), while step length also increased but at a slower rate (slope = 0.40). These dissimilar slopes resulted in a modified WR that systematically decreased with increasing cadence, although ultimately gait speed increased with increasing cadence (slope = 1.41). This relationship indicates that every 10 steps/minute incremental increase in cadence corresponded with a 14 cm/s increase in gait speed.Gait speed appears to increase in a predictable manner when cadence is guided by RAC during overground walking irrespective of apparent changes to the WR.

Investigators have recently demonstrated that standing long jump performance is enhanced when participants focus their attention externally instead of their leg action but found no differences when examining peak force. The purpose of this study was to examine kinetic and kinematic properties associated with the standing long jump that may explain disparities between an internal and external focus of attention. It was hypothesized that the external focus condition would exhibit greater impulse values and a more optimal projection angle (45°) than the internal condition. Twenty-one participants each performed 5 total jumps: 1 baseline jump, in which no focus instructions were given, followed by 4 remaining jumps in which either internal or external focus instructions were introduced in a counter-balanced manner. Analysis of variance revealed that the external condition jumped significantly farther than the internal and baseline conditions. Analyses of kinetic measures (i.e., peak force and impulse) revealed no significant differences among conditions. However, there was a significant difference between the internal and baseline conditions compared with the external condition with respect to projection angle. Specifically, participants in the external focus condition exhibited an average projection angle of 45.7°, compared with the internal (49.5°) and baseline (49.0°) conditions. Therefore, the observed difference in jump distance among conditions can be explained by the external condition producing a more optimal projection angle. The results of this study partially support the constrained action hypothesis.

An external focus of attention has been shown to improve balance measures during static postural tasks. The purpose of this study was to evaluate the effects of different attentional focus strategies in response to a perturbation while performing a dynamic balance task. Participants (n = 29) performed a dynamic balance task that consisted of stepping onto an uneven surface while attempting to continuously walk in a straight line. The orientation of the surface was unknown to the participants. During the external focus conditions, participants were instructed to focus on the surface they walked on. During the internal focus conditions, participants were instructed to focus on keeping their body over their feet. Analyses revealed that the external focus condition exhibited significantly less lateral displacement from the intended walking line following the perturbation (4.56 ± 2.56 cm) than the internal (5.61 ± 2.89 cm, p = .019) and baseline (6.07 ± 2.6 cm, p = .004) conditions. These data indicate that participants were more resilient to the perturbing surface when their attention was focused on external information. Thus, participants were able to respond to a perturbation more effectively when utilizing an external focus of attention.

Human stride intervals exhibit statistically persistent fluctuations over a wide range of timescales. Numerous studies have examined stride interval correlations during overground and treadmill walking. However, the practices and procedures for pre-preprocessing gait data vary considerably. This paper examined how differences in sampling rate and gait event detection affected stride interval correlations measured using detrended fluctuation analysis. Sampling rates ranged from 30–360 Hz. Three common kinematic event detection algorithms were compared to a force-based reference. Lower sampling frequencies failed to capture subtle variations in gait cycle timing, which reduced the strength of stride interval correlations. The kinematic event detection algorithms produced slightly higher, but comparable, estimates of stride interval correlations relative to the force-based reference. Guidelines and considerations for assessing stride interval correlations and the implications of these findings are discussed.

Cadence (steps/minute) is an emerging proxy-indicator of ambulatory metabolic intensity. 100 steps/minute is a consistent threshold associated with absolutely-defined moderate intensity (i.e., 3 metabolic equivalents or METs; 1 MET=3.5 mL O2/kg/min) in adults up to 60 years of age, but its stability in older adults is not clear. Conflicting findings indicate older adults attain moderate intensity at lower, but also higher, cadences. Differences may be due to relative vs. absolute definitions of intensity with age. We present the preliminary results from CADENCE-Adults, an NIH-funded study evaluating cadence and intensity across the adult lifespan up to 85 years of age.