Cadence (steps/min) and relative intensity in 61 to 85-year-olds: the CADENCE-Adults study.

BACKGROUND: We previously demonstrated that a heuristic (i.e., evidence-based, rounded yet practical) cadence threshold of ≥ 100 steps/min was associated with absolutely-defined moderate intensity physical activity (i.e., ≥ 3 metabolic equivalents [METs]) in older adults 61-85 years of age. Although it was difficult to ascertain achievement of absolutely-defined vigorous (6 METs) intensity, ≥ 130 steps/min was identified as a defensible threshold for this population. However, little evidence exists regarding cadence thresholds and relatively-defined moderate intensity indicators, including ≥ 64% heart rate [HR] maximum [HRmax = 220-age], ≥ 40% HR reserve [HRR = HRmax-HRresting], and ≥ 12 Borg Scale Rating of Perceived Exertion [RPE]; or vigorous intensity indicators including ≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE. PURPOSE: To analyze the relationship between cadence and relatively-defined physical activity intensity and identify relatively-defined moderate and vigorous heuristic cadence thresholds for older adults 61-85 years of age. METHODS: Ninety-seven ostensibly healthy adults (72.7 ± 6.9 years; 49.5% women) completed up to nine 5-min treadmill walking bouts beginning at 0.5 mph (0.8 km/h) and progressing by 0.5 mph speed increments (with 2-min rest between bouts). Directly-observed (and video-recorded) steps were hand-counted, HR was measured using a chest-strapped monitor, and in the final minute of each bout, participants self-reported RPE. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds associated with relatively-defined moderate (≥ 64%HRmax, ≥ 40%HRR, and ≥ 12 RPE) and vigorous (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE) intensities. A compromise between the two analytical methods, including Youden's Index (a sum of sensitivity and specificity), positive and negative predictive values, and overall accuracy, yielded final heuristic cadences. RESULTS: Across all relatively-defined moderate intensity indicators, segmented regression models and ROC curve analyses identified optimal cadence thresholds ranging from 105.9 to 112.8 steps/min and 102.0-104.3 steps/min, respectively. Comparable values for vigorous intensity indicators ranged between126.1-132.1 steps/min and 106.7-116.0 steps/min, respectively. Regardless of the relatively-defined intensity indicator, the overall best heuristic cadence threshold aligned with moderate intensity was ≥ 105 steps/min. Vigorous intensity varied between ≥ 115 (greater sensitivity) or ≥ 120 (greater specificity) steps/min. CONCLUSIONS: Heuristic cadence thresholds align with relatively-defined intensity indicators and can be useful for studying and prescribing older adults' physiological response to, and/or perceived experience of, ambulatory physical activity. TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

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.

A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study.

BACKGROUND: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). METHODS: Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). RESULTS: Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045). CONCLUSIONS: Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy. TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258. Registered 24 December 2015.

Classification of moderate-intensity overground walking speed in 21- to 85-year-old adults.

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.

Walking cadence (steps/min) and intensity in 61-85-year-old adults: the CADENCE-Adults study.

BACKGROUND: Heuristic (i.e., evidence-based, rounded) cadences of ≥100 and ≥ 130 steps/min have consistently corresponded with absolutely-defined moderate (3 metabolic equivalents [METs]) and vigorous (6 METs) physical activity intensity, respectively, in adults 21-60 years of age. There is no consensus regarding similar thresholds in older adults. PURPOSE: To provide heuristic cadence thresholds for 3, 4, 5, and 6 METs in 61-85-year-old adults. METHODS: Ninety-eight community-dwelling ambulatory and ostensibly healthy older adults (age = 72.6 ± 6.9 years; 49% women) walked on a treadmill for a series of 5-min bouts (beginning at 0.5 mph with 0.5 mph increments) in this laboratory-based cross-sectional study until: 1) transitioning to running, 2) reaching ≥75% of their age-predicted maximum heart rate, or 3) reporting a Borg rating of perceived exertion > 13. Cadence was directly observed and hand-tallied. Intensity (oxygen uptake [VO2] mL/kg/min) was assessed with indirect calorimetry and converted to METs (1 MET = 3.5 mL/kg/min). Cadence thresholds were identified via segmented mixed effects model regression and using Receiver Operating Characteristic (ROC) curves. Final heuristic cadence thresholds represented an analytical compromise based on classification accuracy (sensitivity, specificity, positive and negative predictive value, and overall accuracy). RESULTS: Cadences of 103.1 (95% Prediction Interval: 70.0-114.2), 116.4 (105.3-127.4), 129.6 (118.6-140.7), and 142.9 steps/min (131.8-148.4) were identified for 3, 4, 5, and 6 METs, respectively, based on the segmented regression. Comparable values based on ROC analysis were 100.3 (95% Confidence Intervals: 95.7-103.1), 111.5 (106.1-112.9), 116.0 (112.4-120.2), and 128.6 steps/min (128.3-136.4). Heuristic cadence thresholds of 100, 110, and 120 were associated with 3, 4, and 5 METs. Data to inform a threshold for ≥6 METs was limited, as only 6/98 (6.0%) participants achieved this intensity. CONCLUSIONS: Consistent with previous data collected from 21-40 and 41-60-year-old adults, heuristic cadence thresholds of 100, 110, and 120 steps/min were associated with 3, 4, and 5 METs, respectively, in 61-85-year-old adults. Most older adults tested did not achieve the intensity of ≥6 METs; therefore, our data do not support establishing thresholds corresponding with this intensity level. TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258 . Registered 24 December 2015.

Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study.

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), 121.3-126.0 (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, 140.2-142.6, 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 127.5, 121.5, 117.2-123.2, 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 105 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.

Using Cadence to Predict the Walk-to-Run Transition in Children and Adolescents: A Logistic Regression Approach.

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.

Walking cadence (steps/min) and intensity in 41 to 60-year-old adults: the CADENCE-adults study.

BACKGROUND: In younger adults (i.e., those < 40 years of age) a walking cadence of 100 steps/min is a consistently supported threshold indicative of absolutely-defined moderate intensity ambulation (i.e., ≥ 3 metabolic equivalents; METs). Less is known about the cadence-intensity relationship in adults of middle-age. PURPOSE: To establish heuristic (i.e., evidence-based, practical, rounded) cadence thresholds for absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity in adults 41 to 60 years of age. METHODS: In this cross-sectional study, 80 healthy adults of middle-age (10 men and 10 women representing each 5-year age-group between 41 to 60 years; body mass index = 26.0 ± 4.0 kg/m2) walked on a treadmill for 5-min bouts beginning at 0.5 mph and increasing in 0.5 mph increments. Performance termination criteria included: 1) transitioning to running, 2) reaching 75% of age-predicted maximum heart rate, or 3) reporting a Borg rating of perceived exertion > 13. Cadence was directly observed (i.e., hand tallied). Intensity (i.e., oxygen uptake [VO2] mL/kg/min) was assessed with an indirect calorimeter and converted to METs (1 MET = 3.5 mL/kg/min). A combination of segmented regression and Receiver Operating Characteristic (ROC) modeling approaches was used to identify optimal cadence thresholds. Final heuristic thresholds were determined based on an evaluation of classification accuracy (sensitivity, specificity, positive and negative predictive value, overall accuracy). RESULTS: The regression model identified 101.7 (95% Predictive Interval [PI]: 54.9-110.6) and 132.1 (95% PI: 122.0-142.2) steps/min as optimal cadence thresholds for 3 METs and 6 METs, respectively. Corresponding values based on ROC models were 98.5 (95% Confidence Intervals [CI]: 97.1-104.9) and 117.3 (95% CI: 113.1-126.1) steps/min. Considering both modeling approaches, the selected heuristic thresholds for moderate and vigorous intensity were 100 and 130 steps/min, respectively. CONCLUSIONS: Consistent with our previous report in 21 to 40-year-old adults, cadence thresholds of 100 and 130 steps/min emerged as heuristic values associated with 3 and 6 METs, respectively, in 41 to 60-year-old adults. These values were selected based on their utility for public health messaging and on the trade-offs in classification accuracy parameters from both statistical methods. Findings will need to be confirmed in older adults and in free-living settings.

Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults.

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 ).

Cadence (steps/min) and intensity during ambulation in 6-20 year olds: the CADENCE-kids study.

BACKGROUND: Steps/day is widely utilized to estimate the total volume of ambulatory activity, but it does not directly reflect intensity, a central tenet of public health guidelines. Cadence (steps/min) represents an overlooked opportunity to describe the intensity of ambulatory activity. We sought to establish thresholds linking directly observed cadence with objectively measured intensity in 6-20 year olds. METHODS: One hundred twenty participants completed multiple 5-min bouts on a treadmill, from 13.4 m/min (0.80 km/h) to 134.0 m/min (8.04 km/h). The protocol was terminated when participants naturally transitioned to running, or if they chose to not continue. Steps were visually counted and intensity was objectively measured using a portable metabolic system. Youth metabolic equivalents (METy) were calculated for 6-17 year olds, with moderate intensity defined as ≥4 and < 6 METy, and vigorous intensity as ≥6 METy. Traditional METs were calculated for 18-20 year olds, with moderate intensity defined as ≥3 and < 6 METs, and vigorous intensity defined as ≥6 METs. Optimal cadence thresholds for moderate and vigorous intensity were identified using segmented random coefficients models and receiver operating characteristic (ROC) curves. RESULT: Participants were on average (± SD) aged 13.1 ± 4.3 years, weighed 55.8 ± 22.3 kg, and had a BMI z-score of 0.58 ± 1.21. Moderate intensity thresholds (from regression and ROC analyses) ranged from 128.4 steps/min among 6-8 year olds to 87.3 steps/min among 18-20 year olds. Comparable values for vigorous intensity ranged from 157.7 steps/min among 6-8 year olds to 119.3 steps/min among 18-20 year olds. Considering both regression and ROC approaches, heuristic cadence thresholds (i.e., evidence-based, practical, rounded) ranged from 125 to 90 steps/min for moderate intensity, and 155 to 125 steps/min for vigorous intensity, with higher cadences for younger age groups. Sensitivities and specificities for these heuristic thresholds ranged from 77.8 to 99.0%, indicating fair to excellent classification accuracy. CONCLUSIONS: These heuristic cadence thresholds may be used to prescribe physical activity intensity in public health recommendations. In the research and clinical context, these heuristic cadence thresholds have apparent value for accelerometer-based analytical approaches to determine the intensity of ambulatory activity.

Additional helmet and pack loading reduce situational awareness during the establishment of marksmanship posture.

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.

Standing Long Jump Performance With an External Focus of Attention Is Improved as a Result of a More Effective Projection Angle.

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.

Dose-Response Association Between Physical Activity (Daily MIMS, Peak 30-Minute MIMS) and Cognitive Function Among Older Adults: NHANES 2011-2014.

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 (ß-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.

Cadence (steps/min) as an indicator of the walk-to-run transition.

BACKGROUND: Humans naturally transition from walking to running at a point known as the walk-to-run transition (WRT). The WRT commonly occurs at a speed of ∼2.1 m/s (m/s) or a Froude number (dimensionless value considering leg length) of 0.5. Emerging evidence suggests the WRT can also be classified using a cadence of 140 steps/min. An accurate cadence-based WRT metric would aid in classifying wearable technology minute-level step metrics as walking vs. running. PURPOSE: To evaluate performance of 1) WRT predictors directly identified from a treadmill-based dataset of sequentially faster bouts, and 2) accepted WRT predictors compiled from previous literature. METHODS: Twenty-eight adults (71.4% men; age = 36.6 ± 12.8 years, BMI = 26.2 ± 4.7 kg/m2) completed a series of five-minute treadmill walking bouts increasing in 0.2 m/s increments until they freely chose to run. Optimal WRT values for speed, Froude number, and cadence were identified using receiver operating characteristic (ROC) curve analyses. WRT value performance was evaluated via classification accuracy metrics. RESULTS: Overall accuracies (metric, percent) according to WRT predictors from previous literature were: speed (2.1 m/s, 55.0%), Froude number (0.5, 76.8%), and cadence (140 steps/min, 91.1%), and those from the dataset herein were: speed (1.9 and 2.0 m/s, 78.6%), Froude number (0.68, 77.3%), and cadence (134, 139, and 141 steps/min, 92.9%). The three equally accurate cadence values support a heuristic range of cadence-based WRT values in young and middle-aged adults: 135-140 steps/min. SIGNIFICANCE: A tight range of cadence values performed better as WRT predictors compared to either previously reported or directly identified speed or Froude number values. These findings have important implications for gait classification, especially considering cadence is a simple metric which can be readily assessed across settings using direct observation or wearable technologies.

Development of a Cadence-based Metabolic Equation for Walking.

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 (<0.01 METs) bias. Including age, leg length, and BMI in the full CME marginally improved predictive accuracy (≤0.36 mL·kg·min [≤0.1 METs]), but may account for larger (up to 2.5 mL·kg·min [0.72 MET]) deviations in the cadence-intensity relationships of outliers in age, stature, and/or BMI. Both CME demonstrated 23%-35% greater accuracy and 2.2-2.8 mL·kg·min (0.6-0.8 METs) lower bias than the ACSM metabolic equation's speed-based predictions. CONCLUSIONS: Although the ACSM metabolic equation incorporates a grade component and is convenient for treadmill-based applications, the CME developed herein enables accurate quantification of walking intensity using a metric that is accessible during overground walking, as is common in free-living contexts.

A Transparent Method for Step Detection using an Acceleration Threshold.

Step-based metrics provide simple measures of ambulatory activity, yet device software either includes undisclosed proprietary step detection algorithms or simply do not compute step-based metrics. We aimed to develop and validate a simple algorithm to accurately detect steps across various ambulatory and non-ambulatory 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 0.22-2.2ms-1. Directly observed steps were hand-tallied. Participants wore GENEActiv and ActiGraph accelerometers, one of each on their waist and on their non-dominant wrist. Raw acceleration (g) signals from the anterior-posterior, medial-lateral, vertical, and vector magnitude (VM) directions were assessed separately for each device. Signals were demeaned across all activities and bandpass filtered [0.25, 2.5Hz]. 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 VM signal. These thresholds yielded low error for the waist (RMSE<173 steps, ≤2.28 steps/minute) and wrist (RMSE<481 steps, ≤6.47 steps/minute) across all activities, and outperformed ActiLife's proprietary algorithm (RMSE=1312 and 2913 steps, 17.29 and 38.06 steps/minute for the waist and wrist, respectively). The thresholds reported herein provide a simple, transparent framework for step detection using accelerometers during treadmill ambulation and activities of daily living for waist- and wrist-worn locations.

Toward Harmonized Treadmill-Based Validation of Step-Counting Wearable Technologies: A Scoping Review.

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.

Multifractality of Unperturbed and Asymmetric Locomotion.

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.