Comparison of older adults' steps per day using NL-1000 pedometer and two GT3X+ accelerometer filters

Comparison of daily step count between the Fitbit Inspire 3 and the activPAL 3 in adults with transtibial amputation

Introduction

Physical activity has significant positive effects on health. Accelerometers can be used to track daily physical activity. The Fitbit Inspire 3 is a commercially available health and fitness tracker, but its validity for tracking steps among individuals with transtibial amputation has not been examined. Therefore, the purpose of this study was to evaluate the concurrent validity of the Fitbit Inspire 3 for assessing free-living daily steps in adults with transtibial amputation.

Methods

Participants (n = 79) completed a general health survey and were provided with a Fitbit Inspire 3 and activPAL 3 accelerometer to wear concurrently for seven days in their home environment. Relationships between the activPAL and Fitbit Inspire 3 were examined using Pearson's Correlation. Paired samples t-tests, mean difference, mean absolute difference, and equivalence testing were used to compared daily step counts between Fitbit Inspire 3 and activPAL 3.

Results

Average step counts were 5,768 ± 3,750 (mean ± SD) and 4,674 ± 3,081 by the Fitbit Inspire 3 and activPAL, respectively. A high correlation (r = 0.93) but significant mean difference was found between the activPAL 3 and Fitbit Inspire 3 (p < 0.001). The mean absolute difference between the devices was 1,347 ± 1,184 steps. On average, the Fitbit Inspire 3 counted 1,094 ± 1,423 more daily steps than the activPAL 3. Equivalency could not be claimed between the devices.

Discussion

The Fitbit Inspire 3 counted more steps compared to the activPAL. Because of the significant mean differences and the large mean absolute difference between the devices, the activPAL 3 and Fitbit Inspire 3 are not interchangeable for estimating physical activity in individuals with transtibial amputation. However, due to the high correlation, the devices will produce similar classification rankings based on step counts.

Effect of Data Reduction Techniques on Daily Moderate to Vigorous Physical Activity Collected with ActiGraph® in People with COPD

ActiGraph® is a valid, frequently used, accelerometer to quantify moderate to vigorous physical activities (MVPA) in people with COPD. The impact of ActiGraph processing techniques on this population is unknown. This study aimed to explore the effect of data reduction techniques on MVPA in people with COPD. MVPA/day, through ActiGraph GT3X+, was estimated using: Troiano, Freedson 98 and FreedsonVM3 cutoffs, 15-s and 60-s epochs, and normal and low-frequency extension (LFE) filters. Cutoff, epoch, and filter effects were explored with Aligned Rank Transform-ANOVA. Lin's concordance correlation coefficients and Bland-Altman plots were used to evaluate agreement and bias between different techniques. The analysis included 136 people with COPD (79% male; 68 ± 8 years; FEV1 51 ± 17% predicted). MVPA/day differed according to cutoff, filter, and epoch selection (p-value < 0.001). FreedsonVM3 cutoff, 15-s epochs, and LFE yielded the highest MVPA (45 min/day, 68% of physically active participants). Troiano cutoff, 60-s epochs, and normal filter yielded the lowest MVPA (8 min/day, 20% of physically active participants). Only comparisons between Troiano and Freedson98 cutoffs presented an almost perfect agreement. ActiGraph data reduction techniques affected MVPA/day estimates and their interpretation at the individual and group level. Studies using different processing criteria should not be compared in people with COPD. Future studies with a gold standard are required to ascertain which processing technique produces the most accurate MVPA estimates in COPD. Meanwhile, future trials employing the ActiGraph GT3X+ may consider estimating MVPA based on Freedson VM3 cutofffs, 60-s epochs, and normal filter.

Physical activity moderates the association between executive function and functional connectivity in older adults

Recent evidence suggests that physical activity may influence the functional connectivity of the aging brain. The purpose of this study was to examine the influence of physical activity on the association between executive function and functional connectivity of key brain networks and graph theory metrics in community-dwelling older adults. Participants were 47 older adults (M = 73 years; SD = 5.92) who participated in neuropsychological testing, physical activity measurements, and magnetic resonance imaging (MRI). Seed-to-voxel moderation analyses and graph theory analyses were conducted. Physical activity was significantly positively associated with default mode network functional connectivity (DMN FC; Posterior Cingulate Gyrus, p-FDR = 0.005; Frontal Pole (L), p-FDR = 0.005; Posterior Cingulate Gyrus, p-FDR = 0.006; Superior Frontal Gyrus (L), p-FDR = 0.016) and dorsal attention network functional connectivity (DAN FC; Inferior Frontal Gyrus Pars Opercularis (R), p-FDR = 0.044). The interaction between physical activity and executive function on the DMN FC and DAN FC was analyzed. The interaction between executive function and physical activity was significantly associated with DMN FC. When this significant interaction was probed, the association between physical activity and DMN FC differed between levels of high and low executive function such that the association was only significant at levels of high executive function. These results suggest that greater physical activity in later life is associated with greater DMN and DAN FC and provides evidence for the importance of physical activity in cognitively healthy older adults.

Validity of Hip and Ankle Worn Actigraph Accelerometers for Measuring Steps as a Function of Gait Speed during Steady State Walking and Continuous Turning

This study aimed to investigate the accuracy and reliability of hip and ankle worn Actigraph GT3X+ (AG) accelerometers to measure steps as a function of gait speed. Additionally, the effect of the low frequency extension filter (LFEF) on the step accuracy was determined. Thirty healthy individuals walked straight and walked with continuous turns in different gait speeds. Number of steps were recorded with a hip and ankle worn AG, and with a Stepwatch (SW) activity monitor positioned around the right ankle, which was used as a reference for step count. The percentage agreement, interclass correlation coefficients and Bland–Altmann plots were determined between the AG and the reference SW across gait speeds for the two walking conditions. The ankle worn AG with the default filter was the most sensitive for step detection at >0.6 m/s, whilst accurate step detection for gait speeds < 0.6 m/s were only observed when applying the LFEF. The hip worn AG with the default filter showed poor accuracy (12–78%) at gait speeds < 1.0 m/s whereas the accuracy increased to >87% for gait speeds < 1.0 m/s when applying the LFEF. Ankle worn AG was the most sensitive to measure steps at a vast range of gait speeds. Our results suggest that sensor placement and filter settings need to be taken into account to provide accurate estimates of step counts.

Use of Connected Technologies to Assess Barriers and Stressors for Age and Disability-Friendly Communities

Background: The benefits of engaging in outdoor physical activity are numerous for older adults. However, previous work on outdoor monitoring of physical activities did not sufficiently identify how older adults characterize and respond to diverse elements of urban built environments, including structural characteristics, safety attributes, and aesthetics.

Objective: To synthesize emerging multidisciplinary trends on the use of connected technologies to assess environmental barriers and stressors among older adults and for persons with disability.

Methods: A multidisciplinary overview and literature synthesis.

Results: First, we review measurement and monitoring of outdoor physical activity in community environments and during transport using wearable sensing technologies, their contextualization and using smartphone-based applications. We describe physiological responses (e.g., gait patterns, electrodermal activity, brain activity, and heart rate), stressors and physical barriers during outdoor physical activity. Second, we review the use of visual data (e.g., Google street images, Street score) and machine learning algorithms to assess physical (e.g., walkability) and emotional stressors (e.g., stress) in community environments and their impact on human perception. Third, we synthesize the challenges and limitations of using real-time smartphone-based data on driving behavior, incompatibility with software data platforms, and the potential for such data to be confounded by environmental signals in older adults. Lastly, we summarize alternative modes of transport for older adults and for persons with disability.

Conclusion: Environmental design for connected technologies, interventions to promote independence and mobility, and to reduce barriers and stressors, likely requires smart connected age and disability-friendly communities and cities.

Association between different cutoff points for objectively measured moderate-to-vigorous physical activity and cardiometabolic markers in older adults

BACKGROUND

Regular moderate-to-vigorous physical activity (MVPA) is inversely associated with cardiovascular diseases in older adults. However, it remains unclear how the use of different cutoff points affects the associations with cardiovascular markers.

OBJECTIVE

To analyze the association between different cutoff points for objectively measured MVPA and cardiometabolic markers in older adults.

METHODS

This was a cross-sectional study involving 425 older adults (aged ≥60 years) from the EpiFloripa Ageing cohort study. We used ActiGraph accelerometers to measure MVPA in total minutes and in bouts (≥10 min) for at least 4 days. The tested cardiometabolic markers were waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein cholesterol (HDL-c), body mass index (BMI), triglycerides, fasting glucose and glycated hemoglobin (HbA1c). To identify MVPA, we used the cutoff points of Freedson et al. (≥ 1952 counts/min), Copeland and Esliger (≥ 1040 counts/min), and Troiano et al (≥ 2020 counts/min).

RESULTS

We observed significant differences in MVPA (total and bouts) between the different cutoff points (p < .001). The magnitude and number of associations between cardiometabolic markers and MVPA varied according to measurement units (total minutes: WC, SBP, DBP, HDL-c, BMI, triglycerides, glucose, and HbA1c versus bouts: WC, DBP, SBP HDL-c, and BMI) and cutoff points (higher associations for the Copeland and Esliger cutoff in total minutes and for the Troiano et al. cutoff in bouts of ≥10 min).

CONCLUSION

The use of different cutoff points in evaluating accelerometer-measured MVPA in older adults provides conflicting estimates, which emphasizes the importance of standardized thresholds.

Quality over quantity: skeletal loading intensity plays a key role in understanding the relationship between physical activity and bone density in postmenopausal women

OBJECTIVE

Increasing physical activity (PA) is regularly cited as a modifiable target to improve health outcomes and quality of life in the aging population, especially postmenopausal women who exhibit low bone mineral density (BMD) and high fracture risk. In this cross-sectional study, we aimed to quantify real-world PA and its association with BMD in postmenopausal women.

METHODS

Seventy postmenopausal women, aged 46 to 79 years, received a dual-energy X-ray absorptiometry scan measuring total hip BMD and wore bilateral triaxial accelerometers on the ankles for 7 days to measure PA in their free-living environment. Custom step detection and peak vertical ground reaction force estimation algorithms, sensitive to both quantity and intensity of PA, were used to calculate a daily bone density index (BDI) for each participant. Multiple regression was used to quantify the relationship between total hip BMD, age, step counts, and mean BDI over the span of 7 days of data collection.

RESULTS

All participants completed the full 7 days of PA monitoring, totaling more than 7 million detected steps. Participants averaged 14,485 ± 4,334 steps daily with mean peak vertical ground reaction force stepping loads of 675 ± 121 N during daily living. Across the population, total hip BMD was found to be significantly correlated with objective estimates of mean BDI (r = 0.44), as well as participant age (r = 0.285).

CONCLUSION

Despite having higher-than-expected PA, the low stepping loads observed in this cohort, along with half of the participants having low BMD measures, underscores the need for PA intensity to be considered in the management of postmenopausal bone health.

Evaluation of Step-Counting Interventions Differing on Intensity Messages

BACKGROUND

Step-counting interventions with discrepant intensity emphases may elicit different effects.

METHODS

A total of 120 sedentary/low-active, postmenopausal women were randomly assigned to one of the following 3 groups: (1) 10,000 steps per day (with no emphasis on walking intensity/speed/cadence; basic intervention, 49 completers), (2) 10,000 steps per day and at least 30 minutes in moderate intensity (ie, at a cadence of at least 100 steps per minute; enhanced intervention, 47 completers), or (3) a control group (19 completers). NL-1000-determined steps and active minutes (a device-specific indicator of time at moderate+ intensity) were collected as process variables during the 12-week intervention. Outcome variables included systolic and diastolic blood pressure, anthropometric measurements, fasting blood glucose and insulin, flow-mediated dilation, gait speed, and ActiGraph GT3X+-determined physical activity and sedentary behavior.

RESULTS

The "basic group" increased 5173 to 9602 steps per day and 9.2 to 30.2 active minutes per day. The "enhanced group" similarly increased 5061 to 10,508 steps per day and 8.7 to 38.8 active minutes per day. The only significant change over time for clinical variables was body mass index.

CONCLUSIONS

Interventions that use simple step-counters can achieve elevated volume and intensity of daily physical activity, regardless of emphasis on intensity. Despite this, few clinical outcomes were apparent in this sample of postmenopausal women with generally normal or controlled hypertension.

Brief Report: Physical Activity, Body Mass Index and Arterial Stiffness in Children with Autism Spectrum Disorder: Preliminary Findings

We examined the association between physical activity (PA), body mass index (BMI) and novel measures of subclinical cardiovascular disease (CVD) in 15 children with autism spectrum disorder (ASD) (mean age 7 ± 2 years, 2 girls). PA was objectively assessed using accelerometry as time spent in moderate-vigorous physical activity (MVPA). Arterial stiffness was measured via aortic pulse wave velocity (PWV) and taken as a marker of subclinical CVD risk. MVPA was inversely associated with aortic PWV (r = - 0.46, p < 0.05). BMI percentile was positively associated with aortic PWV (r = 0.61, p < 0.05). Overall findings suggest that reduced PA and higher body mass in children with ASD are associated with increased arterial stiffness which may have a detrimental impact on overall cardiovascular health.

Design and methodology of the impact of HemoDiaFIlTration on physical activity and self-reported outcomes: a randomized controlled trial (HDFIT trial) in Brazil

BACKGROUND

End stage renal disease (ESRD) patients require a renal replacement therapy (RRT) to filter accumulated toxins and remove excess water, which are associated with impaired physical function. Hemodialysis (HD) removes middle-molecular weight (MMW) toxins less efficiently compared to hemodiafiltration (HDF); we hypothesized HDF may improve physical function. We detailed the design and methodology of the HDFIT protocol that is testing whether changing from HD to HDF effects physical activity levels and various outcomes.

METHODS

HDFIT is a prospective, multi-center, unblinded, randomized control trial (RCT) investigating the impact of dialysis modality (HDF verses HD) on objectively measured physical activity levels, self-reported quality of life, and clinical/non-clinical outcomes. Clinically stable patients with HD vintage of 3 to 24 months without any severe limitation ambulation were recruited from sites throughout southern Brazil. Eligible patients were randomized in a 1:1 ratio to either: 1) be treated with high volume online HDF for 6 months, or 2) continue being treated with high-flux HD. This study includes run-in and randomization visits (baseline), 3- and 6-month study visits during the interventional period, and a 12-month observational follow up. The primary outcome is the difference in the change in steps per 24 h on dialysis days from baseline to the 6-month follow up in patients treated with HDF versus HD. Physical activity is being measured over one week at study visits with the ActiGraph ( www.actigraphcorp.com ). For assessment of peridialytic differences during the dialysis recovery period, we will analyze granular physical activity levels based on the initiation time of HD on dialysis days, or concurrent times on non-dialysis days and the long interdialytic day.

DISCUSSION

In this manuscript, we provide detailed information about the HDFIT study design and methodology. This trial will provide novel insights into peridialytic profiles of physical activity and various self-reported, clinical and laboratory outcomes in ESRD patients treated by high volume online HDF versus high-flux HD. Ultimately, this investigation will elucidate whether HDF is associated with patients having better vitality and quality of life, and less negative outcomes as compared to HD.

TRIAL REGISTRATION

Registered on ClinicalTrials.gov on 20 April 2016 ( NCT02787161 ).

Step-counting accuracy of activity monitors in persons with Down syndrome

BACKGROUND

Accelerometers and pedometers have been used to monitor the number of steps. However, the evidence on the step-counting accuracy of these devices - especially accelerometers - is limited in persons with Down syndrome (DS). This study therefore examined the accuracy of accelerometers placed on the hip or wrist and of a pedometer with a uni-axial accelerometer mechanism in measuring steps in persons with DS and whether device error is associated with walking speed, height, weight, body mass index, waist circumference, leg length, age or sex.

METHOD

Seventeen persons with DS (eight women and nine men; age 33 ± 15 years) walked over-ground for 6 min at their preferred speed. The steps were measured with a hip-worn and a wrist-worn ActiGraph accelerometer using the manufacturer's default (DF) and low-frequency extension (LFE) filters, and with the NL-1000 New Lifestyles pedometer on the hip. Steps were also measured with hand tally which served as the criterion.

RESULTS

Absolute percent error was considerable and differed statistically between devices (P = 0.001); however, error improved for accelerometers when LFE was applied (Hip-DF: 31.6 ± 18.8%; Hip-LFE: 9.7 ± 12.8%; Wrist-DF: 32.7 ± 14.2%; Wrist-LFE: 13.6 ± 10.2%; Pedometer: 23.2 ± 22.8%). Bland-Altman plots indicated underestimation of steps for accelerometers and the pedometer. Application of LFE, however, improved the prediction of the accelerometers. The number of steps measured by the hip accelerometer with LFE and by the pedometer did not differ statistically from actual steps. Steps by the remaining methods were significantly lower than hand tally (P ≤ 0.001). Correlations between percent error for each device and walking speed, anthropometry, age or sex ranged between -0.28 and +0.48, and were non-significant, except for age.

CONCLUSIONS

The results demonstrated that the pedometer and ActiGraph accelerometers have considerable error in measuring steps of persons with DS. Application of LFE, however, significantly improved the step-counting performance of the Actigraph accelerometers.

Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations

BACKGROUND

Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.

OBJECTIVES

The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.

METHODS

Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.

RESULTS

The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.

CONCLUSION

This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.

PROSPERO REGISTRATION NUMBER

CRD42016039991.

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Effect of ActiGraph's low frequency extension for estimating steps and physical activity intensity

This study examined the effects of the ActiGraph’s (AG) low-frequency extension (LFE) filter on steps and physical activity classification in the free-living environment. Thirty-four African-American women (age, 24.5±5.2 years; BMI, 24.9±4.5 kg/m²) had daily activity measured simultaneously with an AG-GT3X⁺ accelerometer and a New Lifestyles NL-800 pedometer for seven days. Steps per day (steps/day) and time (minutes/day) spent in sedentary, light, and moderate-to-vigorous physical activity (MVPA) were examined with and without the LFE filter (AG-LFE and AG-N, respectively). The AG-LFE recorded more total steps (13,723±4,983 steps/day) compared to AG-N and NL-800 (6,172±2,838 and 5,817±3,037 steps/day, respectively; p<0.001). Compared to the AG-N, the AG-LFE estimated less time in sedentary behaviors (518.7±92.1 vs. 504.2±105.4 min/day, respectively; p<0.001), and more time in light (247.7±70.4 vs. 279.1±74.7 min/day, respectively; p<0.001) and MVPA (18.9±16.9 vs. 21.5±18.2 min/day, respectively; p<0.001), respectively. These data suggest that steps and physical activity classifications will be affected when using the ActiGraph with and without the LFE filter. Future research should investigate the accuracy of these measures using the LFE filter.

Validity and reliability of accelerometry in identification of lying, sitting, standing or purposeful activity in adult hospital inpatients recovering from acute or critical illness: a systematic review

Objective:

To investigate the validity and reliability of accelerometers to detect lying, sitting and standing postures or purposeful activity in hospitalized adults recovering from acute or critical illness.

Data sources:

CINAHL, MEDLINE, EMBASE, AMED, Cochrane Library, PEDro, PsycINFO and SPORTDiscuss were searched from inception to June 2017. Professional networks and reference lists of relevant articles were also searched. The main selection criteria were hospitalized adults with acute or critical illness and studies investigating the validity or reliability of accelerometers to identify body position or purposeful activity.

Review methods:

Two authors individually assessed study eligibility and independently undertook methodological quality assessment and data extraction from selected articles. A narrative synthesis of the data was undertaken.

Results:

Fifteen studies, collectively enrolling 385 hospitalized participants, were identified. Populations included stroke, the elderly, acute exacerbation of chronic respiratory disease, abdominal surgery and those recovering from critical illness. Correlations of r = 0.36 to 0.98 and levels of agreement of κ = 0.28 to 0.98 were reported for identification of lying, sitting or standing postures. Correlations of r = 0.4 to 0.8 with general activity were found, with r = 0.94 and 0.96 reported for step count. The reliability of accelerometry measurement was investigated in one study evaluating step count quantification (intraclass correlation coefficient (ICC) = 0.99, 95% confidence interval (CI) = 0.99–1.00).

Conclusion:

The validity of accelerometers to determine lying, sitting and standing postures or quantify purposeful activity within hospitalized acute or critically ill populations is variable. The reliability of accelerometry measurement within this setting remains largely unexplored.

I'd Do Anything for Research, But I Won't Do That: Interest in Pharmacological Interventions in Older Adults Enrolled in a Longitudinal Aging Study

Alzheimer’s disease (AD) ranks as the 6^th leading cause of death in the United States, yet unlike other diseases in this category, there are no disease-modifying medications for AD. Currently there is significant interest in exploring the benefits of pharmacological treatment before the onset of dementia (e.g., in those with mild cognitive impairment); however, recruitment for such studies is challenging. The current study examined interest in pharmacological intervention trials relative to other types of clinical interventions. A total of 67 non-demented older adults enrolled in a longitudinal cognitive aging study completed a questionnaire assessing interest in participating in a variety of hypothetical research study designs. Consistent with past research, results showed that the opportunities for participants to advance science, receive feedback about their current health, and help themselves or others, were associated with increased interest in clinical trial participation. Some factors were not associated with change in interest (e.g., a doctor not recommending participation) while others were associated with decreased interest (e.g., having to come in for multiple visits each week). Relative to other types of interventions, pharmacological intervention trials were associated with the least interest in participation, despite pharmacological interventions being rated as more likely to result in AD treatment. Decreased interest was not predicted by subjective memory concerns, number of current medications, cardiovascular risk, or beliefs about the likely success of pharmacological treatments. These results highlight the challenges faced by researchers investigating pharmacological treatments in non-demented older individuals, and suggest future research could contribute to more effective ways of recruiting participants in AD-related clinical trials.

Step detection using multi- versus single tri-axial accelerometer-based systems

Multiple sensors are often considered necessary for increased step count accuracy. However, subject adherence to device-wear increases using a minimal number of activity monitors (AMs). The study aims were to determine and compare the validity of using multiple AMs versus a single AM to detect steps by comparison to video using a modification of an algorithm previously developed for a four-accelerometer AM system capable, unlike other algorithms, of accurate step detection for gait velocities as low as 0.1 m s(-1). Twelve healthy adults wore ankle, thigh and waist AMs while performing walking/jogging trials at gait velocities from 0.1-4.8 m s(-1) and a simulated free-living dynamic activities protocol. Nineteen older adults wore ankle and waist AMs while walking at velocities from 0.5-2.0 m s(-1). As little as one AM (thigh or waist) accurately detected steps for velocities  >0.5 m s(-1). A single ankle AM accurately detected steps for velocities  ⩾0.1 m s(-1). Only the thigh AM could not accurately detect steps during the dynamic activities. Only the thigh-ankle combination or single waist AM could accurately distinguish between walking and jogging steps. These laboratory-based results suggest that the presented algorithm can accurately detect steps in a free-living environment using only one ankle or waist AM.

Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults

Daily ambulatory activity is associated with health and functional status in older adults; however, assessment requires multiple days of activity monitoring. The objective of this study was to determine the relative capabilities of self-selected walking speed (SSWS), maximal walking speed (MWS), and walking speed reserve (WSR) to provide insight into daily ambulatory activity (steps per day) in community-dwelling older adults. Sixty-seven older adults completed testing and activity monitoring (age 80.39 [6.73] years). SSWS (R2 = .51), MWS (R2 = .35), and WSR calculated as a ratio (R2 = .06) were significant predictors of daily ambulatory activity in unadjusted linear regression. Cutpoints for participants achieving < 8,000 steps/day were identified for SSWS (≤ 0.97 m/s, 44.2% sensitivity, 95.7% specificity, 10.28 +LR, 0.58 -LR) and MWS (≤ 1.39 m/s, 60.5% sensitivity, 78.3% specificity, 2.79 +LR, 0.50 -LR). SSWS may be a feasible proxy for assessing and monitoring daily ambulatory activity in older adults.

Repeat physical activity measurement by accelerometry among colorectal cancer patients--feasibility and minimal number of days of monitoring

Background

Physical activity plays an important role in colorectal cancer and accelerometry is more frequently used to measure physical activity. The aim of this study was to evaluate feasibility of physical activity measurement by accelerometry in colorectal cancer patients under free-living conditions at 6, 12 and 24 months after surgery, to evaluate the appropriate wear time and to compare results to pedometry.

Methods

Colorectal cancer patients (stage 0/I–IV) from the ColoCare study were asked to optionally wear an accelerometer and a pedometer for ten consecutive days 6, 12 and 24 months post-surgery. Participants completed a feedback questionnaire about the accelerometer measurement. The course of moderate-to-vigorous physical activity over the 10 days was investigated. Additionally, daily step counts from accelerometers and pedometers were compared.

Results

In total, there were 317 individual time points, at which 198 participants were asked to wear an accelerometer. Fifty-nine% initially agreed to participate and of these, 83% (n = 156) completed the assessment with at least 4 days of data. Twenty-one% more consents were obtained when participants were asked on a face-to-face basis compared to recruitment by telephone (P = 0.0002). There were no significant differences in time spent in moderate-to-vigorous physical activity between different wear-time lengths of accelerometry. Both Spearman and intraclass correlation coefficients showed strong correlations (0.92–0.99 and 0.84–0.99, respectively) of moderate-to-vigorous physical activity across 3, 4, 7 and 10 days measurement. Step counts measured by accelerometry and pedometry were strongly correlated (ρ = 0.91, P < 0.0001).

Conclusion

This study suggest that accelerometry is a feasible method to assess physical activity in free-living colorectal cancer patients and that three valid days of physical activity measurement are sufficient for an accurate assessment.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1168-y) contains supplementary material, which is available to authorized users.

Pattern changes in step count accumulation and peak cadence due to a physical activity intervention

OBJECTIVES

The purpose was to determine if a 12-week weight loss intervention with a physical activity (PA) component would lead to changes in steps/day, step count accumulation patterns, and peak cadence.

DESIGN

Randomized clinical trial.

METHODS

Overall, 121 overweight/obese White and African-American adults (ages 35-64yrs) were randomized to a diet education plus PA education and behavior change intervention group (DE+PA) or diet education and behavior change group (DE). The DE+PA intervention was designed to increase steps/day, and steps at moderate-to-vigorous intensity. The Actigraph GT3X+ accelerometer was used to measure steps accumulated in different cadence bands (1-19, 20-39, 40-59, 60-79, 80-99, 100-119, 120+ steps/min), and peak 1-min, 30-min and 60-min cadence. Pre- to post-intervention changes in steps/day, step count within each cadence band, and peak cadences were compared within groups using paired sample t-test and between groups after adjustment for baseline values of the same variable using ANCOVA.

RESULTS

Ninety participants had valid data (44 in the DE+PA group). Change in steps/day was not significantly different between the groups. However, participants in the DE+PA group accumulated significantly more steps at post-intervention in the 80-99, 100-119, and 120+ cadence bands, all p<0.02. The DE+PA group increased step counts accumulated within the 100-119 (463±1092 vs 56±546 step counts; p=0.01) and 120+ (390±999 vs 34±321 step counts; p=0.03) cadence bands, as well as peak 60-min cadence when compared to the DE group.

CONCLUSIONS

Non-significant changes in steps/day following a PA intervention may mask changes in steps accumulated at moderate-to-vigorous intensity cadences.

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer, Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings

Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7-16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.

Feasibility, reliability, and validity of a smartphone based application for the assessment of cognitive function in the elderly

While considerable knowledge has been gained through the use of established cognitive and motor assessment tools, there is a considerable interest and need for the development of a battery of reliable and validated assessment tools that provide real-time and remote analysis of cognitive and motor function in the elderly. Smartphones appear to be an obvious choice for the development of these “next-generation” assessment tools for geriatric research, although to date no studies have reported on the use of smartphone-based applications for the study of cognition in the elderly. The primary focus of the current study was to assess the feasibility, reliability, and validity of a smartphone-based application for the assessment of cognitive function in the elderly. A total of 57 non-demented elderly individuals were administered a newly developed smartphone application-based Color-Shape Test (CST) in order to determine its utility in measuring cognitive processing speed in the elderly. Validity of this novel cognitive task was assessed by correlating performance on the CST with scores on widely accepted assessments of cognitive function. Scores on the CST were significantly correlated with global cognition (Mini-Mental State Exam: r = 0.515, p<0.0001) and multiple measures of processing speed and attention (Digit Span: r = 0.427, p<0.0001; Trail Making Test: r = −0.651, p<0.00001; Digit Symbol Test: r = 0.508, p<0.0001). The CST was not correlated with naming and verbal fluency tasks (Boston Naming Test, Vegetable/Animal Naming) or memory tasks (Logical Memory Test). Test re-test reliability was observed to be significant (r = 0.726; p = 0.02). Together, these data are the first to demonstrate the feasibility, reliability, and validity of using a smartphone-based application for the purpose of assessing cognitive function in the elderly. The importance of these findings for the establishment of smartphone-based assessment batteries of cognitive and motor function in the elderly is discussed.