A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.

Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.

Physical activity together for couples living with mild cognitive impairment (PAT-MCI): A feasibility study.

Mild cognitive impairment is a prodromal phase of Alzheimer's disease and related dementias. Cognitive and/or neuropsychiatric symptoms that could worsen over time cause challenges for patients and romantic partners, who often assume the role of informal caregivers. Although physical activity is beneficial, older adults with mild cognitive impairment and their romantic care partners are generally physically inactive. Our 16-week study was performed to see whether physical activity together is feasible to increase physical activity among four dyads (individuals with mild cognitive impairment and their spouses). Our dyadic intervention was feasible given more than 70 % of participants self-reported adherence to physical activity based on the guidelines for adults in the United States. In exit interviews, togetherness was highlighted as one of the biggest strengths of this study. Future studies with more representative samples are needed, as well as adopting a more tailored approach that accounts for individuals' levels of physical fitness.

Community Walks: a cluster randomized controlled trial of a multilevel physical activity intervention for low income public housing residents.

BACKGROUND: Physical activity behavioral interventions to change individual-level drivers of activity, like motivation, attitudes, and self-efficacy, are often not sustained beyond the intervention period. Interventions at both environmental and individual levels might facilitate durable change. This community-based study seeks to test a multilevel, multicomponent intervention to increase moderate intensity physical activity among people with low incomes living in U.S. public housing developments, over a 2 year period. METHODS: The study design is a prospective, cluster randomized controlled trial, with housing developments (n=12) as the units of randomization. In a four-group, factorial trial, we will compare an environmental intervention (E) alone (3 developments), an individual intervention (I) alone (3 developments), an environmental plus individual (E+I) intervention (3 developments), against an assessment only control group (3 developments). The environmental only intervention consists of community health workers leading walking groups and indoor activities, a walking advocacy program for residents, and provision of walking maps/signage. The individual only intervention consists of a 12-week automated telephone program to increase physical activity motivation and self-efficacy. All residents are invited to participate in the intervention activities being delivered at their development. The primary outcome is change in moderate intensity physical activity measured via an accelerometer-based device among an evaluation cohort (n=50 individuals at each of the 12 developments) from baseline to 24-month follow up. Mediation (e.g., neighborhood walkability, motivation) and moderation (e.g., neighborhood stress) of our interventions will be assessed. Lastly, we will interview key informants to assess factors from the Consolidated Framework for Implementation Research domains to inform future implementation. DISCUSSION: We hypothesize participants living in developments in any of the three intervention groups (E only, I only, and E+I combined) will increase minutes of moderate intensity physical activity more than participants in control group developments. We expect delivery of an intervention package targeting environmental and social factors to become active, combined with the individual level intervention, will improve overall physical activity levels to recommended guidelines at the development level. If effective, this trial has the potential for implementation through other federal and state housing authorities. TRIAL REGISTRATION: Clinical Trails.gov PRS Protocol Registration and Results System, NCT05147298 . Registered 28 November 2021.

Gait and/or balance disturbances associated with Alzheimer's dementia among older adults with amnestic mild cognitive impairment: A longitudinal observational study.

AIMS: To explore whether gait and/or balance disturbances are associated with the onset of Alzheimer's dementia (AD) among older adults with amnestic mild cognitive impairment (MCI). DESIGN: This study employed a longitudinal retrospective cohort design. METHODS: We obtained data from the National Alzheimer's Coordinating Center's Uniform Data Set collected from 35 National Institute on Aging Alzheimer's Disease Research Centers between September 2005 and December 2021. The mean age of participants (n = 2692) was 74.5 years with women making up 47.2% of the sample. Risk of incident AD according to baseline gait and/or balance disturbances as measured using the Postural Instability and Gait Disturbance Score, a subscale of the Unified Parkinson's Disease Rating Scale Motor Score, was examined by the Cox proportional hazards regression models adjusting for baseline demographics, medical conditions and study sites. The mean follow-up duration was 4.0 years. RESULTS: Among all the participants, the presence or the severity of gait and/or balance disturbances was associated with an increased risk of AD. The presence or the severity of gait and/or balance disturbances was associated with a higher risk of Alzheimer's dementia among the subgroups of female and male participants. CONCLUSION: Gait and/or balance disturbances may increase the risk of developing AD, regardless of sex. IMPACT: Gait and/or balance disturbances among community-dwelling older adults with amnestic MCI may need to be frequently assessed by nurses to identify potential risk factors for cognitive decline. NO PATIENT OR PUBLIC CONTRIBUTION: Given the secondary analysis, patients, service users, caregivers or members of the public were not directly involved in this study.

C-reactive protein in adult Samoans: Population variation and physiological correlates.

OBJECTIVES: C-reactive protein (CRP) has been associated with adiposity and cardiometabolic disease risk in many populations but remains remarkably understudied in Pacific Islander populations. Here, we provide the first examination of correlates of CRP in adult Samoans (n = 108, ages 35-55 years) to test the hypotheses that CRP exhibits sex-dependent associations with measures of BMI, adiposity, and cardiometabolic disease risks. METHODS: We analyzed associations between measures of adiposity (total fat mass, visceral fat mass, percent total body fat), body mass index (BMI), cardiometabolic risks, behaviors, demographics, and CRP. Unadjusted analyses of CRP were undertaken using Pearson's pairwise, and Spearman's rank correlations; one-way analysis of variance and Kruskal-Wallis tests assessed variables by CRP quartiles. Adjusted analyses of CRP correlates were examined using generalized linear regression. RESULTS: Serum CRP ranged from 0.08 to 13.3 mg/L (median 1.4 mg/L) and varied significantly by sex t (108) = -2.47, p = .015. CRP was weakly to moderately associated with measures of adiposity and BMI (r and ρ ranged between 0.25 and 0.50, p < .05) and some cardiometabolic markers (including HbA1c, fasting insulin, and insulin resistance). CRP was significantly associated with percent body fat in women and men, adjusting for other variables. CONCLUSIONS: These data are among the first to demonstrate CRP correlates in a sample of adult Samoans. CRP differed by sex and was associated with BMI, adiposity, and some cardiometabolic risk markers. These data align with findings in other populations.

Determining day-to-day human variation in indirect calorimetry using Bayesian decision theory.

NEW FINDINGS: What is the central question of this study? We sought to understand the day-to-day variability of human indirect calorimetry during rest and exercise. Previous work has been unable to separate human day-to-day variability from measurement error and within-trial human variability. We developed models accounting for different levels of human- and machine-level variance and compared the probability density functions using total variation distance. What is the main finding and its importance? After accounting for multiple levels of variance, the average human day-to-day variability of minute ventilation, CO2 output and O2 uptake is 4.0, 1.8 and 2.0%, respectively. This is a new method to understand human variability and directly enhances our understanding of human variance during indirect calorimetry. ABSTRACT: One of the challenges of precision medicine is understanding when serial measurements taken across days are quantifiably different from each other. Previous work examining gas exchange measured by indirect calorimetry has been unable to separate differential measurement error, within-trial human variance and day-to-day human variance effectively in order to ascertain how variable humans are across testing sessions. We used previously published reliability data to construct models of indirect calorimetry variance and compare these models with methods arising from Bayesian decision theory. These models are conditional on the data upon which they are derived and assume that errors conform to a truncated normal distribution. A serial analysis of modelled probability density functions demonstrated that the average human day-to-day variance in minute ventilation ( V ̇ E ), carbon dioxide output ( V ̇ C O 2 ) and oxygen uptake ( V ̇ O 2 ) was 4.0, 1.8 and 2.0%, respectively. However, the average day-to-day variability masked a wide range of non-linear variance across flow rates, particularly for V ̇ E . This is the first report isolating day-to-day human variability in indirect calorimetry gas exchange from other sources of variability. This method can be extended to other physiological tools, and an extension of this work facilitates a statistical tool to examine within-trial V ̇ O 2 differences, available in a graphical user interface.

Feasibility and acceptability of "healthy directions" a lifestyle intervention for adults with lung cancer.

OBJECTIVE: The aims of this feasibility study of an adapted lifestyle intervention for adults with lung cancer were to (1) determine rates of enrollment, attrition, and completion of 5 nurse-patient contacts; (2) examine demographic characteristics of those more likely to enroll into the program; (3) determine acceptability of the intervention; and (4) identify patient preferences for the format of supplemental educational intervention materials. METHODS: This study used a single-arm, pretest and posttest design. Feasibility was defined as ≥20% enrollment and a completion rate of 70% for 5 nurse-patient contact sessions. Acceptability was defined as 80% of patients recommending the program to others. Data was collected through electronic data bases and phone interviews. Descriptive statistics, Fisher's exact test and Wilcoxon rank sum test were used for analyses. RESULTS: Of 147 eligible patients, 42 (28.6%) enrolled and of these, 32 (76.2%) started the intervention and 27 (N = 27/32; 84.4%; 95% CI, 67.2%-94.7%) completed the intervention. Patients who were younger were more likely to enroll in the study (P = .04) whereas there were no significant differences by gender (P = .35). Twenty-three of the 24 (95.8%) participants' contacted posttest recommended the intervention for others. Nearly equal numbers of participants chose the website (n = 16, 50%) vs print (n = 14, 44%). CONCLUSION: The intervention was feasible and acceptable in patients with lung cancer. Recruitment rates were higher and completion rates were similar as compared to previous home-based lifestyle interventions for patients with other types of cancer. Strategies to enhance recruitment of older adults are important for future research.

Energy Cost Expression for a Youth Compendium of Physical Activities: Rationale for Using Age Groups.

PURPOSE: This study compared the accuracy of physical activity energy expenditure (PAEE) prediction using 2 methods of accounting for age dependency versus 1 standard (single) value across all ages. METHODS: PAEE estimates were derived by pooling data from 5 studies. Participants, 6-18 years (n = 929), engaged in 14 activities while in a room calorimeter or wearing a portable metabolic analyzer. Linear regression was used to estimate the measurement error in PAEE (expressed as youth metabolic equivalent) associated with using age groups (6-9, 10-12, 13-15, and 16-18 y) and age-in-years [each year of chronological age (eg, 12 = 12.0-12.99 y)] versus the standard (a single value across all ages). RESULTS: Age groups and age-in-years showed similar error, and both showed less error than the standard method for cycling, skilled, and moderate- to vigorous-intensity activities. For sedentary and light activities, the standard had similar error to the other 2 methods. Mean values for root mean square error ranged from 0.2 to 1.7 youth metabolic equivalent across all activities. Error reduction ranged from -0.2% to 21.7% for age groups and -0.23% to 18.2% for age-in-years compared with the standard. CONCLUSIONS: Accounting for age showed lower errors than a standard (single) value; using an age-dependent model in the Youth Compendium is recommended.

Estimating physical activity in youth using an ankle accelerometer.

This study developed and validated a vector magnitude (VM) two-regression model (2RM) for use with an ankle-worn ActiGraph accelerometer. For model development, 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 2-7 structured activities. For cross-validation, 42 youth (age, 12.6 ± 0.8 yr) completed approximately 2 hr of unstructured physical activity (PA). PA data were collected using an ActiGraph accelerometer, (non-dominant ankle) and the VM was expressed as counts/5-s. Measured energy expenditure (Cosmed K4b2) was converted to youth METs (METy; activity VO2 divided by resting VO2). A coefficient of variation (CV) was calculated for each activity to distinguish continuous walking/running from intermittent activity. The ankle VM sedentary behavior threshold was ≤10 counts/5-s, and a CV≤15 counts/5-s was used to identify walking/running. The ankle VM2RM was within 0.42 METy of measured METy during the unstructured PA (P > 0.05). The ankle VM2RM was within 5.7 min of measured time spent in sedentary, LPA, MPA, and VPA (P > 0.05). Compared to the K4b2, the ankle VM2RM provided similar estimates to measured values during unstructured play and provides a feasible wear location for future studies.

Effects of Knee Alignments and Toe Clip on Frontal Plane Knee Biomechanics in Cycling.

Effects of knee alignment on the internal knee abduction moment (KAM) in walking have been widely studied. The KAM is closely associated with the development of medial knee osteoarthritis. Despite the importance of knee alignment, no studies have explored its effects on knee frontal plane biomechanics during stationary cycling. The purpose of this study was to examine the effects of knee alignment and use of a toe clip on the knee frontal plane biomechanics during stationary cycling. A total of 32 participants (11 varus, 11 neutral, and 10 valgus alignment) performed five trials in each of six cycling conditions: pedaling at 80 rpm and 0.5 kg (40 Watts), 1.0 kg (78 Watts), and 1.5 kg (117 Watts) with and without a toe clip. A motion analysis system and a customized instrumented pedal were used to collect 3D kinematic and kinetic data. A 3 × 2 × 3 (group × toe clip × workload) mixed design ANOVA was used for statistical analysis (p < 0.05). There were two different knee frontal plane loading patterns, internal abduction and adduction moment, which were affected by knee alignment type. The knee adduction angle was 12.2° greater in the varus group compared to the valgus group (p = 0.001), yet no difference was found for KAM among groups. Wearing a toe clip increased the knee adduction angle by 0.95º (p = 0.005). The findings of this study indicate that stationary cycling may be a safe exercise prescription for people with knee malalignments. In addition, using a toe clip may not have any negative effects on knee joints during stationary cycling.

Effects of an afterschool community center physical activity program on fitness and body composition in obese youth.

Physical activity (PA) promotes health in obese youth and is an important adjunct to medical weight management. Access to structured fitness programmes for obese, low-income youth is limited and potential benefits of such programmes are poorly understood. We describe an urban afterschool fitness programme for obese youth and participants' changes in fitness and body composition. A case series of 30 youth (age: 11.5 ± 2.5 years) with BMI ≥95th percentile and physician referral received a 24-wk programme scholarship. The programme, offered 4 times a week for 90-min.session, included aerobic, strength, and self-organised PA. Primary outcomes, measured at baseline (BL) time 1 (4-8 wk) and time 2 (12-16 wk) were BMI, per cent body fat (%BF), fat-free mass (FFM), heart rate during a treadmill test, and muscular strength (one repetition maximum (1RM)) and endurance (reps at 70% of 1RM) on the leg press (LP) and chest press (CP). Average participation was 1.5 ± 0.6 visits per week for 18.7 ± 6.5 weeks. Between BL and time 2, LP and CP 1RM and endurance significantly improved (P < 0.05). Additionally, there was a significant interaction for %BF with boys losing 5.2% (P > 0.05) while girls lost 0% (>0.05). Obese youth attending an urban fitness programme for at least three months improved strength and body composition, but average attendance was below planned levels.

Bipart: Learning Block Structure for Activity Detection.

Physical activity consists complex behavior, typically structured in bouts which can consist of one continuous movement (e.g. exercise) or many sporadic movements (e.g. household chores). Each bout can be represented as a block of feature vectors corresponding to the same activity type. This paper introduces a general distance metric technique to use this block representation to first predict activity type, and then uses the predicted activity to estimate energy expenditure within a novel framework. This distance metric, dubbed Bipart, learns block-level information from both training and test sets, combining both to form a projection space which materializes block-level constraints. Thus, Bipart provides a space which can improve the bout classification performance of all classifiers. We also propose an energy expenditure estimation framework which leverages activity classification in order to improve estimates. Comprehensive experiments on waist-mounted accelerometer data, comparing Bipart against many similar methods as well as other classifiers, demonstrate the superior activity recognition of Bipart, especially in low-information experimental settings.

Accelerometer-Based Estimates of Physical Activity and Sedentary Time Among Samoan Adults.

BACKGROUND: The prevalence of obesity-related cardiometabolic disease in Samoa is among the highest globally. While physical activity is a modifiable risk factor for obesity-related disease, little is known about physical activity levels among adult Samoans. Using wrist-worn accelerometer-based devices, this study aimed to characterize physical activity among Samoan adults. METHODS: Samoan adults (n = 385; 55% female, mean [SD] age 52 [10] y) wore Actigraph GT3X+ devices for 7 to 10 days. General linear models were used to examine mean daily minutes of sedentary time, light physical activity, and moderate to vigorous physical activity by various participant characteristics. RESULTS: Time spent in moderate to vigorous physical activity did not differ statistically between men (88 [5] min; 95% confidence interval [CI], 80-97) and women (78 [4] min; 95% CI, 70-86; P = .08). Women, however, spent more time than men in light physical activity: 380 (7) minutes (95% CI, 367-393) versus 344 (7) minutes (95% CI, 329-358; P < .001). While there were no differences in physical activity by census region, education, or occupation among women, men in urban areas spent significantly less time in moderate to vigorous physical activity than those in peri-urban and rural areas (P = .015). Women with class II/III obesity spent more time in sedentary activities than those with healthy weight or overweight/class I obesity (P = .048). CONCLUSIONS: This study characterizes physical activity among Samoan adults and highlights variation by sex, urbanicity, and weight status. In providing initial device-measured estimates of physical activity in Samoa, this analysis establishes a baseline from which the success of future attempts to intervene on physical activity may be assessed.

Ecological monitoring of physical activity, emotions and daily life activities in schizophrenia: the DiAPAson study.

BACKGROUND: Schizophrenia spectrum disorders (SSD) compromise psychosocial functioning, including daily time use, emotional expression and physical activity (PA). OBJECTIVE: We performed a cohort study aimed at investigating: (1) the differences in PA, daily activities and emotions between patients with SSD and healthy controls (HC); (2) the strength of the association between these variables and clinical features among patients with SSD. METHODS: Ninety-nine patients with SSD (53 residential patients, 46 outpatients) and 111 matched HC were assessed for several clinical variables, and levels of functioning by means of standardised clinical measures. Self-reported daily activities and emotions were assessed with a smartphone application for ecological momentary assessment (EMA), and PA levels were assessed with a wearable accelerometer for 7 consecutive days.FindingsPatients with SSD, especially those living in residential facilities, spent more time being sedentary, and self-reported more sedentary and self-care activities, experiencing higher levels of negative emotions compared with HC. Moreover, higher functioning levels among patients were associated with more time spent in moderate-to-vigorous activity. CONCLUSIONS: Sedentary behaviour and negative emotions are particularly critical among patients with SSD and are associated with more impaired clinical outcomes. CLINICAL IMPLICATIONS: Mobile-EMA and wearable sensors are useful for monitoring the daily life of patients with SSD and the level of PA. This population needs to be targeted with specific rehabilitative programmes aimed at improving their commitment to structured daily activities.

Core components of a rehabilitation program in pediatric cardiac disease.

There is increasing effort in both the inpatient and outpatient setting to improve care, function, and quality of life for children with congenital heart disease, and to decrease complications. As the mortality rates of surgical procedures for congenital heart disease decrease, improvement in perioperative morbidity and quality of life have become key metrics of quality of care. Quality of life and function in patients with congenital heart disease can be affected by multiple factors: the underlying heart condition, cardiac surgery, complications, and medical treatment. Some of the functional areas affected are motor abilities, exercise capacity, feeding, speech, cognition, and psychosocial adjustment. Rehabilitation interventions aim to enhance and restore functional ability and quality of life for those with physical impairments or disabilities. Interventions such as exercise training have been extensively evaluated in adults with acquired heart disease, and rehabilitation interventions for pediatric patients with congenital heart disease have similar potential to improve perioperative morbidity and quality of life. However, literature regarding the pediatric population is limited. We have gathered a multidisciplinary team of experts from major institutions to create evidence- and practice-based guidelines for pediatric cardiac rehabilitation programs in both inpatient and outpatient settings. To improve the quality of life of pediatric patients with congenital heart disease, we propose the use of individualized multidisciplinary rehabilitation programs that include: medical management; neuropsychology; nursing care; rehabilitation equipment; physical, occupational, speech, and feeding therapies; and exercise training.

Knee biomechanics of patients with total knee replacement during downhill walking on different slopes.

PURPOSE: The purpose of this study was to compare knee biomechanics of the replaced limb to the non-replaced limb of total knee replacement (TKR) patients and healthy controls during walking on level ground and on decline surfaces of 5°, 10°, and 15°. METHODS: Twenty-five TKR patients and 10 healthy controls performed 5 walking trials on different decline slopes on a force platform and an instrumented ramp system. Two analyses of variance, 2 × 2 (limb × group) and 2 × 4 (limb × decline slope), were used to examine selected biomechanics variables. RESULTS: The replaced limb of TKR patients had lower peak loading-response and push-off knee extension moment than the non-replaced and the matched limb of healthy controls. No differences were found in loading-response and push-off knee internal abduction moments among replaced, non-replaced, and matched limb of healthy controls. The knee flexion range of motion, peak loading-response vertical ground reaction force, and peak knee extension moment increased across all slope comparisons between 0° and 15° in both the replaced and non-replaced limb of TKR patients. CONCLUSION: Downhill walking may not be appropriate to include in early stage rehabilitation exercise protocols for TKR patients.

Association of Bone Mineral Density with Lean Mass, Fat Mass, and Physical Activity in Young Overweight and Obese Women.

To examine the associations between bone mineral density (BMD), body composition and habitual physical activity in women who are overweight/obese. We measured whole-body bone, and body composition (lean mass, fat mass, and total fat percent) via dual-energy x-ray absorptiometry (model General Electric Lunar whole-body scanner) in a diverse group of women (N=48, age 26.6+/-4.7 years, 63% Black) living in an urban setting. The relations between BMD with total fat percent [%]), lean mass (kg), fat mass (kg), and physical activity were examined using Pearson correlations and multiple linear regression models, adjusted for race, age, and dietary calcium. BMD was positively correlated with lean mass (r=0.43, p=0.002) and negatively correlated with total fat percentage (r=-0.31, p=0.03). Multiple linear regression models indicated BMD was positively associated with lean mass (ß: 0.007, p<0.001), and negatively associated with fat mass (kg) and total fat percentage (ß: -0.003, p=0.03; ß: -0.004, p=0.03, respectively). When stratified by race, these relations were maintained in white women but only lean mass in Black women. When stratified by age, the positive correlation between BMD and lean mass was significant in younger women (<30y) only. There were no significant relationships between BMD and any physical activity measures. Our results indicate that in young women who are overweight/obese BMD is significantly associated with body composition, both lean mass and total fat percentage, but not habitual physical activity. An emphasis on lean mass accrual may be valuable for young women, particularly Black women, to improve bone health.

Mobile health plus community health worker support for weight management among public housing residents (Path to Health): A randomized controlled trial protocol.

Interventions delivered by mobile devices (mHealth interventions) have the potential to increase access to weight management treatment in low-income populations. However, little prior research has examined effects of mHealth programming plus phone-based community health worker (CHW) support for weight management among public housing residents. For our intervention, we first interacted with a community advisory board to collect feedback on proposed intervention components. Transcripts from 5 advisory board meetings were coded and qualitative data was organized into themes. We used these data to inform our ongoing trial, in which public housing residents are randomized to one of three different groups: phone text messaging and digital self-weighing (mHealth only); mHealth intervention plus CHW behavioral phone counseling (mHealth+CHW); or assessment only to evaluate their differential effects on weight loss at 6- and 12-month follow-up. We will examine changes in diet and physical activity behaviors as well as potential mediating and moderating factors. Results of this trial could provide support for technology-based weight management interventions which may have greater potential for scalability and long-term dissemination than face-to-face programming. Clinical Trial Registration Number: NCT04852042.

Validity of estimating minute-by-minute energy expenditure of continuous walking bouts by accelerometry.

BACKGROUND: Objective measurement of physical activity remains an important challenge. For wearable monitors such as accelerometer-based physical activity monitors, more accurate methods are needed to convert activity counts into energy expenditure (EE). PURPOSE: The purpose of this study was to examine the accuracy of the refined Crouter 2-Regression Model (C2RM) for estimating EE during the transition from rest to walking and walking to rest. A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined C2RM and the 2006 C2RM. METHODS: Thirty volunteers (age, 28 ± 7.7 yrs) performed 15 minutes of seated rest, 8 minutes of over-ground walking, and 8 minutes of seated rest. An ActiGraph GT1M accelerometer and Cosmed K4b2 portable metabolic system were worn during all activities. Participants were randomly assigned to start the walking bout at 0, 20, or 40 s into the minute (according to the ActiGraph clock). Acceleration data were analyzed by two methods: 2006 Crouter model and a new refined model. RESULTS: The 2006 Crouter 2-Regression model over-predicted measured kcal kg-1 hr-1 during the first and last transitional minutes of the 20-s and 40-s walking conditions (P < 0.001). It also over-predicted the average EE for a walking bout (4.0 ± 0.5 kcal kg-1 hr-1), compared to both the measured kcal kg-1 hr-1 (3.6 ± 0.7 kcal kg-1 hr-1) and the refined Crouter model (3.5 ± 0.5 kcal kg-1 hr-1) (P < 0.05). CONCLUSION: The 2006 Crouter 2-regression model over-predicts EE at the beginning and end of walking bouts, due to high variability in accelerometer counts during the transitional minutes. The new refined model eliminates this problem and results in a more accurate prediction of EE during walking.