Smartwatch step counting: impact on daily step-count estimation accuracy
Ontology highlight
ABSTRACT:
SUBMITTER: Duking P
PROVIDER: S-EPMC11339027 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Importance:It is unclear whether the number of steps per day and the intensity of stepping are associated with lower mortality. Objective:Describe the dose-response relationship between step count and intensity and mortality. Design, Setting, and Participants:Representative sample of US adults aged at least 40 years in the National Health and Nutrition Examination Survey who wore an accelerometer for up to 7 days ( from 2003-2006). Mortality was ascertained through December 2015. Exposures:Accelerometer-measured number of steps per day and 3 step intensity measures (extended bout cadence, peak 30-minute cadence, and peak 1-minute cadence [steps/min]). Accelerometer data were based on measurements obtained during a 7-day period at baseline. Main Outcomes and Measures:The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular disease (CVD) and cancer mortality. Hazard ratios (HRs), mortality rates, and 95% CIs were estimated using cubic splines and quartile classifications adjusting for age; sex; race/ethnicity; education; diet; smoking status; body mass index; self-reported health; mobility limitations; and diagnoses of diabetes, stroke, heart disease, heart failure, cancer, chronic bronchitis, and emphysema. Results:A total of 4840 participants (mean age, 56.8 years; 2435 [54%] women; 1732 [36%] individuals with obesity) wore accelerometers for a mean of 5.7 days for a mean of 14.4 hours per day. The mean number of steps per day was 9124. There were 1165 deaths over a mean 10.1 years of follow-up, including 406 CVD and 283 cancer deaths. The unadjusted incidence density for all-cause mortality was 76.7 per 1000 person-years (419 deaths) for the 655 individuals who took less than 4000 steps per day; 21.4 per 1000 person-years (488 deaths) for the 1727 individuals who took 4000 to 7999 steps per day; 6.9 per 1000 person-years (176 deaths) for the 1539 individuals who took 8000 to 11 999 steps per day; and 4.8 per 1000 person-years (82 deaths) for the 919 individuals who took at least 12 000 steps per day. Compared with taking 4000 steps per day, taking 8000 steps per day was associated with significantly lower all-cause mortality (HR, 0.49 [95% CI, 0.44-0.55]), as was taking 12 000 steps per day (HR, 0.35 [95% CI, 0.28-0.45]). Unadjusted incidence density for all-cause mortality by peak 30 cadence was 32.9 per 1000 person-years (406 deaths) for the 1080 individuals who took 18.5 to 56.0 steps per minute; 12.6 per 1000 person-years (207 deaths) for the 1153 individuals who took 56.1 to 69.2 steps per minute; 6.8 per 1000 person-years (124 deaths) for the 1074 individuals who took 69.3 to 82.8 steps per minute; and 5.3 per 1000 person-years (108 deaths) for the 1037 individuals who took 82.9 to 149.5 steps per minute. Greater step intensity was not significantly associated with lower mortality after adjustment for total steps per day (eg, highest vs lowest quartile of peak 30 cadence: HR, 0.90 [95% CI, 0.65-1.27]; P value for trend = .34). Conclusions and Relevance:Based on a representative sample of US adults, a greater number of daily steps was significantly associated with lower all-cause mortality. There was no significant association between step intensity and mortality after adjusting for total steps per day.
| S-EPMC7093766 | biostudies-literature
Project description:Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device.
| S-EPMC9823757 | biostudies-literature
Project description:Pedometer step count improves with pulmonary rehabilitation and deteriorates with time. The MCID for improvement and deterioration is 427 and -456 steps, respectively, but there is uncertainty about the reliability of these estimates. https://bit.ly/3ci97Jh.
| S-EPMC7983253 | biostudies-literature
Project description:Predicting cardiorespiratory fitness levels can be useful for measuring progress in an exercise program as well as for stratifying cardiovascular risk in asymptomatic adults. This study proposes a model to predict fitness level in terms of maximal oxygen uptake using anthropometric, heart rate, and step count data. The model was trained on a diverse cohort of 3115 healthy subjects (1035 women and 2080 men) aged 42 ± 10.6 years and tested on a cohort of 779 healthy subjects (260 women and 519 men) aged 42 ± 10.18 years. The developed model is capable of making accurate and reliable predictions with the average test set error of 3.946 ml/kg/min. The maximal oxygen uptake labels were obtained using wearable devices (Apple Watch and Garmin) during recorded workout sessions. Additionally, the model was validated on a sample of 10 subjects with maximal oxygen uptake determined directly using a treadmill protocol in a laboratory setting and showed an error of 4.982 ml/kg/min. Unlike most other models, which use accelerometer readings as additional input data, the proposed model relies solely on heart rate and step counts-data readily available on the majority of fitness trackers. The proposed model provides a point estimation and a probabilistic prediction of cardiorespiratory fitness level, thus it can estimate the prediction's uncertainty and construct confidence intervals.
| S-EPMC10517160 | biostudies-literature
Project description:BackgroundPeople with HIV (PWH) may have lower daily activity levels compared with persons without HIV. We sought to determine the impact of initiating a supervised exercise program on the daily step count of sedentary PWH and uninfected controls.MethodsPWH and controls, aged 50-75, were enrolled in a 24-week supervised exercise program. All individuals were given a pedometer and instructed in regular use. A linear mixed model taking into account random effects was used to model daily step count.ResultsOf 69 participants that began the study, 55 completed and 38 (21 PWH, 17 controls) had complete pedometer data. Baseline daily step count on nonsupervised exercise day was (estimated geometric mean, 95% confidence interval) 3543 (1306 to 9099) for PWH and 4182 (1632 to 10,187) for controls. Both groups increased daily steps on supervised [43% (20 to 69)%, P < 0.001] but not unsupervised exercise days [-12% (-24 to 1)%, P = 0.071]. Compared with controls, PWH had 26% [(-47 to 4)%, P = 0.08] fewer daily steps on days with supervised exercise and 35% [-53 to -10)%, P = 0.011] fewer daily steps on days without supervised exercise. Higher body mass index (per 1 unit) and smoking were associated with fewer daily steps [-5% (-9 to -1)%; -49% (-67 to -23)%; P ≤ 0.012]. Days with precipitation [-8% (-13 to -3)%, P = 0.002] or below freezing [-10% [-15 to -4)%, P < 0.001] were associated with fewer steps.ConclusionSupervised exercise increased daily step counts in sedentary individuals, but at the expense of fewer steps on nonsupervised exercise days.
| S-EPMC7228846 | biostudies-literature
Project description:BackgroundPeople with dysvascular lower limb amputation (LLA) achieve one-third of the recommended steps per day and experience severe disability. Although physical function improves with rehabilitation after dysvascular LLA, physical activity remains largely unchanged, and factors contributing to limited daily step count are unknown.ObjectivesTo identify factors that contribute to daily step count after dysvascular LLA.DesignCross-sectional, secondary data analysis.SettingOutpatient rehabilitation facilities.ParticipantsFifty-eight patients with dysvascular major LLA (age: 64 ± 9 years, body mass index: 30 ± 8 kg/m2 , male: 95%, transtibial LLA: 95%).MethodsData were collected by a blinded assessor after dysvascular LLA. Candidate explanatory variables included (1) demographics, (2) LLA characteristics, (3) comorbidities and health behaviors, and (4) physical function. Variables with univariate associations with log steps/day (transformed due to non-normality) were included in a multiple linear regression model using backward elimination to identify factors that explained significant variability in log steps/day.Primary outcome measureThe primary outcome, daily step count, was measured with accelerometer-based activity monitors worn by participants for 10 days.ResultsParticipants took an average (± SD) of 1450 ± 1309 steps/day. After backward elimination, the final model included four variables explaining 62% of the overall daily step count (P < .0001): 2-minute walk distance (32%), assistive device use (11%), cardiovascular disease (10%), and pre-amputation walking time (11%).ConclusionsAverage daily step count of 1450 steps/day reflects the lowest category of sedentary behavior. Physical function, cardiovascular disease, and pre-amputation walking time explain 62% of daily step count after dysvascular LLA. Although physical rehabilitation commonly focuses on improving physical function, interventions to increase daily step count after dysvascular LLA should also consider chronic disease and health behaviors that predate LLA.Level of evidenceIII.
| S-EPMC8259321 | biostudies-literature
Project description:ImportanceRecent evidence syntheses have supported the protective role of daily steps in decreasing the risk of cardiovascular disease and all-cause mortality. However, step count-based recommendations should cover additional health outcomes.ObjectiveTo synthesize the associations between objectively measured daily step counts and depression in the general adult population.Data sourcesIn this systematic review and meta-analysis, a systematic search of the PubMed, PsycINFO, Scopus, SPORTDiscus, and Web of Science databases was conducted from inception until May 18, 2024, to identify observational studies using search terms related to physical activity, measures of daily steps, and depression, among others. Supplementary search methods were also applied.Study selectionAll identified studies were uploaded to an online review system and were considered without restrictions on publication date or language. Included studies had objectively measured daily step counts and depression data.Data extraction and synthesisThis systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology reporting guidelines. Two independent reviewers extracted the published data.Main outcomes and measuresPooled effect sizes (correlation coefficient, standardized mean difference [SMD], and risk ratio [RR]) with 95% CIs were estimated using the Sidik-Jonkman random-effects method.ResultsThirty-three studies (27 cross-sectional and 6 longitudinal [3 panel and 3 prospective cohort]) involving 96 173 adults aged 18 years or older (range of mean [SD] ages: 18.6 [0.6] to 91.2 [1.6] years) were included. Daily steps were inversely correlated with depressive symptoms in both cross-sectional and panel studies. Compared with fewer than 5000 steps/d, pooled SMDs from cross-sectional studies revealed that 10 000 or more steps/d (SMD, -0.26; 95% CI, -0.38 to -0.14), 7500 to 9999 steps/d (SMD, -0.27; 95% CI, -0.43 to -0.11), and 5000 to 7499 steps/d (SMD, -0.17; 95% CI, -0.30 to -0.04) were significantly associated with fewer depressive symptoms. Pooled estimates from prospective cohort studies indicated that participants with 7000 or more steps/d had reduced risk of depression compared with their counterparts with fewer than 7000 steps/d (RR, 0.69; 95% CI, 0.62-0.77). An increase of 1000 steps/d was associated with a lower risk of depression (RR, 0.91; 95% CI, 0.87-0.94).Conclusions and relevanceIn this systematic review and meta-analysis of 33 observational studies involving 96 173 adults, higher daily step counts were associated with fewer depressive symptoms in cross-sectional and longitudinal studies in the general adult population. Further prospective cohort studies are needed to clarify the potential protective role of daily steps in mitigating the risk of depression during adulthood.
| S-EPMC11650418 | biostudies-literature
Project description:ObjectivePrior research has implied that promoting sustaining physical activity through nudges is challenging and boosting health literacy is important for the long-term establishment of behaviors. This study aimed to investigate the effects of commitment-based health application on step count and health literacy.MethodsA control experiment was conducted involving employees from companies located in Shizuoka Prefecture, Japan. Participants were divided into three groups: the commitment app group (utilizing a commitment-based application "Minchalle," where teams of around five members were randomly assigned to declare a target step count and report daily step count with pictures), the self-commitment group (individuals declaring a target step count and endeavoring on their own), and the control group (no intervention). Changes in step count and health literacy were examined over one month.ResultsA total of 109 employees from 7 companies participated. The changes in step count were an increase of 893 steps for the commitment app group, 243 steps for the self-commitment group, and 178 steps for the control group, with a significant increase in the commitment app group compared to the control group. Regarding health literacy measures, there was significant progress in four items out of five for the commitment app group compared to the control group, and significant progress in one item for the self-commitment group compared to the control group.ConclusionCommunication within the app teams, such as commitment, sharing photos of their goal achievements and provide encouraging comments to others, functioned as social nudges, suggesting the potential for an immediate increase in step count and long-term behavioral reinforcement through improved health literacy.
| S-EPMC11318894 | biostudies-literature
Project description: Not available
| S-EPMC11562455 | biostudies-literature
Project description:Despite the accessibility of several step count measurement systems, count accuracy in real environments remains a major challenge. Microelectromechanical systems and pressure sensors seem to present a potential solution for step count accuracy. The purpose of this study was to equip an insole with pressure sensors and to test a novel and potentially more accurate method of detecting steps. Methods: Five force-sensitive resistors (FSR) were integrated under the heel, the first, third, and fifth metatarsal heads and the great toe. This system was tested with twelve healthy participants at self-selected and maximal walking speeds in indoor and outdoor settings. Step counts were computed based on previously reported calculation methods, individual and averaged FSR-signals, and a new method: cumulative sum of all FSR-signals. These data were compared to a direct visual step count for accuracy analysis. Results: This system accurately detected steps with success rates ranging from 95.5 ± 3.5% to 98.5 ± 2.1% (indoor) and from 96.5 ± 3.9% to 98.0 ± 2.3% (outdoor) for self-selected walking speeds and from 98.1 ± 2.7% to 99.0 ± 0.7% (indoor) and 97.0 ± 6.2% to 99.4 ± 0.7% (outdoor) for maximal walking speeds. Cumulative sum of pressure signals during the stance phase showed high step detection accuracy (99.5 ± 0.7%⁻99.6 ± 0.4%) and appeared to be a valid method of step counting. Conclusions: The accuracy of step counts varied according to the calculation methods, with cumulative sum-based method being highly accurate.
| S-EPMC6427154 | biostudies-literature