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  1. Khoo S, Mohbin N, Ansari P, Al-Kitani M, Müller AM
    PMID: 34071342 DOI: 10.3390/ijerph18115798
    This review aimed to identify, evaluate, and synthesize the scientific literature on mobile health (mHealth) interventions to promote physical activity (PA) or reduce sedentary behavior (SB) in cancer survivors. We searched six databases from 2000 to 13 April 2020 for controlled and non-controlled trials published in any language. We conducted best evidence syntheses on controlled trials to assess the strength of the evidence. All 31 interventions included in this review measured PA outcomes, with 10 of them also evaluating SB outcomes. Most study participants were adults/older adults with various cancer types. The majority (n = 25) of studies implemented multicomponent interventions, with activity trackers being the most commonly used mHealth technology. There is strong evidence for mHealth interventions, including personal contact components, in increasing moderate-to-vigorous intensity PA among cancer survivors. However, there is inconclusive evidence to support mHealth interventions in increasing total activity and step counts. There is inconclusive evidence on SB potentially due to the limited number of studies. mHealth interventions that include personal contact components are likely more effective in increasing PA than mHealth interventions without such components. Future research should address social factors in mHealth interventions for PA and SB in cancer survivors.
    Matched MeSH terms: Fitness Trackers
  2. Müller AM, Wang NX, Yao J, Tan CS, Low ICC, Lim N, et al.
    JMIR Mhealth Uhealth, 2019 10 02;7(10):e14120.
    PMID: 31579026 DOI: 10.2196/14120
    BACKGROUND: Wrist-worn activity trackers are popular, and an increasing number of these devices are equipped with heart rate (HR) measurement capabilities. However, the validity of HR data obtained from such trackers has not been thoroughly assessed outside the laboratory setting.

    OBJECTIVE: This study aimed to investigate the validity of HR measures of a high-cost consumer-based tracker (Polar A370) and a low-cost tracker (Tempo HR) in the laboratory and free-living settings.

    METHODS: Participants underwent a laboratory-based cycling protocol while wearing the two trackers and the chest-strapped Polar H10, which acted as criterion. Participants also wore the devices throughout the waking hours of the following day during which they were required to conduct at least one 10-min bout of moderate-to-vigorous physical activity (MVPA) to ensure variability in the HR signal. We extracted 10-second values from all devices and time-matched HR data from the trackers with those from the Polar H10. We calculated intraclass correlation coefficients (ICCs), mean absolute errors, and mean absolute percentage errors (MAPEs) between the criterion and the trackers. We constructed decile plots that compared HR data from Tempo HR and Polar A370 with criterion measures across intensity deciles. We investigated how many HR data points within the MVPA zone (≥64% of maximum HR) were detected by the trackers.

    RESULTS: Of the 57 people screened, 55 joined the study (mean age 30.5 [SD 9.8] years). Tempo HR showed moderate agreement and large errors (laboratory: ICC 0.51 and MAPE 13.00%; free-living: ICC 0.71 and MAPE 10.20%). Polar A370 showed moderate-to-strong agreement and small errors (laboratory: ICC 0.73 and MAPE 6.40%; free-living: ICC 0.83 and MAPE 7.10%). Decile plots indicated increasing differences between Tempo HR and the criterion as HRs increased. Such trend was less pronounced when considering the Polar A370 HR data. Tempo HR identified 62.13% (1872/3013) and 54.27% (5717/10,535) of all MVPA time points in the laboratory phase and free-living phase, respectively. Polar A370 detected 81.09% (2273/2803) and 83.55% (9323/11,158) of all MVPA time points in the laboratory phase and free-living phase, respectively.

    CONCLUSIONS: HR data from the examined wrist-worn trackers were reasonably accurate in both the settings, with the Polar A370 showing stronger agreement with the Polar H10 and smaller errors. Inaccuracies increased with increasing HRs; this was pronounced for Tempo HR.

    Matched MeSH terms: Fitness Trackers/standards*; Fitness Trackers/statistics & numerical data
  3. Ibrahim NS, Rampal S, Lee WL, Pek EW, Suhaimi A
    Cardiovasc Eng Technol, 2024 Feb;15(1):12-21.
    PMID: 37973701 DOI: 10.1007/s13239-023-00693-z
    PURPOSE: Photoplethysmography measurement of heart rate with wrist-worn trackers has been introduced in healthy individuals. However, additional consideration is necessary for patients with ischemic heart disease, and the available evidence is limited. The study aims to evaluate the validity and reliability of heart rate measures by a wrist-worn photoplethysmography (PPG) tracker compared to an electrocardiogram (ECG) during incremental treadmill exercise among patients with ischemic heart disease.

    METHODS: Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers.

    RESULTS: At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent.

    CONCLUSIONS: Low-cost trackers AMAZFIT Cor and Bip validity and reliability were within acceptable ranges, especially during low-intensity exercise among patients with ischemic heart disease recovering from cardiac procedures. Though using the tracker as part of the diagnosis tool still requires more supporting studies, it can potentially be used as a self-monitoring tool with precautions.

    Matched MeSH terms: Fitness Trackers
  4. Chu AHY, Bernard JY, Koh D, Müller-Riemenschneider F
    Res Q Exerc Sport, 2021 Sep;92(3):361-368.
    PMID: 32154777 DOI: 10.1080/02701367.2020.1734520
    Purpose: Variability in accelerometry-data processing decisions limited data comparability across studies. We aimed to examine different accelerometry-data processing rules: varying bout lengths and allowance of 0- and 2-min interruptions on the total and bout-accumulated time spent in moderate-to-vigorous physical activity (MVPA) and sedentary behavior estimates, and describe the distribution of activity time based on counts per min (CPM) in granular categories. Method: Using the Singapore Health 2 survey, this study included 746 adults (41.8% women, median age 45.0 years) who provided valid ActiGraph GT3X+ accelerometer-data (≥4 valid days with ≥10-h/day). Quantile regression analysis adjusting for accelerometry daily wear time, age, and gender was performed to calculate the median and interquartile range of accelerometry estimates. Results: Median MVPA time accumulated in bouts of 1-min versus bouts of 10-min was 39.2 min/day and 6.0 min/day, respectively. MVPA time was higher when considering a 2-min interruption (range: 1.8-39.2 min/day) compared to 0-min interruption (range: 0-35.5 min/day) across bout lengths of 1- to 15-min. Participants were sedentary (≤100 CPM) for a daily median of 7.6 h/day. Median activities min/day on the lower-intensity activity spectrum (100-2499 CPM) decreased from 63.4 to 4.6 min/day, while on the higher-intensity activity spectrum (≥2500 CPM) was ≤2.9 min/day. Men generally spent more time in MVPA than women. Conclusions: This study highlights the differences in accelerometry estimates based on data processing decisions, and the importance of quantifying accelerometry-based activity time across the granular intensity spectrum. More studies are warranted to understand the determinants and health impact of these behaviors.
    Matched MeSH terms: Fitness Trackers*
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