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Journal of Clinical Sleep Medicine :... Dec 2015To review sleep related consumer technologies, including mobile electronic device "apps," wearable devices, and other technologies. Validation and methodological... (Review)
Review
OBJECTIVE
To review sleep related consumer technologies, including mobile electronic device "apps," wearable devices, and other technologies. Validation and methodological transparency, the effect on clinical sleep medicine, and various social, legal, and ethical issues are discussed.
METHODS
We reviewed publications from the digital libraries of the Association for Computing Machinery, Institute of Electrical and Electronics Engineers, and PubMed; publications from consumer technology websites; and mobile device app marketplaces. Search terms included "sleep technology," "sleep app," and "sleep monitoring."
RESULTS
Consumer sleep technologies are categorized by delivery platform including mobile device apps (integrated with a mobile operating system and utilizing mobile device functions such as the camera or microphone), wearable devices (on the body or attached to clothing), embedded devices (integrated into furniture or other fixtures in the native sleep environment), accessory appliances, and conventional desktop/website resources. Their primary goals include facilitation of sleep induction or wakening, self-guided sleep assessment, entertainment, social connection, information sharing, and sleep education.
CONCLUSIONS
Consumer sleep technologies are changing the landscape of sleep health and clinical sleep medicine. These technologies have the potential to both improve and impair collective and individual sleep health depending on method of implementation.
Topics: Accelerometry; Actigraphy; Humans; Mobile Applications; Monitoring, Ambulatory; Reproducibility of Results; Sleep; Sleep Wake Disorders; Smartphone
PubMed: 26156958
DOI: 10.5664/jcsm.5288 -
The Journal of Veterinary Medical... Jun 2024The sleep-wake cycle represents a crucial physiological process essential for maintaining homeostasis and promoting individual growth. In dogs, alterations in sleep...
The sleep-wake cycle represents a crucial physiological process essential for maintaining homeostasis and promoting individual growth. In dogs, alterations in sleep patterns associated with age and dog's correlation with temperament factors, such as nervousness, have been reported, and there is an increasing demand for precise monitoring of sleep and physical activity in dogs. The present study aims to develop an analysis method for measuring sleep-wake patterns and physical activity in dogs by utilizing an accelerometer and a smartphone. By analyzing time series data collected from the accelerometer attached to the dog's collar, a comprehensive sleep and activity analysis model was constructed. This model classified the activity level into seven classes and effectively highlighted the variations in sleep-activity patterns. Two classes with lower activity levels were considered as sleep, while other five levels were regarded as wake based on the rate of occurrence. This protocol of data acquisition and analysis provides a methodology that enables accurate and extended evaluation of both sleep and physical activity in dogs.
Topics: Animals; Dogs; Sleep; Accelerometry; Smartphone; Male; Female; Wakefulness; Monitoring, Physiologic; Motor Activity
PubMed: 38684414
DOI: 10.1292/jvms.23-0472 -
The International Journal of Behavioral... Apr 2012To undertake a review of the methods and findings of published research evaluating the influence of season on accelerometer-determined sedentary behaviour (SB) and... (Review)
Review
AIM
To undertake a review of the methods and findings of published research evaluating the influence of season on accelerometer-determined sedentary behaviour (SB) and physical activity (PA) in children.
METHODS
A literature search was carried out using PubMed, Embase, Medline and Web of Science up to, and including, June 2011. The search strategy focused on four key elements: children, SB or PA, season and accelerometer. Articles were eligible for inclusion if they were published in English, included healthy study participants aged ≤ 18 years, reported at least one outcome variable derived from accelerometer-determined measurements, and compared SB or PA between two or more seasons, or controlled for season of measurement. Eligible papers were reviewed and evidence tables compiled reporting on publication year, country studied, study recruitment, consent rate, sample descriptives, study design, accelerometer protocol, valid accelerometer data receipt, season definition, statistical methods and key findings.
RESULTS
Sixteen of 819 articles were eligible for inclusion: children aged two to five years, six to twelve, or six to 18 years were included in five, six and five articles respectively. Six articles were from the UK, six from other European countries, three from the USA and one from New Zealand. Study sample sizes ranged from 64 to 5595. PA was reported in all articles but SB in only three. Only four studies were longitudinal and none of these reported SB. Seasonal variation in PA was reported in all UK studies, being highest in summer and lowest in winter. In four non-UK studies seasonal variation in PA was not found. Findings were inconclusive for SB.
CONCLUSION
There is sufficient evidence to support public health interventions aimed at increasing PA during winter in UK children. No conclusions can be drawn regarding the effect of season on children's SB reflecting few studies of small sample size, lack of repeat measures, incomparable definitions of season and inconsistent accelerometer protocols. Future research should determine factors that drive seasonal patterns in PA and SB in children such as age, sex, and geographic and climatic setting to inform interventions and target populations.
Topics: Accelerometry; Adolescent; Child; Child Behavior; Child, Preschool; Climate; Europe; Exercise; Female; Humans; Male; Motor Activity; New Zealand; Seasons; Sedentary Behavior; United States
PubMed: 22546178
DOI: 10.1186/1479-5868-9-49 -
The International Journal of Behavioral... Feb 2020Early experiences in physical activity (PA) are important to shape healthy movement behaviours long-term; as such, it is critical that PA is promoted from infancy, and... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Early experiences in physical activity (PA) are important to shape healthy movement behaviours long-term; as such, it is critical that PA is promoted from infancy, and that detrimental behaviours (e.g., prolonged sedentary time [ST]) are minimized. The purpose of this systematic review and meta-analysis was to examine infants' and toddlers' movement behaviours across daytime hours.
METHODS
Seven online databases were searched for terms related to infants (< 12 months), toddlers (12-35.9 months), PA, ST, and accelerometry. Two independent reviewers examined 4873 articles for peer-reviewed original research, published in English, that assessed infants' (counts/min) and/or toddlers' PA or ST (min/day) using accelerometry across daytime hours. Infants' mean PA level (counts/min) was averaged across studies, and ranges were produced. Estimates of toddlers' movement behaviours were aggregated meta-analytically to produce average daily rates, and accelerometer placement, cut-point validity, device type, and epoch length were tested as a moderating variables.
RESULTS
Twenty-four studies from 16 countries (published 2011-2019), representing 3699 participants, were included in the systematic review. Five studies reported on infants' PA, which ranged from 78.2 to 2580.5 cpm. Across 20 studies, toddlers' total PA, light PA, moderate-to vigorous-intensity PA, and ST ranged from 72.9 to 636.5, 48.5 to 582.4, 6.5 to 89.9, and 172.7 to 545.0 min/day, respectively. After taking into account accelerometer placement, cut-point validity, device type, and epoch length, we found that toddlers engaged in 246.19 min/day (SE = 28.50; 95% CI: 190.34, 302.04) of total PA, 194.10 min/day (SE = 28.76; 95% CI: 137.73, 250.47) of light PA, and 60.16 min/day (SE = 5.88; 95% CI: 48.64, 71.69) of moderate-to vigorous-intensity PA. Toddlers engaged in 337.04 min/day (SE = 32.67; 95% CI: 273.01, 401.07) of ST.
CONCLUSIONS
With limited studies conducted in infants (n = 5), PA estimates are inconclusive and largely heterogeneous. Overall, toddlers tend to exceed the total PA recommendation of 180 min/day; however, very little of this time is spent at higher movement intensities. Even with high PA rates, toddlers still engage in substantial ST. More consistent and valid measurement protocols are needed to improve comparability across studies.
Topics: Accelerometry; Child, Preschool; Exercise; Humans; Infant; Monitoring, Ambulatory; Sedentary Behavior
PubMed: 32028975
DOI: 10.1186/s12966-020-0912-4 -
The International Journal of Behavioral... Dec 2015Consumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to... (Review)
Review
BACKGROUND
Consumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to summarize the evidence for validity and reliability of popular consumer-wearable activity trackers (Fitbit and Jawbone) and their ability to estimate steps, distance, physical activity, energy expenditure, and sleep.
METHODS
Searches included only full-length English language studies published in PubMed, Embase, SPORTDiscus, and Google Scholar through July 31, 2015. Two people reviewed and abstracted each included study.
RESULTS
In total, 22 studies were included in the review (20 on adults, 2 on youth). For laboratory-based studies using step counting or accelerometer steps, the correlation with tracker-assessed steps was high for both Fitbit and Jawbone (Pearson or intraclass correlation coefficients (CC) > =0.80). Only one study assessed distance for the Fitbit, finding an over-estimate at slower speeds and under-estimate at faster speeds. Two field-based studies compared accelerometry-assessed physical activity to the trackers, with one study finding higher correlation (Spearman CC 0.86, Fitbit) while another study found a wide range in correlation (intraclass CC 0.36-0.70, Fitbit and Jawbone). Using several different comparison measures (indirect and direct calorimetry, accelerometry, self-report), energy expenditure was more often under-estimated by either tracker. Total sleep time and sleep efficiency were over-estimated and wake after sleep onset was under-estimated comparing metrics from polysomnography to either tracker using a normal mode setting. No studies of intradevice reliability were found. Interdevice reliability was reported on seven studies using the Fitbit, but none for the Jawbone. Walking- and running-based Fitbit trials indicated consistently high interdevice reliability for steps (Pearson and intraclass CC 0.76-1.00), distance (intraclass CC 0.90-0.99), and energy expenditure (Pearson and intraclass CC 0.71-0.97). When wearing two Fitbits while sleeping, consistency between the devices was high.
CONCLUSION
This systematic review indicated higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. The evidence reviewed indicated high interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models. As new activity trackers and features are introduced to the market, documentation of the measurement properties can guide their use in research settings.
Topics: Accelerometry; Energy Metabolism; Female; Humans; Male; Monitoring, Ambulatory; Reproducibility of Results; Running; Sleep; Validation Studies as Topic; Walking
PubMed: 26684758
DOI: 10.1186/s12966-015-0314-1 -
Medicine and Science in Sports and... Sep 2023Five times sit-to-stand (STS) test is commonly used as a clinical assessment of lower-extremity functional ability, but its association with free-living performance has...
PURPOSE
Five times sit-to-stand (STS) test is commonly used as a clinical assessment of lower-extremity functional ability, but its association with free-living performance has not been studied. Therefore, we investigated the association between laboratory-based STS capacity and free-living STS performance using accelerometry. The results were stratified according to age and functional ability groups.
METHODS
This cross-sectional study included 497 participants (63% women) 60-90 yr old from three independent studies. A thigh-worn triaxial accelerometer was used to estimate angular velocity in maximal laboratory-based STS capacity and in free-living STS transitions over 3-7 d of continuous monitoring. Functional ability was assessed with short physical performance battery.
RESULTS
Laboratory-based STS capacity was moderately associated with the free-living mean and maximal STS performance ( r = 0.52-0.65, P < 0.01). Angular velocity was lower in older compared with younger and in low- versus high-functioning groups, in both capacity and free-living STS variables (all P < 0.05). Overall, angular velocity was higher in capacity compared with free-living STS performance. The STS reserve (test capacity - free-living maximal performance) was larger in younger and in high-functioning groups compared with older and low-functioning groups (all P < 0.05).
CONCLUSIONS
Laboratory-based STS capacity and free-living performance were found to be associated. However, capacity and performance are not interchangeable but rather provide complementary information. Older and low-functioning individuals seemed to perform free-living STS movements at a higher percentage of their maximal capacity compared with younger and high-functioning individuals. Therefore, we postulate that low capacity may limit free-living performance.
Topics: Humans; Adult; Female; Aged; Male; Thigh; Cross-Sectional Studies; Movement; Activities of Daily Living; Accelerometry
PubMed: 37005494
DOI: 10.1249/MSS.0000000000003178 -
Gait & Posture Oct 2022Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another.
BACKGROUND
Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another.
RESEARCH QUESTION
What are the differences and associations between the steps of 13 selected consumer-based and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials?
METHODS
In total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days).
RESULTS
When the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87-0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P < 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility.
SIGNIFICANCE
Step obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions.
Topics: Adult; Humans; Young Adult; Middle Aged; Fitness Trackers; Accelerometry; Exercise; Actigraphy; Wearable Electronic Devices; Reproducibility of Results
PubMed: 36030707
DOI: 10.1016/j.gaitpost.2022.08.004 -
JMIR MHealth and UHealth Jul 2022Given the evolution of processing and analysis methods for accelerometry data over the past decade, it is important to understand how newer summary measures of physical... (Comparative Study)
Comparative Study Observational Study
BACKGROUND
Given the evolution of processing and analysis methods for accelerometry data over the past decade, it is important to understand how newer summary measures of physical activity compare with established measures.
OBJECTIVE
We aimed to compare objective measures of physical activity to increase the generalizability and translation of findings of studies that use accelerometry-based data.
METHODS
High-resolution accelerometry data from the Baltimore Longitudinal Study on Aging were retrospectively analyzed. Data from 655 participants who used a wrist-worn ActiGraph GT9X device continuously for a week were summarized at the minute level as ActiGraph activity count, monitor-independent movement summary, Euclidean norm minus one, mean amplitude deviation, and activity intensity. We calculated these measures using open-source packages in R. Pearson correlations between activity count and each measure were quantified both marginally and conditionally on age, sex, and BMI. Each measures pair was harmonized using nonparametric regression of minute-level data.
RESULTS
Data were from a sample (N=655; male: n=298, 45.5%; female: n=357, 54.5%) with a mean age of 69.8 years (SD 14.2) and mean BMI of 27.3 kg/m2 (SD 5.0). The mean marginal participant-specific correlations between activity count and monitor-independent movement summary, Euclidean norm minus one, mean amplitude deviation, and activity were r=0.988 (SE 0.0002324), r=0.867 (SE 0.001841), r=0.913 (SE 0.00132), and r=0.970 (SE 0.0006868), respectively. After harmonization, mean absolute percentage errors of predicting total activity count from monitor-independent movement summary, Euclidean norm minus one, mean amplitude deviation, and activity intensity were 2.5, 14.3, 11.3, and 6.3, respectively. The accuracies for predicting sedentary minutes for an activity count cut-off of 1853 using monitor-independent movement summary, Euclidean norm minus one, mean amplitude deviation, and activity intensity were 0.981, 0.928, 0.904, and 0.960, respectively. An R software package called SummarizedActigraphy, with a unified interface for computation of the measures from raw accelerometry data, was developed and published.
CONCLUSIONS
The findings from this comparison of accelerometry-based measures of physical activity can be used by researchers and facilitate the extension of knowledge from existing literature by demonstrating the high correlation between activity count and monitor-independent movement summary (and other measures) and by providing harmonization mapping.
Topics: Accelerometry; Aged; Aging; Data Analysis; Exercise; Female; Humans; Longitudinal Studies; Male; Retrospective Studies
PubMed: 35867392
DOI: 10.2196/38077 -
Journal of Neuroengineering and... Mar 2017The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This... (Review)
Review
BACKGROUND
The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies.
METHOD
A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010-April 2016).
RESULTS
Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial.
CONCLUSIONS
This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.
Topics: Accelerometry; Biomechanical Phenomena; Clothing; Humans; Movement; Posture; Range of Motion, Articular; Rehabilitation
PubMed: 28284228
DOI: 10.1186/s12984-017-0229-y -
British Journal of Sports Medicine Jul 2014The technology and application of current accelerometer-based devices in physical activity (PA) research allow the capture and storage or transmission of large volumes... (Review)
Review
The technology and application of current accelerometer-based devices in physical activity (PA) research allow the capture and storage or transmission of large volumes of raw acceleration signal data. These rich data not only provide opportunities to improve PA characterisation, but also bring logistical and analytic challenges. We discuss how researchers and developers from multiple disciplines are responding to the analytic challenges and how advances in data storage, transmission and big data computing will minimise logistical challenges. These new approaches also bring the need for several paradigm shifts for PA researchers, including a shift from count-based approaches and regression calibrations for PA energy expenditure (PAEE) estimation to activity characterisation and EE estimation based on features extracted from raw acceleration signals. Furthermore, a collaborative approach towards analytic methods is proposed to facilitate PA research, which requires a shift away from multiple independent calibration studies. Finally, we make the case for a distinction between PA represented by accelerometer-based devices and PA assessed by self-report.
Topics: Accelerometry; Consensus; Diffusion of Innovation; Exercise; Humans; Monitoring, Ambulatory; Nutrition Surveys; Self Report
PubMed: 24782483
DOI: 10.1136/bjsports-2014-093546