Evaluating Accuracy in Five Commercial Sleep-Tracking Devices Compared to Research-Grade Actigraphy and Polysomnography.

The development of consumer sleep-tracking technologies has outpaced the scientific evaluation of their accuracy. In this study, five consumer sleep-tracking devices, research-grade actigraphy, and polysomnography were used simultaneously to monitor the overnight sleep of fifty-three young adults in the lab for one night. Biases and limits of agreement were assessed to determine how sleep stage estimates for each device and research-grade actigraphy differed from polysomnography-derived measures. Every device, except the Garmin Vivosmart, was able to estimate total sleep time comparably to research-grade actigraphy. All devices overestimated nights with shorter wake times and underestimated nights with longer wake times. For light sleep, absolute bias was low for the Fitbit Inspire and Fitbit Versa. The Withings Mat and Garmin Vivosmart overestimated shorter light sleep and underestimated longer light sleep. The Oura Ring underestimated light sleep of any duration. For deep sleep, bias was low for the Withings Mat and Garmin Vivosmart while other devices overestimated shorter and underestimated longer times. For REM sleep, bias was low for all devices. Taken together, these results suggest that proportional bias patterns in consumer sleep-tracking technologies are prevalent and could have important implications for their overall accuracy.

Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial.

BACKGROUND: Over the recent years, technological advances of wrist-worn fitness trackers heralded a new era in the continuous monitoring of vital signs. So far, these devices have primarily been used for sports. OBJECTIVE: However, for using these technologies in health care, further validations of the measurement accuracy in hospitalized patients are essential but lacking to date. METHODS: We conducted a prospective validation study with 201 patients after moderate to major surgery in a controlled setting to benchmark the accuracy of heart rate measurements in 4 consumer-grade fitness trackers (Apple Watch 7, Garmin Fenix 6 Pro, Withings ScanWatch, and Fitbit Sense) against the clinical gold standard (electrocardiography). RESULTS: All devices exhibited high correlation (r≥0.95; P<.001) and concordance (rc≥0.94) coefficients, with a relative error as low as mean absolute percentage error <5% based on 1630 valid measurements. We identified confounders significantly biasing the measurement accuracy, although not at clinically relevant levels (mean absolute error<5 beats per minute). CONCLUSIONS: Consumer-grade fitness trackers appear promising in hospitalized patients for monitoring heart rate. TRIAL REGISTRATION: ClinicalTrials.gov NCT05418881; https://www.clinicaltrials.gov/ct2/show/NCT05418881.

Validation of the Withings ScanWatch as a Wrist-Worn Reflective Pulse Oximeter: Prospective Interventional Clinical Study.

BACKGROUND: A decrease in the level of pulse oxygen saturation as measured by pulse oximetry (SpO2) is an indicator of hypoxemia that may occur in various respiratory diseases, such as chronic obstructive pulmonary disease (COPD), sleep apnea syndrome, and COVID-19. Currently, no mass-market wrist-worn SpO2 monitor meets the medical standards for pulse oximeters. OBJECTIVE: The main objective of this monocentric and prospective clinical study with single-blind analysis was to test and validate the accuracy of the reflective pulse oximeter function of the Withings ScanWatch to measure SpO2 levels at different stages of hypoxia. The secondary objective was to confirm the safety of this device when used as intended. METHODS: To achieve these objectives, we included 14 healthy participants aged 23-39 years in the study, and we induced several stable plateaus of arterial oxygen saturation (SaO2) ranging from 100%-70% to mimic nonhypoxic conditions and then mild, moderate, and severe hypoxic conditions. We measured the SpO2 level with a Withings ScanWatch on each participant's wrist and the SaO2 from blood samples with a co-oximeter, the ABL90 hemoximeter (Radiometer Medical ApS). RESULTS: After removal of the inconclusive measurements, we obtained 275 and 244 conclusive measurements with the two ScanWatches on the participants' right and left wrists, respectively, evenly distributed among the 3 predetermined SpO2 groups: SpO2≤80%, 80%

Sleep in the Natural Environment: A Pilot Study.

Sleep quality has been directly linked to cognitive function, quality of life, and a variety of serious diseases across many clinical domains. Standard methods for assessing sleep involve overnight studies in hospital settings, which are uncomfortable, expensive, not representative of real sleep, and difficult to conduct on a large scale. Recently, numerous commercial digital devices have been developed that record physiological data, such as movement, heart rate, and respiratory rate, which can act as a proxy for sleep quality in lieu of standard electroencephalogram recording equipment. The sleep-related output metrics from these devices include sleep staging and total sleep duration and are derived via proprietary algorithms that utilize a variety of these physiological recordings. Each device company makes different claims of accuracy and measures different features of sleep quality, and it is still unknown how well these devices correlate with one another and perform in a research setting. In this pilot study of 21 participants, we investigated whether sleep metric outputs from self-reported sleep metrics (SRSMs) and four sensors, specifically Fitbit Surge (a smart watch), Withings Aura (a sensor pad that is placed under a mattress), Hexoskin (a smart shirt), and Oura Ring (a smart ring), were related to known cognitive and psychological metrics, including the n-back test and Pittsburgh Sleep Quality Index (PSQI). We analyzed correlation between multiple device-related sleep metrics. Furthermore, we investigated relationships between these sleep metrics and cognitive scores across different timepoints and SRSM through univariate linear regressions. We found that correlations for sleep metrics between the devices across the sleep cycle were almost uniformly low, but still significant (P < 0.05). For cognitive scores, we found the Withings latency was statistically significant for afternoon and evening timepoints at P = 0.016 and P = 0.013. We did not find any significant associations between SRSMs and PSQI or cognitive scores. Additionally, Oura Ring's total sleep duration and efficiency in relation to the PSQI measure was statistically significant at P = 0.004 and P = 0.033, respectively. These findings can hopefully be used to guide future sensor-based sleep research.

An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices.

BACKGROUND: Sleep is a modifiable lifestyle factor that can be a target for efficient intervention studies to improve the quality of life and decrease the risk or burden of some chronic conditions. Knowing the profiles of individuals with poor sleep patterns is therefore a prerequisite. Wearable devices have recently opened new areas in medical research as potential efficient tools to measure lifestyle factors such as sleep quantity and quality. OBJECTIVES: The goal of our research is to identify the determinants of poor sleep based on data from a large population of users of connected devices. METHODS: We analyzed data from 15,839 individuals (13,658 males and 2181 females) considered highly connected customers having purchased and used at least 3 connected devices from the consumer electronics company Withings (now Nokia). Total and deep sleep durations as well as the ratio of deep/total sleep as a proxy of sleep quality were analyzed in association with available data on age, sex, weight, heart rate, steps, and diastolic and systolic blood pressures. RESULTS: With respect to the deep/total sleep duration ratio used as a proxy of sleep quality, we have observed that those at risk of having a poor ratio (≤0.40) were more frequently males (odds ratio [OR]female vs male=0.45, 95% CI 0.38-0.54), younger individuals (OR>60 years vs 18-30 years=0.47, 95% CI 0.35-0.63), and those with elevated heart rate (OR>78 bpm vs ≤61 bpm=1.18, 95% CI 1.04-1.34) and high systolic blood pressure (OR>133 mm Hg vs ≤116 mm Hg=1.22, 95% CI 1.04-1.43). A direct association with weight was observed for total sleep duration exclusively. CONCLUSIONS: Wearables can provide useful information to target individuals at risk of poor sleep. Future alert or mobile phone notification systems based on poor sleep determinants measured with wearables could be tested in intervention studies to evaluate the benefits.

Primary Prevention of Asymptomatic Cardiovascular Disease Using Physiological Sensors Connected to an iOS App.

Cardiovascular disease is the first cause of death and disease and one of the leading causes of disability in developed countries. The prevalence of this disease is expected to increase in coming years although the death rate may be lower due to better treatment. To present the design and development of a technology solution for primary prevention of cardiovascular disease in asymptomatic patients. The system aims to raise the population's awareness of the importance of adopting healthy heart habits by using self-feedback techniques. A series of sensors which makes it possible to detect cardiovascular risk factors in asymptomatic patients were used. These sensors enable evaluation of heart rate, blood pressure, SpO2 -oxygen saturation in blood- and body temperature. This work has developed a modular solution centred on four parts: iOS app, sensors, server and web. The CoreBluetooth library, which carries out Bluetooth 4.0 communication, was used for the connection between the app and the sensors. The data files are stored on the iPad and the server by using CoreData and SQL mechanisms. The system was validated with 20 healthy volunteers and 10 patients with established structural heart disease. Once the samples had been obtained, a comparison of all the significant data was run, in addition to a statistical analysis. The result of this calculation was a total of 32 cases of first level significance correlations (p < 0.01), for example, the inverse relationship between the daily step count and high blood pressure (p = 0.008) and 24 s level cases (p < 0.05) such as the significant correlation between risk and age (p = 0.013). The system designed in this paper has made it possible to create an application capable of collecting data on cardiovascular risk factors through a sensor system that measures physiological variables and records physical activity and diet.

Reliability of continuous vital sign monitoring in post-operative patients employing consumer-grade fitness trackers: A randomised pilot trial.

Introduction: Fitness trackers can provide continuous monitoring of vital signs and thus have the potential to become a complementary, mobile and effective tool for early detection of patient deterioration and post-operative complications. Methods: To evaluate potential implementations in acute care setting, we included 36 patients after moderate to major surgery in a recent randomised pilot trial to compare the performance of vital sign monitoring by three different fitness trackers (Apple Watch 7, Garmin Fenix 6pro and Withings ScanWatch) with established standard clinical monitors in post-anaesthesia care units and monitoring wards. Results: During a cumulative period of 56 days, a total of 53,197 heart rate (HR) measurements, as well as 12,219 measurements of the peripheral blood oxygen saturation (SpO2) and 28,954 respiratory rate (RR) measurements were collected by fitness trackers. Under real-world conditions, HR monitoring was accurate and reliable across all benchmarked devices (r = [0.95;0.98], p < 0.001; Bias = [-0.74 bpm;-0.01 bpm]; MAPE∼2%). However, the performance of SpO2 (r = [0.21;0.68]; p < 0.001; Bias = [-0.46%;-2.29%]; root-mean-square error = [2.82%;4.1%]) monitoring was substantially inferior. RR measurements could not be obtained for two of the devices, therefore exclusively the accuracy of the Garmin tracker could be evaluated (r = 0.28, p < 0.001; Bias = -1.46/min). Moreover, the time resolution of the vital sign measurements highly depends on the tracking device, ranging from 0.7 to 117.94 data points per hour. Conclusion: According to the results of the present study, tracker devices are generally reliable and accurate for HR monitoring, whereas SpO2 and RR measurements should be interpreted carefully, considering the clinical context of the respective patients.

Feasibility and reliability of whintings scanwatch to record 4-lead Electrocardiogram: A comparative analysis with a standard ECG.

The recent technological advances allowed us to produce some new wearable devices, such as smartphones and smartwatches (SW). These devices provide different services to their users through different software applications installed even in the SW or smartphones. Health monitoring functionalities, among these services, are nowadays the new technological fashion. In fact, the monitoring is ensured by the sensor incorporated in the SW. The SW allows the record of only one single lead Electrocardiogram (ECG), which is sufficient to screen or diagnosis of rhythm and conduction disorders, especially during the onset of cardiac symptoms, but insufficient for the detection of ischemic disease and cardiomyopathies. In this context, this paper aims to evaluate the feasibility, and reliability of a SW to obtain ECG recordings in comparison with a standard ECG. For that purpose, 140 patients were recruited for this analysis. At the first step, the 12 lead ECG followed with four lead SW-ECG; using the Withings Scanwatch device, were recorded in the same resting conditions. The four lead SW-ECG consists of Einthoven DI lead recorded with the SW, where the SW was on the left wrist and the right index finger on the crown, and three Wilson-type leads, in the which the V1 was recorded in the fourth right parasternal intercostal space, V3 was recorded in the fifth intercostal space on the midclavicular line, and V6 was recorded in the fifth intercostal space on the left midaxillary line with the right index finger placed on the crown and the left hand encompassing the right wrist. 700 ECGs recordings were collected and statistically analyzed in this study. In total, 97 % of the patients were able to obtain an ECG through the SW. A strong correlation was observed between the two recording methods concerning the duration of the studied parameters (r >90 %). The correlation coefficient showed that 33 out of 44 parameters have a strong correlation with the standard ECG. The similarity of the combined leads in the 4 established subgroups was significantly higher, meaning that increasing the number of leads would improve the detection of electrical anomalies. Our findings confirm the existing data on the high similarity between SW and standard 12-leads ECG. Despite SW not having the accuracy and utility of the standard ECG machine, they should be considered as an interesting screening tool for cardiac rhythm disorders, and a compelling solution to electrical documentation of general cardiac symptoms.

Circadian-like patterns in electrochemical skin conductance measured from home-based devices: a retrospective study.

In this study, we investigated the potential of electrochemical skin conductance (ESC) measurements gathered from home-based devices to detect circadian-like patterns. We analyzed data from 43,284 individuals using the Withings Body Comp or Body Scan scales, which provide ESC measurements. Our results highlighted a circadian pattern of ESC values across different age groups and countries. Our findings suggest that home-based ESC measurements could be used to evaluate circadian rhythm disorders associated with neuropathies and contribute to a better understanding of their pathophysiology. However, further controlled studies are needed to confirm these results. This study highlights the potential of digital health devices to generate new scientific and medical knowledge.

Validation of the Withings BPM Core Device for Self-Blood Pressure Measurements in General Population According to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization Universal Standard.

Background: Most of the scientific societies recommend assessing the accuracy of electronic devices for blood pressure (BP) measurements using established validation protocol. Objective: To determine the accuracy of the BP measurements using the Withings BPM Core device in the general population according to the "Universal Standard (ISO 81060-2:2018/AMD 1:2020)". Methods: The Withings BPM Core is an oscillometric device measuring BP at the brachial level. The study was performed according to the "Universal Standard (ISO 81060-2:2018/AMD 1:2020) protocol" using the same-arm sequential BP measurement method. Subjects (n ≥ 85) fulfilling the age, gender, BP, and cuff distribution criteria of the protocol were included. Analysis was performed as required by the Universal protocol using Criterion 1 - differences between observers' mercury sphygmomanometer reference measurements and test device BP values (test versus reference) and their standard deviation (SD); and Criterion 2 - The SD of the mean BP differences between the test device and reference BP per subject. Results: Eighty-six subjects were selected, 85 of whom were included. The mean BP differences between the simultaneous two observers' measurements were -0.2 ± 2.1 mmHg for systolic BP (SBP) and 0.3 ± 2.1 mmHg for diastolic BP (DBP). For validation criterion 1, the mean difference ± SD between the reference and device BP values was -0.6 ± 4.8 mmHg for SBP and 0.1 ± 3.7 mmHg for DBP (≤5 ± 8 mmHg for both SBP and DBP). For criterion 2, the SD of the mean BP differences between the test device and reference BP per subject was 3.2/2.6 mmHg for SBP and DBP (≤6.91/6.95 mmHg). Conclusion: The results of this study showed that the Withings BPM Core oscillometric device for home BP measurement fulfilled the accuracy requirements of the (ISO 81060-2:2018/AMD 1:2020) Universal protocol in the general population.

Three Contactless Sleep Technologies Compared With Actigraphy and Polysomnography in a Heterogeneous Group of Older Men and Women in a Model of Mild Sleep Disturbance: Sleep Laboratory Study.

BACKGROUND: Contactless sleep technologies (CSTs) hold promise for longitudinal, unobtrusive sleep monitoring in the community and at scale. They may be particularly useful in older populations wherein sleep disturbance, which may be indicative of the deterioration of physical and mental health, is highly prevalent. However, few CSTs have been evaluated in older people. OBJECTIVE: This study evaluated the performance of 3 CSTs compared to polysomnography (PSG) and actigraphy in an older population. METHODS: Overall, 35 older men and women (age: mean 70.8, SD 4.9 y; women: n=14, 40%), several of whom had comorbidities, including sleep apnea, participated in the study. Sleep was recorded simultaneously using a bedside radar (Somnofy [Vital Things]: n=17), 2 undermattress devices (Withings sleep analyzer [WSA; Withings Inc]: n=35; Emfit-QS [Emfit; Emfit Ltd]: n=17), PSG (n=35), and actigraphy (Actiwatch Spectrum [Philips Respironics]: n=18) during the first night in a 10-hour time-in-bed protocol conducted in a sleep laboratory. The devices were evaluated through performance metrics for summary measures and epoch-by-epoch classification. PSG served as the gold standard. RESULTS: The protocol induced mild sleep disturbance with a mean sleep efficiency (SEFF) of 70.9% (SD 10.4%; range 52.27%-92.60%). All 3 CSTs overestimated the total sleep time (TST; bias: >90 min) and SEFF (bias: >13%) and underestimated wake after sleep onset (bias: >50 min). Sleep onset latency was accurately detected by the bedside radar (bias: <6 min) but overestimated by the undermattress devices (bias: >16 min). CSTs did not perform as well as actigraphy in estimating the all-night sleep summary measures. In an epoch-by-epoch concordance analysis, the bedside radar performed better in discriminating sleep versus wake (Matthew correlation coefficient [MCC]: mean 0.63, SD 0.12, 95% CI 0.57-0.69) than the undermattress devices (MCC of WSA: mean 0.41, SD 0.15, 95% CI 0.36-0.46; MCC of Emfit: mean 0.35, SD 0.16, 95% CI 0.26-0.43). The accuracy of identifying rapid eye movement and light sleep was poor across all CSTs, whereas deep sleep (ie, slow wave sleep) was predicted with moderate accuracy (MCC: >0.45) by both Somnofy and WSA. The deep sleep duration estimates of Somnofy correlated (r2=0.60; P<.01) with electroencephalography slow wave activity (0.75-4.5 Hz) derived from PSG, whereas for the undermattress devices, this correlation was not significant (WSA: r2=0.0096, P=.58; Emfit: r2=0.11, P=.21). CONCLUSIONS: These CSTs overestimated the TST, and sleep stage prediction was unsatisfactory in this group of older people in whom SEFF was relatively low. Although it was previously shown that CSTs provide useful information on bed occupancy, which may be useful for particular use cases, the performance of these CSTs with respect to the TST and sleep stage estimation requires improvement before they can serve as an alternative to PSG in estimating most sleep variables in older individuals.

Contactless and longitudinal monitoring of nocturnal sleep and daytime naps in older men and women: a digital health technology evaluation study.

STUDY OBJECTIVES: To compare the 24-hour sleep assessment capabilities of two contactless sleep technologies (CSTs) to actigraphy in community-dwelling older adults. METHODS: We collected 7-14 days of data at home from 35 older adults (age: 65-83), some with medical conditions, using Withings Sleep Analyser (WSA, n = 29), Emfit QS (Emfit, n = 17), a standard actigraphy device (Actiwatch Spectrum [AWS, n = 34]), and a sleep diary (n = 35). We compared nocturnal and daytime sleep measures estimated by the CSTs and actigraphy without sleep diary information (AWS-A) against sleep-diary-assisted actigraphy (AWS|SD). RESULTS: Compared to sleep diary, both CSTs accurately determined the timing of nocturnal sleep (intraclass correlation [ICC]: going to bed, getting out of bed, time in bed >0.75), whereas the accuracy of AWS-A was much lower. Compared to AWS|SD, the CSTs overestimated nocturnal total sleep time (WSA: +92.71 ± 81.16 minutes; Emfit: +101.47 ± 75.95 minutes) as did AWS-A (+46.95 ± 67.26 minutes). The CSTs overestimated sleep efficiency (WSA: +9.19% ± 14.26%; Emfit: +9.41% ± 11.05%), whereas AWS-A estimate (-2.38% ± 10.06%) was accurate. About 65% (n = 23) of participants reported daytime naps either in bed or elsewhere. About 90% in-bed nap periods were accurately determined by WSA while Emfit was less accurate. All three devices estimated 24-hour sleep duration with an error of ≈10% compared to the sleep diary. CONCLUSIONS: CSTs accurately capture the timing of in-bed nocturnal sleep periods without the need for sleep diary information. However, improvements are needed in assessing parameters such as total sleep time, sleep efficiency, and naps before these CSTs can be fully utilized in field settings.

Accuracy of the Withings BPM Connect Device for Self-Blood Pressure Measurements in General Population - Validation According to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization Universal Standard.

Background: As recommended by various authorities and scientific societies, electronic devices for blood pressure (BP) measurements must undergo independent clinical validations for accuracy assessment. Objective: To assess the accuracy of the Withings BPM Connect device in the general population according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization "AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018)". Methods: The Withings BPM Connect device measures BP at the brachial level using the oscillometric method. According to this protocol using the same-arm sequential BP measurement method, subjects (n ≥ 85) fulfilling the age, gender, BP and cuff distribution criteria must be included. Two criteria are used for the analysis: Criterion 1: differences between observers' mercury sphygmomanometer reference measurements and test device BP values (test versus reference) and their standard deviation (SD) must be ≤5 ± 8 mmHg for both systolic (SBP) and diastolic BP (DBP). Criterion 2: the SD of the mean BP differences between the test device and reference BP per subject must be ≤6.91/6.62 mmHg for SBP/DBP. Results: Ninety-two subjects were selected, 85 of whom were included. For validation criterion 1, the mean difference ± SD between the reference and device BP values was 0.6 ± 5.3 mmHg for SBP and 2.1 ± 4.3 mmHg for DBP. For criterion 2, the SD of the mean BP differences between the test device and reference BP per subject was 4.2/3.6 mmHg (SBP/DBP). These results fulfilled the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018) protocol requirements. Conclusion: The Withings BPM Connect oscillometric device for home BP measurement fulfilled all of the accuracy requirements of the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018) in general population and consequently can be recommended for home BP measurements.

Clinical Accuracy of the Withings BPM Connect for Self-Blood Pressure Measurements in Pregnancy and Pre-Eclampsia: Validation According to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization Universal Standard.

Background: Electronic devices for blood pressure (BP) measurements require independent clinical validation as recommended by various authorities/societies, both in general and special populations such as pregnancy. Objective: To assess the accuracy of the Withings BPM Connect device in pregnancy and pre-eclampsia according to the Universal Standard Validation Protocol. Methods: The Withings BPM Connect device measures BP at the brachial level using the oscillometric method. The study was performed according to the so-called "modified AAMI/ESH/ISO (ISO 81060-2:2018) protocol" or the "Universal Standard Protocol". The validation study included 45 pregnant women in the second and third gestational trimester: 15 with pre-eclampsia, 15 with gestational hypertension and 15 normotensives. Differences between mercury sphygmomanometer BP measurements (reference) and device BP values (test) and their standard deviation (SD) were calculated. Results: The mean differences between the mercury standard and device BP values in pregnancy (n = 45) were -0.5 ± 5.7 mmHg for systolic BP (SBP) and -0.8 ± 3.8 mmHg for diastolic BP (DBP). In the preeclamptic patients (n = 15), the mean differences were 0.14 ± 5.5 mmHg for SBP and 0.39 ± 3.7 mmHg for DBP. These results fulfilled the protocol requirements (<5 ± 8 mmHg). Conclusion: The Withings BPM Connect fulfills the validation protocol criteria in pregnancy and pre-eclampsia. Consequently, this device can be recommended for home BP measurements in this specific pregnancy population.

Importance of Getting Enough Sleep and Daily Activity Data to Assess Variability: Longitudinal Observational Study.

BACKGROUND: The gold standard measurement for recording sleep is polysomnography performed in a hospital environment for 1 night. This requires individuals to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. Self-trackers, such as wearable sensors (eg, smartwatch) and nearable sensors (eg, sleep mattress), can measure a broad range of physiological parameters related to free-living sleep conditions; however, the optimal duration of such a self-tracker measurement is not known. For such free-living sleep studies with actigraphy, 3 to 14 days of data collection are typically used. OBJECTIVE: The primary goal of this study is to investigate if 3 to 14 days of sleep data collection is sufficient while using self-trackers. The secondary goal is to investigate whether there is a relationship among sleep quality, physical activity, and heart rate. Specifically, we study whether individuals who exhibit similar activity can be clustered together and to what extent the sleep patterns of individuals in relation to seasonality vary. METHODS: Data on sleep, physical activity, and heart rate were collected over 6 months from 54 individuals aged 52 to 86 years. The Withings Aura sleep mattress (nearable; Withings Inc) and Withings Steel HR smartwatch (wearable; Withings Inc) were used. At the individual level, we investigated the consistency of various physical activities and sleep metrics over different time spans to illustrate how sensor data from self-trackers can be used to illuminate trends. We used exploratory data analysis and unsupervised machine learning at both the cohort and individual levels. RESULTS: Significant variability in standard metrics of sleep quality was found between different periods throughout the study. We showed specifically that to obtain more robust individual assessments of sleep and physical activity patterns through self-trackers, an evaluation period of >3 to 14 days is necessary. In addition, we found seasonal patterns in sleep data related to the changing of the clock for daylight saving time. CONCLUSIONS: We demonstrate that >2 months' worth of self-tracking data are needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3 to 14 days for sleep quality assessment and call for the rethinking of standards when collecting data for research purposes. Seasonal patterns and daylight saving time clock change are also important aspects that need to be taken into consideration when choosing a period for collecting data and designing studies on sleep. Furthermore, we suggest using self-trackers (wearable and nearable ones) to support longer-term evaluations of sleep and physical activity for research purposes and, possibly, clinical purposes in the future.

Associations of Physical Activity Level and Variability With 6-Month Weight Change Among 26,935 Users of Connected Devices: Observational Real-Life Study.

BACKGROUND: Physical activity (PA) is a modifiable lifestyle factor that can be targeted to increase energy expenditure and promote weight loss. However, the amount of PA required for weight loss remains inconsistent. Wearable activity trackers constitute a valuable opportunity to obtain objective measurements of PA and study large populations in real-life settings. OBJECTIVE: We aim to study the associations of initial device-assessed PA characteristics (average step counts and step count variability) and their evolution with 6-month weight change. METHODS: We analyzed data from 26,935 Withings-connected device users (wearable activity trackers and digital scales). To assess the initial PA characteristics and their 6-month changes, we used data recorded during the first and sixth 30-day periods of activity tracker use. For each of these periods, we used the monthly mean of daily step values as a proxy for PA level and derived the monthly coefficient of variation (CV) of daily step values to estimate PA level variability. Associations between initial PA characteristics and 6-month weight change were assessed using multivariable linear regression analyses controlled for age, sex, blood pressure, heart rate, and the predominant season. Restricted cubic spline regression was performed to better characterize the continuous shape of the associations between PA characteristics and weight change. Secondary analyses were performed by analyzing the 6-month evolution of PA characteristics in relation to weight change. RESULTS: Our results revealed that both a greater PA level and lower PA level variability were associated with weight loss. Compared with individuals who were initially in the sedentary category (<5000 steps/day), individuals who were low active (5000-7499 steps/day), somewhat active (7500-9999 steps/day), and active (≥10,000 steps/day) had a 0.21-kg, a 0.52-kg, and a 1.17-kg greater decrease in weight, respectively (95% CI -0.36 to -0.06, -0.70 to -0.33, and -1.42 to -0.93, respectively). Compared with users whose PA level CV was >63%, users whose PA level CV ranged from 51% to 63%, 40% to 51%, and was ≤40%, had a 0.19-kg, a 0.23-kg, and a 0.33-kg greater decrease in weight, respectively (95% CI -0.38 to -0.01, -0.41 to -0.04, and -0.53 to -0.13, respectively). We also observed that each 1000 steps/day increase in PA level over the 6-month follow-up was associated with a 0.26-kg (95% CI -0.29 to -0.23) decrease in weight. No association was found between the 6-month changes in PA level variability and weight change. CONCLUSIONS: Our results add to the current body of knowledge that health benefits can be observed below the 10,000 steps/day threshold and suggest that not only increased mean PA level but also greater regularity of the PA level may play important roles in short-term weight loss.

Validation of the Withings BP-800 in pregnancy and impact of maternal characteristics on the accuracy of blood pressure measurement.

OBJECTIVE: Firstly, to validate the Withings BP-800 automated device for use in pregnancy and, secondly, to assess the impact of maternal somatometric and demographic variables on the accuracy of the device. DESIGN: Prospective observational study. SETTING: Kings College Hospital, London, UK. POPULATION: Forty-seven women of any gestation. METHODS: Validation: The British Hypertension Society (BHS) Protocol (1993) was used for the validation of the Withings BP-800. Two trained observers took nine sequential same arm measurements alternating between the Withings BP-800 and the mercury sphygmomanometer. Assessment of factors affecting the disagreement between the two devices: The associations between discrepancies in the measured systolic and diastolic blood pressure by the two devices and potential predictors of discrepancy and/or possible confounders of associations including age, gestational age, ethnicity, body mass index and arm circumference were investigated using two-level mixed effects models to take into account the repeated measurements. MAIN OUTCOME MEASURES: Accuracy of the Withings BP-800 based on the grading criteria of the BHS Protocol (1993). RESULTS: The Withings BP-800 failed to meet the validation criteria of the BHS protocol for pregnancy and preeclampsia. Inter-device discrepancy was significantly associated with larger arm circumferences and was more pronounced with diastolic blood pressure. This relationship was independent of other maternal characteristics. CONCLUSIONS: The Withings BP-800 cannot be recommended for the measurement of blood pressure in pregnancy or preeclampsia. The inaccuracy of the Withings BP-800 increases when used in patients with larger arm circumferences with a propensity to over-read.

Validation of four devices: Omron M6 Comfort, Omron HEM-7420, Withings BP-800, and Polygreen KP-7670 for home blood pressure measurement according to the European Society of Hypertension International Protocol.

BACKGROUND: Four oscillometric devices, including the Omron M6 Comfort, Omron HEM-7420, Withings BP-800, and Polygreen KP-7670, designed for self-blood pressure measurement (SBPM) were evaluated according to the European Society of Hypertension (ESH) International Protocol Revision 2010 in four separate studies. METHODS: The four devices measure brachial blood pressure (BP) using the oscillometric method. The Withings BP-800 has to be connected to an Apple® iOS device such as an iPhone®, iPad®, or iPod®. The ESH International Protocol Revision 2010 includes a total number of 33 subjects. The difference between observer and device BP values was calculated for each measure. Ninety-nine pairs of BP differences were classified into three categories (≤5 mmHg, ≤10 mmHg, ≤15 mmHg). The protocol procedures were followed precisely in each of the four studies. RESULTS: All four tested devices passed the validation process. The mean differences between the device and mercury readings were: -1.8±5.1 mmHg and -0.4±2.8 mmHg for systolic and diastolic BP, respectively, using the Omron M6 Comfort device; 2.5±4.6 mmHg and -1.2±4.3 mmHg for the Omron HEM-7420 device; -0.2±5.0 mmHg and 0.4±4.2 mmHg for the Withings BP-800 device; and 3.0±5.3 mmHg and 0.3±5.2 mmHg for the Polygreen KP-7670 device. CONCLUSION: Omron M6 Comfort, Omron HEM-7420, Withings BP-800, and Polygreen KP-7670 readings differing by less than 5 mmHg, 10 mmHg, and 15 mmHg fulfill the ESH International Protocol Revision 2010 requirements, and therefore are suitable for use by patients for SBPM, if used correctly.