scholarly journals Physiologic Response to the COVID-19 Vaccine Measured Using Wearable Devices (Preprint)

2021 ◽  
Author(s):  
Alexander George Hajduczok ◽  
Kara Marie DiJoseph ◽  
Brinnae Bent ◽  
Audrey K Thorp ◽  
Jon B Mullholland ◽  
...  
Keyword(s):  
Heart Rate ◽  
Immune Response ◽  
Observational Study ◽  
Sleep Duration ◽  
Vaccine Dose ◽  
Wearable Devices ◽  
Initial Increase ◽  
Percent Change ◽  
Physiologic Response ◽  
Immune Biomarkers

BACKGROUND The Pfizer COVID-19 Vaccine employs a novel technology which utilizes messenger Ribonucleic Acid (mRNA) to deliver viral proteins to the host and elicit a protective immune response, but the short-term physiologic response to the vaccine has yet to be studied using wearable devices. OBJECTIVE Using wearable devices, we aim to characterize physiologic changes in response to COVID-19 vaccination in a small cohort of subjects. METHODS In this prospective observational study, physiologic data from 19 internal medicine residents at a single institution who received both doses of the Pfizer COVID-19 vaccine were collected using the WHOOP strap 3.0 to determine participant baseline resting heart rate (RHR), heart rate variability (HRV), respiratory rate (RR), and sleep duration. Primary outcomes included change from baseline in HRV, RHR, RR, and sleep duration. Percent change and standard deviation from baseline (defined as the 30 days of wear prior to vaccination) were calculated for six days after the first and second dose of the Pfizer COVID-19 for all participants who met inclusion and exclusion criteria. Symptom type, severity, and duration were reported as secondary outcomes. RESULTS In 19 individuals, mean age 28.8 (+/- 2.2), 53% female, percent change in HRV was decreased on day 1 (-13.44% +/- 13.62%) following administration of the first vaccine dose, and this response was blunted following dose 2 (-9.25% +/- 22.6%). RHR had a slight initial increase (+2.73% +/- 5.50%, +4.20% +/- 9.42%) after each dose and normalized after one day and RR showed no change compared to baseline after either vaccine dose. Sleep duration was increased up to 6 days post vaccine and peaked on day 3. Increased sleep duration prior to vaccine also demonstrated a more significant change in HRV compared to those who were sleep deprived (as determined by Pearson correlations). A more robust response in terms of symptom severity and duration was seen following dose 2. Arm soreness was the most reported symptom for both doses. CONCLUSIONS This represents the first observational study of the physiologic response in humans to any of the novel COVID-19 vaccines, as measured using wearable devices. We provide evidence that HRV decreases in response to both vaccine doses, with no consequent changes in RHR or RR. Sleep duration initially decreased following each dose and subsequently increased thereafter. Future studies with a larger cohort and comparison to other inflammatory and immune biomarkers, such as antibody response, will be needed to determine the true utility of this type of continuous wearable monitoring in regards to vaccine responses. Our data raises the possibility that increased sleep prior to vaccination may impact physiologic response, which could be used to track immune response to vaccination. CLINICALTRIAL NCT04304703: https://www.clinicaltrials.gov/ct2/show/NCT04304703

scholarly journals Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study (Preprint)

2018 ◽  
Author(s):  
Junqing Xie ◽  
Dong Wen ◽  
Lizhong Liang ◽  
Yuxi Jia ◽  
Li Gao ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Consumption ◽  
Sleep Duration ◽  
Measurement Accuracy ◽  
Health Indicators ◽  
Wearable Devices ◽  
Health Related ◽  
Fitness Tracking ◽  
Activity State ◽  
Fitness Trackers

BACKGROUND Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. OBJECTIVE The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. METHODS A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). RESULTS Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under the resting state (MAPE of 0.04), whereas Dongdong performed the best for the measurement of the number of steps under the walking state (MAPE of 0.01). Fitbit Surge performed the best for distance measurement under the cycling state (MAPE of 0.04), and Huawei Talk Band B3 performed the best for energy consumption measurement under the walking state (MAPE of 0.17). CONCLUSIONS At present, mainstream devices are able to reliably measure heart rate, number of steps, distance, and sleep duration, which can be used as effective health evaluation indicators, but the measurement accuracy of energy consumption is still inadequate. Fitness trackers of different brands vary with regard to measurement of indicators and are all affected by the activity state, which indicates that manufacturers of fitness trackers need to improve their algorithms for different activity states.

scholarly journals Physiologic Response to the Pfizer-BioNTech COVID-19 Vaccine Measured Using Wearable Devices: A Prospective Observational Study (Preprint)

10.2196/28568 ◽  
2021 ◽  
Author(s):  
Alexander G Hajduczok ◽  
Kara M DiJoseph ◽  
Brinnae Bent ◽  
Audrey K Thorp ◽  
Jon B Mullholand ◽  
...  
Keyword(s):  
Observational Study ◽  
Prospective Observational Study ◽  
Wearable Devices ◽  
Physiologic Response

scholarly journals Exercise Intensity during Olympic-Distance Triathlon in Well-Trained Age-Group Athletes: An Observational Study

Sports ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 18
Author(s):  
Atsushi Aoyagi ◽  
Keisuke Ishikura ◽  
Yoshiharu Nabekura
Keyword(s):  
Heart Rate ◽  
Observational Study ◽  
Exercise Intensity ◽  
Time Range ◽  
Age Group ◽  
Slow Group ◽  
H 41 ◽  
The Mean ◽  
Aerobic And Anaerobic ◽  
Very High

The aim of this study was to examine the exercise intensity during the swimming, cycling, and running legs of nondraft legal, Olympic-distance triathlons in well-trained, age-group triathletes. Seventeen male triathletes completed incremental swimming, cycling, and running tests to exhaustion. Heart rate (HR) and workload corresponding to aerobic and anaerobic thresholds, maximal workloads, and maximal HR (HRmax) in each exercise mode were analyzed. HR and workload were monitored throughout the race. The intensity distributions in three HR zones for each discipline and five workload zones in cycling and running were quantified. The subjects were then assigned to a fast or slow group based on the total race time (range, 2 h 07 min–2 h 41 min). The mean percentages of HRmax in the swimming, cycling, and running legs were 89.8% ± 3.7%, 91.1% ± 4.4%, and 90.7% ± 5.1%, respectively, for all participants. The mean percentage of HRmax and intensity distributions during the swimming and cycling legs were similar between groups. In the running leg, the faster group spent relatively more time above HR at anaerobic threshold (AnT) and between workload at AnT and maximal workload. In conclusion, well-trained male triathletes performed at very high intensity throughout a nondraft legal, Olympic-distance triathlon race, and sustaining higher intensity during running might play a role in the success of these athletes.

scholarly journals Wearable Technologies in Field Hockey Competitions: A Scoping Review

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5242
Author(s):  
Jolene Ziyuan Lim ◽  
Alexiaa Sim ◽  
Pui Wah Kong
Keyword(s):  
Heart Rate ◽  
Inertial Sensors ◽  
Wearable Devices ◽  
Field Hockey ◽  
Heart Rate Monitors ◽  
Search Terms ◽  
Physiological Demands ◽  
And Performance ◽  
Future Work ◽  
Skin Temperatures

The aim of this review is to investigate the common wearable devices currently used in field hockey competitions, and to understand the hockey-specific parameters these devices measure. A systematic search was conducted by using three electronic databases and search terms that included field hockey, wearables, accelerometers, inertial sensors, global positioning system (GPS), heart rate monitors, load, performance analysis, player activity profiles, and competitions from the earliest record. The review included 39 studies that used wearable devices during competitions. GPS units were found to be the most common wearable in elite field hockey competitions, followed by heart rate monitors. Wearables in field hockey are mostly used to measure player activity profiles and physiological demands. Inconsistencies in sampling rates and performance bands make comparisons between studies challenging. Nonetheless, this review demonstrated that wearable devices are being used for various applications in field hockey. Researchers, engineers, coaches, and sport scientists can consider using GPS units of higher sampling rates, as well as including additional variables such as skin temperatures and injury associations, to provide a more thorough evaluation of players’ physical and physiological performances. Future work should include goalkeepers and non-elite players who are less studied in the current literature.

scholarly journals Later sleep timing predicts accelerated summer weight gain among elementary school children: a prospective observational study

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jennette P. Moreno ◽  
Javad Razjouyan ◽  
Houston Lester ◽  
Hafza Dadabhoy ◽  
Mona Amirmazaheri ◽  
...  
Keyword(s):  
Physical Activity ◽  
Observational Study ◽  
Sleep Duration ◽  
Obesity Prevention ◽  
Prospective Observational Study ◽  
Light Exposure ◽  
Activity Level ◽  
Activity Levels ◽  
School Year ◽  
Children’S Sleep

Abstract Objectives and background Social demands of the school-year and summer environment may affect children’s sleep patterns and circadian rhythms during these periods. The current study examined differences in children’s sleep and circadian-related behaviors during the school-year and summer and explored the association between sleep and circadian parameters and change in body mass index (BMI) during these time periods. Methods This was a prospective observational study with 119 children ages 5 to 8 years with three sequential BMI assessments: early school-year (fall), late school-year (spring), and beginning of the following school-year in Houston, Texas, USA. Sleep midpoint, sleep duration, variability of sleep midpoint, physical activity, and light exposure were estimated using wrist-worn accelerometry during the school-year (fall) and summer. To examine the effect of sleep parameters, physical activity level, and light exposure on change in BMI, growth curve modeling was conducted controlling for age, race, sex, and chronotype. Results Children’s sleep midpoint shifted later by an average of 1.5 h during summer compared to the school-year. After controlling for covariates, later sleep midpoints predicted larger increases in BMI during summer, (γ = .0004, p = .03), but not during the school-year. Sleep duration, sleep midpoint variability, physical activity levels, and sedentary behavior were not associated with change in BMI during the school-year or summer. Females tended to increase their BMI at a faster rate during summer compared to males, γ = .06, p = .049. Greater amounts of outdoor light exposure (γ = −.01, p = .02) predicted smaller increases in school-year BMI. Conclusions Obesity prevention interventions may need to target different behaviors depending on whether children are in or out of school. Promotion of outdoor time during the school-year and earlier sleep times during the summer may be effective obesity prevention strategies during these respective times.

scholarly journals Transversal gene expression panel to evaluate intestinal health in broiler chickens in different challenging conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
L. Criado-Mesas ◽  
N. Abdelli ◽  
A. Noce ◽  
M. Farré ◽  
J. F. Pérez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Barrier Function ◽  
Nutrient Transport ◽  
Gene Expression Pattern ◽  
Vaccine Dose ◽  
Special Focus ◽  
Intestinal Health ◽  
Barrier Failure ◽  
Expression Of Genes

AbstractThere is a high interest on gut health in poultry with special focus on consequences of the intestinal diseases, such as coccidiosis and C. perfringens-induced necrotic enteritis (NE). We developed a custom gene expression panel, which could provide a snapshot of gene expression variation under challenging conditions. Ileum gene expression studies were performed through high throughput reverse transcription quantitative real-time polymerase chain reaction. A deep review on the bibliography was done and genes related to intestinal health were selected for barrier function, immune response, oxidation, digestive hormones, nutrient transport, and metabolism. The panel was firstly tested by using a nutritional/Clostridium perfringens model of intestinal barrier failure (induced using commercial reused litter and wheat-based diets without exogenous supplementation of enzymes) and the consistency of results was evaluated by another experiment under a coccidiosis challenge (orally gavaged with a commercial coccidiosis vaccine, 90× vaccine dose). Growth traits and intestinal morphological analysis were performed to check the gut barrier failure occurrence. Results of ileum gene expression showed a higher expression in genes involved in barrier function and nutrient transport in chickens raised in healthy conditions, while genes involved in immune response presented higher expression in C.perfringens-challenged birds. On the other hand, the Eimeria challenge also altered the expression of genes related to barrier function and metabolism, and increased the expression of genes related to immune response and oxidative stress. The panel developed in the current study gives us an overview of genes and pathways involved in broiler response to pathogen challenge. It also allows us to deep into the study of differences in gene expression pattern and magnitude of responses under either a coccidial vaccine or a NE.

scholarly journals 651 Longitudinal, unobtrusive, and ecologically valid sleep metric estimation from a smart bed to predict the pathology of COVID-19

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A255-A255
Author(s):  
Dmytro Guzenko ◽  
Gary Garcia ◽  
Farzad Siyahjani ◽  
Kevin Monette ◽  
Susan DeFranco ◽  
...  
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Predictive Model ◽  
Sleep Duration ◽  
Wearable Sensors ◽  
Test Results ◽  
Cloud Data ◽  
Cardiorespiratory Function ◽  
Group Data ◽  
Rich Information

Abstract Introduction Pathophysiologic responses to viral respiratory challenges such as SARS-CoV-2 may affect sleep duration, quality and concomitant cardiorespiratory function. Unobtrusive and ecologically valid methods to monitor longitudinal sleep metrics may therefore have practical value for surveillance and monitoring of infectious illnesses. We leveraged sleep metrics from Sleep Number 360 smart bed users to build a COVID-19 predictive model. Methods An IRB approved survey was presented to opting-in users from August to November 2020. COVID-19 test results were reported by 2003/6878 respondents (116 positive; 1887 negative). From the positive group, data from 82 responders (44.7±11.3 yrs.) who reported the date of symptom onset were used. From the negative group, data from 1519 responders (48.4±12.9 yrs.) who reported testing dates were used. Sleep duration, sleep quality, restful sleep duration, time to fall asleep, respiration rate, heart rate, and motion level were obtained from ballistocardiography signals stored in the cloud. Data from January to October 2020 were considered. The predictive model consists of two levels: 1) the daily probability of staying healthy calculated by logistic regression and 2) a continuous density Hidden Markov Model to refine the daily prediction considering the past decision history. Results With respect to their baseline, significant increases in sleep duration, average breathing rate, average heart rate and decrease in sleep quality were associated with symptom exacerbation in COVID-19 positive respondents. In COVID-19 negative respondents, no significant sleep or cardiorespiratory metrics were observed. Evaluation of the predictive model resulted in cross-validated area under the receiving-operator curve (AUC) estimate of 0.84±0.09 which is similar to values reported for wearable-sensors. Considering additional days to confirm prediction improved the AUC estimate to 0.93±0.05. Conclusion The results obtained on the smart bed user population suggest that unobtrusive sleep metrics may offer rich information to predict and track the development of symptoms in individuals infected with COVID-19. Support (if any):

scholarly journals Sleep Indices and Cardiac Autonomic Activity Responses during an International Tournament in a Youth National Soccer Team

2021 ◽  
Vol 18 (4) ◽  
pp. 2076
Author(s):  
Pedro Figueiredo ◽  
Júlio Costa ◽  
Michele Lastella ◽  
João Morais ◽  
João Brito
Keyword(s):  
Heart Rate ◽  
Frequency Domain ◽  
Sleep Duration ◽  
Time Domain ◽  
Soccer Players ◽  
Autonomic Activity ◽  
Male Youth ◽  
Youth Soccer ◽  
Wrist Actigraphy ◽  
Cardiac Autonomic Activity

This study aimed to describe habitual sleep and nocturnal cardiac autonomic activity (CAA), and their relationship with training/match load in male youth soccer players during an international tournament. Eighteen elite male youth soccer players (aged 14.8 ± 0.3 years; mean ± SD) participated in the study. Sleep indices were measured using wrist actigraphy, and heart rate (HR) monitors were used to measure CAA during night-sleep throughout 5 consecutive days. Training and match loads were characterized using the session-rating of perceived exertion (s-RPE). During the five nights 8 to 17 players slept less than <8 h and only one to two players had a sleep efficiency <75%. Players’ sleep duration coefficient of variation (CV) ranged between 4 and 17%. Nocturnal heart rate variability (HRV) indices for the time-domain analyses ranged from 3.8 (95% confidence interval, 3.6; 4.0) to 4.1 ln[ms] (3.9; 4.3) and for the frequency-domain analyses ranged from 5.9 (5.6; 6.5) to 6.6 (6.3; 7.4). Time-domain HRV CV ranged from 3 to 10% and frequency-domain HRV ranged from 2 to 12%. A moderate within-subjects correlation was found between s-RPE and sleep duration [r = −0.41 (−0.62; −0.14); p = 0.003]. The present findings suggest that youth soccer players slept less than the recommended during the international tournament, and sleep duration was negatively associated with training/match load.

scholarly journals Development of SARS-CoV-2 Specific IgG and Virus-Neutralizing Antibodies after Infection with Variants of Concern or Vaccination

Vaccines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 700
Author(s):  
Franziska Neumann ◽  
Ruben Rose ◽  
Janine Römpke ◽  
Olaf Grobe ◽  
Thomas Lorentz ◽  
...  
Keyword(s):  
Immune Response ◽  
Receptor Binding ◽  
Neutralizing Antibodies ◽  
Neutralization Test ◽  
Vaccine Dose ◽  
High Avidity ◽  
Receptor Binding Domain ◽  
Robust Immune Response ◽  
Specific Igg ◽  
Nucleoprotein N

The humoral immunity after SARS-CoV-2 infection or vaccination was examined. Convalescent sera after infection with variants of concern (VOCs: B.1.1.7, n = 10; B.1.351, n = 1) and sera from 100 vaccinees (Pfizer/BioNTech, BNT162b2, n = 33; Moderna, mRNA-1273, n = 11; AstraZeneca, ChAdOx1 nCoV-19/AZD1222, n = 56) were tested for the presence of immunoglobulin G (IgG) directed against the viral spike (S)-protein, its receptor-binding domain (RBD), the nucleoprotein (N) and for virus-neutralizing antibodies (VNA). For the latter, surrogate assays (sVNT) and a Vero-cell based neutralization test (cVNT) were used. Maturity of IgG was determined by measuring the avidity in an immunoblot (IB). Past VOC infection resulted in a broad reactivity of anti-S IgG (100%), anti-RBD IgG (100%), and anti-N IgG (91%), while latter were absent in 99% of vaccinees. Starting approximately two weeks after the first vaccine dose, anti-S IgG (75–100%) and particularly anti-RBD IgG (98–100%) were detectable. After the second dose, their titers increased and were higher than in the convalescents. The sVNT showed evidence of VNA in 91% of convalescents and in 80–100%/100% after first/second vaccine dose, respectively. After the second dose, an increase in VNA titer and IgGs of high avidity were demonstrated by cVNT and IB, respectively. Re-vaccination contributes to a more robust immune response.

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