scholarly journals Using Biometric Sensor Data to Monitor Cancer Patients During Radiotherapy: Protocol for the OncoWatch Feasibility Study

10.2196/26096 ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. e26096
Author(s):  
Cecilie Holländer-Mieritz ◽  
Ivan R Vogelius ◽  
Claus A Kristensen ◽  
Allan Green ◽  
Judith L Rindum ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Side Effects ◽  
Feasibility Study ◽  
Demographic Data ◽  
Home Monitoring ◽  
Sensor Data ◽  
Activity Levels ◽  
Objective Data ◽  
Biometric Data

Background Patients with head and neck cancer (HNC) experience severe side effects during radiotherapy (RT). Ongoing technological advances in wearable biometric sensors allow for the collection of objective data (eg, physical activity and heart rate), which might, in the future, help detect and counter side effects before they become severe. A smartwatch such as the Apple Watch allows for objective data monitoring outside the hospital with minimal effort from the patient. To determine whether such tools can be implemented in the oncological setting, feasibility studies are needed. Objective This protocol describes the design of the OncoWatch 1.0 feasibility study that assesses the adherence of patients with HNC to an Apple Watch during RT. Methods A prospective, single-cohort trial will be conducted at the Department of Oncology, Rigshospitalet (Copenhagen, Denmark). Patients aged ≥18 years intended for primary or postoperative curatively intended RT for HNC will be recruited. Consenting patients will be asked to wear an Apple Watch on the wrist during and until 2 weeks after RT. The study will include 10 patients. Data on adherence, data acquisition, and biometric data will be collected. Demographic data, objective toxicity scores, and hospitalizations will be documented. Results The primary outcome is to determine if it is feasible for the patients to wear a smartwatch continuously (minimum 12 hours/day) during RT. Furthermore, we will explore how the heart rate and physical activity change over the treatment course. Conclusions The study will assess the feasibility of using the Apple Watch for home monitoring of patients with HNC. Our findings may provide novel insights into the patient’s activity levels and variations in heart rate during the treatment course. The knowledge obtained from this study will be essential for further investigating how biometric data can be used as part of symptom monitoring for patients with HNC. Trial Registration ClinicalTrials.gov NCT04613232; https://clinicaltrials.gov/ct2/show/NCT04613232 International Registered Report Identifier (IRRID) PRR1-10.2196/26096

scholarly journals Using Biometric Sensor Data to Monitor Cancer Patients During Radiotherapy: Protocol for the OncoWatch Feasibility Study (Preprint)

2020 ◽  
Author(s):  
Cecilie Holländer-Mieritz ◽  
Ivan R Vogelius ◽  
Claus A Kristensen ◽  
Allan Green ◽  
Judith L Rindum ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Side Effects ◽  
Feasibility Study ◽  
Demographic Data ◽  
Home Monitoring ◽  
Sensor Data ◽  
Activity Levels ◽  
Objective Data ◽  
Biometric Data

BACKGROUND Patients with head and neck cancer (HNC) experience severe side effects during radiotherapy (RT). Ongoing technological advances in wearable biometric sensors allow for the collection of objective data (eg, physical activity and heart rate), which might, in the future, help detect and counter side effects before they become severe. A smartwatch such as the Apple Watch allows for objective data monitoring outside the hospital with minimal effort from the patient. To determine whether such tools can be implemented in the oncological setting, feasibility studies are needed. OBJECTIVE This protocol describes the design of the OncoWatch 1.0 feasibility study that assesses the adherence of patients with HNC to an Apple Watch during RT. METHODS A prospective, single-cohort trial will be conducted at the Department of Oncology, Rigshospitalet (Copenhagen, Denmark). Patients aged ≥18 years intended for primary or postoperative curatively intended RT for HNC will be recruited. Consenting patients will be asked to wear an Apple Watch on the wrist during and until 2 weeks after RT. The study will include 10 patients. Data on adherence, data acquisition, and biometric data will be collected. Demographic data, objective toxicity scores, and hospitalizations will be documented. RESULTS The primary outcome is to determine if it is feasible for the patients to wear a smartwatch continuously (minimum 12 hours/day) during RT. Furthermore, we will explore how the heart rate and physical activity change over the treatment course. CONCLUSIONS The study will assess the feasibility of using the Apple Watch for home monitoring of patients with HNC. Our findings may provide novel insights into the patient’s activity levels and variations in heart rate during the treatment course. The knowledge obtained from this study will be essential for further investigating how biometric data can be used as part of symptom monitoring for patients with HNC. CLINICALTRIAL ClinicalTrials.gov NCT04613232; https://clinicaltrials.gov/ct2/show/NCT04613232 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/26096

Maximal Oxygen Uptake and Daily Physical Activity in 7- to 12-Year-Old Boys

1993 ◽  
Vol 5 (4) ◽  
pp. 357-366 ◽  
Author(s):  
Hazzaa M. Al-Hazzaa ◽  
Mohammed A. Sulaiman
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Open Circuit ◽  
Daily Physical Activity ◽  
Activity Level ◽  
Activity Levels ◽  
School Time ◽  
The Relationship

The present study examined the relationship between maximal oxygen uptake (V̇O2max) and daily physical activity in a group of 7- to 12-year-old boys. V̇O2max was assessed through the incremental treadmill test using an open circuit system. Physical activity level was obtained from heart rate telemetry outside of school time for 8 hrs during weekdays and during 40 min of physical education classes. The findings indicated that the absolute value of V̇O2max increased with age, while relative to body weight it remained almost the same across age, with a mean of 48.4 ml · kg−1 · min−1. Moreover, heart rate telemetry showed that the boys spent a limited amount of time on activities that raise the heart rate to a level above 160 bpm (an average of 1.9%). In addition, V̇O2max was found to be significantly related to the percentage of time spent at activity levels at or above a heart rate of 140 bpm, but not with activity levels at or above a heart rate of 160 bpm.

Getting Enough Sleep: On the Importance of Collecting Longitudinal Data from Wearables to Assess Sleep Quality and Seasonal Effects on Variability in Daily Activity (Preprint)

2021 ◽  
Author(s):  
María Óskarsdóttir ◽  
Anna Sigridur Islind ◽  
Elias August ◽  
Erna Sif Arnardóttir ◽  
Francois Patou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Data Collection ◽  
Sleep Quality ◽  
Daily Activity ◽  
Hospital Environment ◽  
Sensor Data ◽  
Seasonal Patterns ◽  
Sleep Patterns ◽  
Sleep Habits

BACKGROUND The method considered the gold standard for recording sleep is a polysomnography, where the measurement is performed in a hospital environment for 1-3 nights. This requires subjects to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. For longer studies with actigraphy, 3-14 days of data collection is typically used for both clinical and research studies. OBJECTIVE The primary goal of this paper is to investigate if the aforementioned timespan is sufficient for data collection, when performing sleep measurements at home using wearable and non-wearable sensors. Specifically, whether 3-14 days of data collection sufficient to capture an individual’s sleep habits and fluctuations in sleep patterns in a reliable way for research purposes. Our secondary goals are to investigate whether there is a relationship between sleep quality, physical activity, and heart rate, and whether individuals who exhibit similar activity and sleep patterns in general and in relation to seasonality can be clustered together. METHODS Data on sleep, physical activity, and heart rate was collected over a period of 6 months from 54 individuals in Denmark aged 52-86 years. The Withings Aura sleep tracker (non-wearable) and Withings Steel HR smartwatch (wearable) 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. RESULTS Significant variability in standard metrics of sleep quality was found between different periods throughout the study. We show specifically that in order to get more robust individual assessment of sleep and physical activity patterns through wearable and non-wearable devices, a longer evaluation period than 3-14 days is necessary. Additionally, we found seasonal patterns in sleep data related to changing of the clock for Daylight Saving Time (DST). CONCLUSIONS We demonstrate that over two months worth of self-tracking data is needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3-14 days for sleep quality assessment and call for rethinking standards when collecting data for research purposes. Seasonal patterns and DST clock change are also important aspects that need to be taken into consideration, and designed for, when choosing a period for collecting data. Furthermore, we suggest using consumer-grade self-trackers (wearable and non-wearable ones) to support longer term evaluations of sleep and physical activity for research purposes and, possibly, clinical ones in the future.

scholarly journals Application and Validation of Activity Monitors’ Epoch Lengths and Placement Sites for Physical Activity Assessment in Exergaming

2018 ◽  
Vol 7 (9) ◽  
pp. 268 ◽  
Author(s):  
Jungyun Hwang ◽  
Austin Fernandez ◽  
Amy Lu
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Intraclass Correlation ◽  
Activity Levels ◽  
Physical Activity Intensity ◽  
Activity Monitors ◽  
Epoch Length ◽  
Activity Intensity ◽  
Physical Activity Levels ◽  
Rate Sensor

We assessed the agreement of two ActiGraph activity monitors (wGT3X vs. GT9X) placed at the hip and the wrist and determined an appropriate epoch length for physical activity levels in an exergaming setting. Forty-seven young adults played a 30-min exergame while wearing wGT3X and GT9X on both hip and wrist placement sites and a heart rate sensor below the chest. Intraclass correlation coefficient indicated that intermonitor agreement in steps and activity counts was excellent on the hip and good on the wrist. Bland-Altman plots indicated good intermonitor agreement in the steps and activity counts on both placement sites but a significant intermonitor difference was detected in steps on the wrist. Time spent in sedentary and physical activity intensity levels varied across six epoch lengths and depended on the placement sites, whereas time spent from a 1-s epoch of the hip-worn monitors most accurately matched the relative exercise intensity by heart rate. Hip placement site was associated with better step-counting accuracy for both activity monitors and more valid estimation of physical activity levels. A 1-s epoch was the most appropriate epoch length to detect short bursts of intense physical activity and may be the best choice for data processing and analysis in exergaming studies examining intermittent physical activities.

scholarly journals Home Monitoring in Glaucoma

2018 ◽  
Vol 12 (2) ◽  
pp. 102 ◽  
Author(s):  
Toby Boote ◽  
Andrew J Tatham ◽  
◽  
◽  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Heart Rate ◽  
Intraocular Pressure ◽  
New Technologies ◽  
Home Monitoring ◽  
Self Monitoring ◽  
Digital Devices ◽  
Wide Range ◽  
Efficacy Of Treatment

A wide range of relatively cheap, wearable digital devices are now available that enable self-monitoring of parameters such as heart rate, blood pressure, physical activity and sleep patterns. Although these devices are often marketed at healthy people, new technologies that permit home monitoring may also have the potential to improve the detection and management of chronic diseases including glaucoma. If patients were able to measure their intraocular pressure or perform perimetry at home, many more measurements could be obtained, with the potential to improve our ability to differentiate true change from test–retest variability. Home monitoring may also improve our ability to determine efficacy of treatment and enhance patient engagement.

scholarly journals Association of heart rate variability with regional difference in senility death ratio: ALLSTAR big data analysis

2019 ◽  
Vol 7 ◽  
pp. 205031211985225 ◽  
Author(s):  
Junichiro Hayano ◽  
Masaya Kisohara ◽  
Yutaka Yoshida ◽  
Hiroyuki Sakano ◽  
Emi Yuda
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Big Data ◽  
Regional Differences ◽  
Regional Difference ◽  
Elderly Person ◽  
Activity Level ◽  
Activity Levels ◽  
Physical Activity Levels

Objectives: Senility death is defined as natural death in the elderly who do not have a cause of death to be described otherwise and, if human life is finite, it may be one of the ultimate goals of medicine and healthcare. A recent survey in Japan reports that municipalities with a high senility death ratio have lower healthcare costs per late-elderly person. However, the causes of regional differences in senility death ratio and their biomedical determinants were unknown. In this study, we examined the relationships of the regional difference in senility death ratio with the regional differences in heart rate variability and physical activity. Methods: We compared the age-adjusted senility death ratio of all Japanese prefectures with the regional averages of heart rate variability and actigraphic physical activity obtained from a physiological big data of Allostatic State Mapping by Ambulatory ECG Repository (ALLSTAR). Results: The age-adjusted senility death ratio of 47 Japanese prefectures in 2015 ranged from 1.2% to 3.6% in men and from 3.5% to 7.8% in women. We compared these ratios with the age-adjusted indices of heart rate variability in 108,865 men and 136,536 women and of physical activity level in 16,661 men and 21,961 women. Heart rate variability indices and physical activity levels that are known to be associated with low mortality risk were higher in prefectures with higher senility death ratio. Conclusion: The regional senility death ratio in Japan may be associated with regional health status as reflected in heart rate variability and physical activity levels.

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