scholarly journals Wearable Sensor System to Monitor Physical Activity and the Physiological Effects of Heat Exposure

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 855 ◽  
Author(s):  
Sean Pham ◽  
Danny Yeap ◽  
Gisela Escalera ◽  
Rupa Basu ◽  
Xiangmei Wu ◽  
...  
Keyword(s):  
Physical Activity ◽  
Environmental Conditions ◽  
Wearable Sensors ◽  
Heat Exposure ◽  
Extreme Heat ◽  
Mobile Systems ◽  
Physiological Data ◽  
Activity Levels ◽  
Integrated Sensor ◽  
Healthcare Facilities

Mobile health monitoring via non-invasive wearable sensors is poised to advance telehealth for older adults and other vulnerable populations. Extreme heat and other environmental conditions raise serious health challenges that warrant monitoring of real-time physiological data as people go about their normal activities. Mobile systems could be beneficial for many communities, including elite athletes, military special forces, and at-home geriatric monitoring. While some commercial monitors exist, they are bulky, require reconfiguration, and do not fit seamlessly as a simple wearable device. We designed, prototyped and tested an integrated sensor platform that records heart rate, oxygen saturation, physical activity levels, skin temperature, and galvanic skin response. The device uses a small microcontroller to integrate the measurements and store data directly on the device for up to 48+ h. continuously. The device was compared to clinical standards for calibration and performance benchmarking. We found that our system compared favorably with clinical measures, such as fingertip pulse oximetry and infrared thermometry, with high accuracy and correlation. Our novel platform would facilitate an individualized approach to care, particularly those whose access to healthcare facilities is limited. The platform also can be used as a research tool to study physiological responses to a variety of environmental conditions, such as extreme heat, and can be customized to incorporate new sensors to explore other lines of inquiry.

scholarly journals An empirical example of analysis using a two-stage modeling approach: within-subject association of outdoor context and physical activity predicts future daily physical activity levels

2020 ◽  
Author(s):  
Chih-Hsiang Yang ◽  
Jaclyn P Maher ◽  
Aditya Ponnada ◽  
Eldin Dzubur ◽  
Rachel Nordgren ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Wearable Sensors ◽  
Activity Levels ◽  
Two Stage ◽  
Modeling Approach ◽  
Source Program ◽  
Modeling Strategy ◽  
Stage Modeling

Abstract People differ from each other to the extent to which momentary factors, such as context, mood, and cognitions, influence momentary health behaviors. However, statistical models to date are limited in their ability to test whether the association between two momentary variables (i.e., subject-level slopes) predicts a subject-level outcome. This study demonstrates a novel two-stage statistical modeling strategy that is capable of testing whether subject-level slopes between two momentary variables predict subject-level outcomes. An empirical case study application is presented to examine whether there are differences in momentary moderate-to-vigorous physical activity (MVPA) levels between the outdoor and indoor context in adults and whether these momentary differences predict mean daily MVPA levels 6 months later. One hundred and eight adults from a multiwave longitudinal study provided 4 days of ecological momentary assessment (during baseline) and accelerometry data (both at baseline and 6 month follow-up). Multilevel data were analyzed using an open-source program (MixWILD) to test whether momentary strength between outdoor context and MVPA during baseline was associated with average daily MVPA levels measured 6 months later. During baseline, momentary MVPA levels were higher in outdoor contexts as compared to indoor contexts (b = 0.07, p < .001). Participants who had more momentary MVPA when outdoors (vs. indoors) during baseline (i.e., a greater subject-level slope) had higher daily MVPA at the 6 month follow-up (b = 0.09, p < .05). This empirical example shows that the subject-level momentary association between specific context (i.e., outdoors) and health behavior (i.e., physical activity) may contribute to overall engagement in that behavior in the future. The demonstrated two-stage modeling approach has extensive applications in behavioral medicine to analyze intensive longitudinal data collected from wearable sensors and mobile devices.

scholarly journals Innovation through Wearable Sensors to Collect Real-Life Data among Pediatric Patients with Cardiometabolic Risk Factors

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kestens Yan ◽  
Barnett Tracie ◽  
Mathieu Marie-Ève ◽  
Henderson Mélanie ◽  
Bigras Jean-Luc ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Heart Rate ◽  
Cardiometabolic Risk ◽  
Wearable Sensors ◽  
Real Life ◽  
Cardiometabolic Risk Factors ◽  
University Hospital ◽  
Activity Levels ◽  
Accelerometer Data

Background. While increasing evidence links environments to health behavior, clinicians lack information about patients’ physical activity levels and lifestyle environments. We present mobile health tools to collect and use spatio-behavioural lifestyle data for personalized physical activity plans in clinical settings.Methods. The Dyn@mo lifestyle intervention was developed at the Sainte-Justine University Hospital Center to promote physical activity and reduce sedentary time among children with cardiometabolic risk factors. Mobility, physical activity, and heart rate were measured in free-living environments during seven days. Algorithms processed data to generate spatio-behavioural indicators that fed a web-based interactive mapping application for personalised counseling. Proof of concept and tools are presented using data collected among the first 37 participants recruited in 2011.Results. Valid accelerometer data was available for 5.6 (SD=1.62) days in average, heart rate data for 6.5 days, and GPS data was available for 6.1 (2.1) days. Spatio-behavioural indicators were shared between patients, parents, and practitioners to support counseling.Conclusion. Use of wearable sensors along with data treatment algorithms and visualisation tools allow to better measure and describe real-life environments, mobility, physical activity, and physiological responses. Increased specificity in lifestyle interventions opens new avenues for remote patient monitoring and intervention.

scholarly journals Acceptability of Continuous Glucose Monitoring in Free-Living Healthy Individuals: Implications for the Use of Wearable Biosensors in Diet and Physical Activity Research (Preprint)

2018 ◽  
Author(s):  
Yue Liao ◽  
Susan Schembre
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Glucose Monitoring ◽  
Relevant Information ◽  
Sensor Technology ◽  
Physiological Data ◽  
Clinical Settings ◽  
Continuous Glucose Monitor ◽  
Diet And Physical Activity ◽  
Study Participants

BACKGROUND Wearable sensors have been increasingly used in behavioral research for real-time assessment and intervention purposes. The rapid advancement of biomedical technology typically used in clinical settings has made wearable sensors more accessible to a wider population. Yet the acceptability of this technology for nonclinical purposes has not been examined. OBJECTIVE The aim was to assess the acceptability of wearing a continuous glucose monitor (CGM) device among a sample of nondiabetic individuals, and to compare the acceptability of a CGM between a mobile diet tracking app (MyFitnessPal) and an accelerometer. METHODS A total of 30 nondiabetic adults went through a 7-day observational study. They wore a CGM sensor, tracked their diet and physical activity using the CGM receiver and MyFitnessPal, and wore an accelerometer on their waist. After the monitoring period, they completed a 10-item survey regarding acceptability of each of the study tools. Two-tailed paired-sample t tests were conducted to examine whether the summary acceptability scores were comparable between the CGM sensor/receiver and MyFitnessPal/accelerometer. RESULTS More than 90% of the study participants agreed that the CGM sensor and receiver were easy to use (28/30 and 27/30, respectively), useful (28/30 and 29/30, respectively), and provided relevant information that was of interest to them (27/30 and 28/30, respectively). The summary acceptability scores (out of a 5-point Likert scale) were mean 4.06 (SD 0.55) for the CGM sensor, mean 4.05 (SD 0.58) for the CGM receiver, mean 4.10 (SD 0.68) for MyFitnessPal, and mean 3.73 (SD 0.76) for the accelerometer. CONCLUSIONS The high acceptability of using a CGM from this study suggests a great potential for using CGMs in nondiabetic adults in research settings. Although potential selection bias might contribute to the high acceptability in this study, the continued advancements in wearable sensor technology will make the barriers to tracking and collecting personal physiological data more and more minimal.

scholarly journals Comfort Perception of Breathable and Nonbreathable Diapers

2005 ◽  
Vol os-14 (3) ◽  
pp. 1558925005os-14
Author(s):  
Audra Wright ◽  
Frank Akin
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Relative Humidity ◽  
Environmental Conditions ◽  
The Other ◽  
Activity Levels ◽  
Subjective Perceptions ◽  
Comfort Perception ◽  
External Conditions ◽  
Outer Cover

Breathable diapers were rated significantly drier, cooler and more comfortable than nonbreathable diapers over a range of controlled environmental conditions. Healthy, continent adults evaluated two types of diapers, one of which contained a microporous, breathable outer cover and the other a standard occlusive cover, in a series of blinded, comparison studies under various external conditions and activity levels. The subjects were capable of perceiving comfort or discomfort in the diaper area to a remarkable degree. Subjective perceptions of warmth and wetness underneath the diaper correlated with objective measurements of temperature and relative humidity (RH). Comfort ratings for the breathable diaper increased significantly over that of the nonbreathable garment as ambient temperature, RH and physical activity increased. Data analysis showed that the sensation of wetness in the diaper area was strongly associated with discomfort.

Step Count Validation of a Tri-Axial Accelerometer During Walking and Jogging

2012 ◽  
Author(s):  
Emma Fortune ◽  
Vipul Lugade ◽  
Melissa Morrow ◽  
Kenton Kaufman
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Living Environment ◽  
Activity Levels ◽  
Light Weight ◽  
Free Living ◽  
Step Counts ◽  
Step Counting ◽  
High Level ◽  
Very High

Gait analysis is an important tool in assessing the health and activity levels of patients and regular physical activity has been associated with health improvements in a number of populations. Step counting is one of the most commonly used measures of physical activity [1] and many studies have investigated the use of wearable sensors for step counts [2–4]. Their small size and light weight mean that they may be used in a free living environment and are suitable for home deployment. One of the main issues associated with step counts as a measure of physical activity is that a very high level of accuracy in step detection is needed.

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