Influences of Sensor Placement Site and Subject Posture on Measurement of Respiratory Frequency Using Triaxial Accelerometers

Hughes, Stephen; Liu, Haipeng; Zheng, Dingchang

doi:10.3389/fphys.2020.00823

Cited by 16 publications

(21 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, when there was a signi cant difference in the test of homogeneity of variance for experimental data, the data were log10-transformed before statistical modeling. If there was still a signi cant difference in the homogeneity test of variance for log10transformed data, the data were analyzed by Scheirer-Ray-Hare test (Hughes et al 2020). The graphs were made by GraphPad Prism 7.0 software.…”

Section: Discussionmentioning

confidence: 99%

The Role of Estrogen Receptor β in PM2.5 Organic Extract-Induced Pulmonary Inflammation in Female and Male Mice

Guo

Feng

et al. 2022

Preprint

View full text Add to dashboard Cite

Automobile exhaust is one of the main sources of PM2.5 in urban areas, and traffic-originated PM2.5 organic extract (Po) can promote inflammation in different organs, especially in the lung. In addition, sex differences were reported in many inflammatory diseases, but the triggering factors of sex differences in inflammatory responses are still unclear. In this study, we investigated the effects of Po exposure on pulmonary inflammatory responses and evaluated the role of sex in this process. Mice were exposed to 100 µg/m3 Po for 12 weeks by an inhalation exposure system in a polycarbonate chamber. In Po-exposed mice, the lung histopathological analysis shown obvious inflammation, the cell numbers in bronchoalveolar lavage fluid (BALF) were significantly increased, and most inflammatory cytokines in BALF were upregulated. Factorial analysis of variance was carried out to investigate the interaction between sex and Po exposure in these effects. The results shown that the increase of inflammatory cell numbers and the fluctuation of cytokine levels (TNF-α, IL-5, and GRO/KC) in BALF induced by Po were significantly different between female and male mice. Notably, these differences were diminished while Po-exposed mice were injected with PHTPP, an ERβ antagonist (1 mg/kg, i.p.). We hypothesized that Po-induced inflammatory responses were different between female and male mice, and ERβ was involved in these processes. To our knowledge, this is the first investigation about the role of sex in Po-induced adverse effects. This study provided a theoretical basis for understanding the sex differences in the adverse effects of environmental pollutants.

show abstract

Section: Discussionmentioning

confidence: 99%

The Role of Estrogen Receptor β in PM2.5 Organic Extract-Induced Pulmonary Inflammation in Female and Male Mice

Guo

Feng

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Respiratory frequency ( f R, in Hz) is also often used as an indicator for the respiratory rate (Note RR = f R /60). [ 58 , 59 , 60 ] The normal RR for an adult human is 12–22 bpm. [ 61 ] The respiratory rate is very sensitive to a variety of physiological, psychological, and environmental stressors.…”

Section: Wearable Sensors For Remote Health Monitoringmentioning

confidence: 99%

“…[ 61 ] The respiratory rate is very sensitive to a variety of physiological, psychological, and environmental stressors. Measuring respiratory rate is of great importance as it is related to the human health status, [ 58 , 62 , 63 ] from physical activity to mental status. [ 64 , 65 , 66 ] The respiratory rate provides critical information for patients suffering from asthma, sleep apnea, Covid‐19, postoperative respiratory instability, sport science, etc.…”

Section: Wearable Sensors For Remote Health Monitoringmentioning

confidence: 99%

“…Despite not requiring any special instrument, the method is not considered reliable due to the bias and errors of the staff. [58,63,70,71] Besides, this method is not capable of continuous monitoring of respiratory rate. Electrical chest impedance, pneumotachograph, arterial blood sampling, diffusion capacity, and optoelectronic plethysmography are some other popular methods for respiratory measurement.…”

Section: Sensors For Measuring Respiratory Behaviormentioning

confidence: 99%

See 1 more Smart Citation

Wearable Sensors for Remote Health Monitoring: Potential Applications for Early Diagnosis of Covid‐19

Mirjalali

Peng

Fang³

et al. 2021

Adv Materials Technologies

View full text Add to dashboard Cite

Wearable sensors are emerging as a new technology to detect physiological and biochemical markers for remote health monitoring. By measuring vital signs such as respiratory rate, body temperature, and blood oxygen level, wearable sensors offer tremendous potential for the noninvasive and early diagnosis of numerous diseases such as Covid‐19. Over the past decade, significant progress has been made to develop wearable sensors with high sensitivity, accuracy, flexibility, and stretchability, bringing to reality a new paradigm of remote health monitoring. In this review paper, the latest advances in wearable sensor systems that can measure vital signs at an accuracy level matching those of point‐of‐care tests are presented. In particular, the focus of this review is placed on wearable sensors for measuring respiratory behavior, body temperature, and blood oxygen level, which are identified as the critical signals for diagnosing and monitoring Covid‐19. Various designs based on different materials and working mechanisms are summarized. This review is concluded by identifying the remaining challenges and future opportunities for this emerging field.

show abstract

“…Further, there was no instruction regarding how to perform the PAs during real-life data collection. Therefore, participants might have performed posture activities differently, influencing accelerometer data from different body locations (Hughes et al, 2020). For example, staying in a sitting position with legs crossed rather than legs straight can change the accelerometer values for the knee-positioned sensor.…”

Section: Individual Classification Modelsmentioning

confidence: 99%

Assessing the Transferability of Physical Activity Type Detection Models: Influence of Age Group Is Underappreciated

Allahbakhshi¹,

Röcke²,

Weibel³

2021

Front. Physiol.

View full text Add to dashboard Cite

Increasing the amount of physical activity (PA) in older adults that have shifted to a sedentary lifestyle is a determining factor in decreasing health and social costs. It is, therefore, imperative to develop objective methods that accurately detect daily PA types and provide detailed PA guidance for healthy aging. Most of the existing techniques have been applied in the younger generation or validated in the laboratory. To what extent, these methods are transferable to real-life and older adults are a question that this paper aims to answer. Sixty-three participants, including 33 younger and 30 older healthy adults, participated in our study. Each participant wore five devices mounted on the left and right hips, right knee, chest, and left pocket and collected accelerometer and GPS data in both semi-structured and real-life environments. Using this dataset, we developed machine-learning models to detect PA types walking, non-level walking, jogging/running, sitting, standing, and lying. Besides, we examined the accuracy of the models within-and between-age groups applying different scenarios and validation approaches. The within-age models showed convincing classification results. The findings indicate that due to age-related behavioral differences, there are more confusion errors between walking, non-level walking, and running in older adults’ results. Using semi-structured training data, the younger adults’ models outperformed older adults’ models. However, using real-life training data alone or in combination with semi-structured data generated better results for older adults who had high real-life data quality. Assessing the transferability of the models to older adults showed that the models trained with younger adults’ data were only weakly transferable. However, training the models with a combined dataset of both age groups led to reliable transferability of results to the data of the older subgroup. We show that age-related behavioral differences can alter the PA classification performance. We demonstrate that PA type detection models that rely on combined datasets of young and older adults are strongly transferable to real-life and older adults’ data. Our results yield significant time and cost savings for future PA studies by reducing the overall volume of training data required.

show abstract

Influences of Sensor Placement Site and Subject Posture on Measurement of Respiratory Frequency Using Triaxial Accelerometers

Cited by 16 publications

References 25 publications

The Role of Estrogen Receptor β in PM2.5 Organic Extract-Induced Pulmonary Inflammation in Female and Male Mice

The Role of Estrogen Receptor β in PM2.5 Organic Extract-Induced Pulmonary Inflammation in Female and Male Mice

Wearable Sensors for Remote Health Monitoring: Potential Applications for Early Diagnosis of Covid‐19

Assessing the Transferability of Physical Activity Type Detection Models: Influence of Age Group Is Underappreciated

Contact Info

Product

Resources

About