Wearable sensor-based evaluation of psychosocial stress in patients with metabolic syndrome

Akbulut, Fatma Patlar; İkitimur, Barış; Akan, Aydın

doi:10.1016/j.artmed.2020.101824

Cited by 37 publications

(9 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using ozone inhalation as an example, we demonstrate the utility of such an approach to monitor the dynamics of stressor effects on human health that is amenable with currently available technologies. 65 This study assessed responses after exposure to only ozone. While we have shown similar changes in stress hormones and glucose after exposure to other gaseous irritant, acrolein, 51 this response may be linked to irritancy and should not be generalized to all pollutants and pollution mixtures.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers

Henriquez

Snow

House

et al. 2021

Preprint

View full text Add to dashboard Cite

Background. Stress-related neurobehavioral and metabolic disorders are associated with altered circulating adrenal-derived hormones and hyperglycemia. Temporal assessment of glucose and these hormones is critical for insights on an individuals health. Objectives. Here we use implantable-telemetry in rats to assess real-time changes in circulating glucose during and after exposure to the air pollutant ozone, and link responses to circulating neuroendocrine stress and metabolic hormones. We also proposed to compare rodent glucose and corticosterone (cortisol in humans) responses to humans exposed to ozone. Methods. First, using a cross-over design, we monitored glucose levels during single or repeated ozone exposures (0.0, 0.2, 0.4 and 0.8-ppm) and non-exposure periods in male Wistar-Kyoto-rats implanted with glucose-telemeters. A second cohort of un-implanted rats was exposed to ozone (0.0, 0.4 or 0.8-ppm) for 30-min, 1-hour, 2-hour, or 4-hour with hormones measured immediately after exposure. Then we assessed glucose metabolism in sham and adrenalectomized rats with or without pharmacological interventions of adrenergic and glucocorticoid receptors. Finally, we assessed glucose and cortisol in serum samples form a clinical study involving exposure of human volunteers to air or 0.3 ppm ozone. Results. Ozone (0.8-ppm) caused hyperglycemia and hypothermia beginning 90-min into exposure, with reversal of effects 4-6 hours post-exposure. Glucose monitoring during four daily 4-hour ozone exposures revealed duration of hyperglycemia, adaptation, and diurnal variations. Ozone-induced hyperglycemia was preceded by increased adrenocorticotropic hormone, corticosterone, and epinephrine, but depletion of thyroid-stimulating, prolactin, and luteinizing hormones. Hyperglycemia was inhibited in rats that are adrenalectomized and/or treated with glucocorticoid inhibitor. There was coherence among rats and humans in ozone-induced corticosterone/cortisol increases. Discussion. We demonstrate for the first time the temporality of neuroendocrine-stress-mediated biological sequalae responsible for ozone-induced metabolic dysfunction as exposure occurs. Real-time glucose monitoring with stress hormones assessment may be useful in identifying interactions among pollutants and stress-related illnesses.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Using ozone inhalation as an example, we here demonstrated the utility of such an approach to monitor the dynamics of stressor effects on health that is amenable in humans with currently available technologies. 55…”

Section: Discussionmentioning

confidence: 99%

Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers

Henriquez

Snow

House

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Non-adjustable parameters consist of sampling rates of 64 Hz for BVP, 4 Hz for EDA, 32 Hz for ACC, and 4 Hz for temperature signals. EDA and BVP signals are also considered to be associated with stress-related physiological signals [6] , [7] , [8] , [9] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Investigating the effects of stress on achievement: BIOSTRESS dataset

Çöpürkaya,

Meriç,

Erik

et al. 2023

Data in Brief

View full text Add to dashboard Cite

“…Today’s world benefits from automatic emotion recognition systems in different domains [ 6 ] such as patient care, medical diagnosis, education, video gaming, automotive assistance, recruiting personnel for companies, fraud detection for finance, etc.. For instance, emotion recognition systems can play a significant role in healthcare because the patient’s diagnosis and the recovery period can be understood and managed with higher accuracy [ 1 ]. In addition, it is utilized in tough follow-up processes of depression and anxiety patients [ 2 ]. Another effective utilization area is the evaluation of the student/lecturer interaction [ 31 ] during online education.…”

Section: Introductionmentioning

confidence: 99%

Analysis of facial emotion expression in eating occasions using deep learning

Yıldırım

Akbulut

Çatal

2023

Multimed Tools Appl

View full text Add to dashboard Cite

Eating is experienced as an emotional social activity in any culture. There are factors that influence the emotions felt during food consumption. The emotion felt while eating has a significant impact on our lives and affects different health conditions such as obesity. In addition, investigating the emotion during food consumption is considered a multidisciplinary problem ranging from neuroscience to anatomy. In this study, we focus on evaluating the emotional experience of different participants during eating activities and aim to analyze them automatically using deep learning models. We propose a facial expression-based prediction model to eliminate user bias in questionnaire-based assessment systems and to minimize false entries to the system. We measured the neural, behavioral, and physical manifestations of emotions with a mobile app and recognize emotional experiences from facial expressions. In this research, we used three different situations to test whether there could be any factor other than the food that could affect a person’s mood. We asked users to watch videos, listen to music or do nothing while eating. This way we found out that not only food but also external factors play a role in emotional change. We employed three Convolutional Neural Network (CNN) architectures, fine-tuned VGG16, and Deepface to recognize emotional responses during eating. The experimental results demonstrated that the fine-tuned VGG16 provides remarkable results with an overall accuracy of 77.68% for recognizing the four emotions. This system is an alternative to today’s survey-based restaurant and food evaluation systems.

show abstract

Wearable sensor-based evaluation of psychosocial stress in patients with metabolic syndrome

Cited by 37 publications

References 28 publications

Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers

Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers

Investigating the effects of stress on achievement: BIOSTRESS dataset

Analysis of facial emotion expression in eating occasions using deep learning

Contact Info

Product

Resources

About