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Body Temperature

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Improving energy expenditure estimates from wearable devices: A machine learning approach.

Journal of sports sciences
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...

Using Machine Learning to Train a Wearable Device for Measuring Students' Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use.

Sensors (Basel, Switzerland)
Automated tracking of physical fitness has sparked a health revolution by allowing individuals to track their own physical activity and health in real time. This concept is beginning to be applied to tracking of cognitive load. It is well known that ...

Predicting dairy cattle heat stress using machine learning techniques.

Journal of dairy science
The objectives of the study were to use a heat stress scoring system to evaluate the severity of heat stress on dairy cows using different heat abatement techniques. The scoring system ranged from 1 to 4, where 1 = no heat stress; 2 = mild heat stres...

An attempt at estrus detection in cattle by continuous measurements of ventral tail base surface temperature with supervised machine learning.

The Journal of reproduction and development
We aimed to determine the effectiveness of estrus detection based on continuous measurements of the ventral tail base surface temperature (ST) with supervised machine learning in cattle. ST data were obtained through 51 estrus cycles on 11 female cat...

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

Epilepsia
OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessm...

Evaluation of a wearable wireless device with artificial intelligence, iThermonitor WT705, for continuous temperature monitoring for patients in surgical wards: a prospective comparative study.

BMJ open
OBJECTIVES: To evaluate a new-generation, non-invasive, wireless axillary thermometer with artificial intelligence, iThermonitor (WT705, Raiing Medical, Beijing, China), and to ascertain its feasibility for perioperative continuous body temperature m...

Body Temperature-Triggered Mechanical Instabilities for High-Speed Soft Robots.

Soft robotics
Nature offers bionic inspirations for elegant applications of mechanical principles such as the concept of snap buckling, which occurs in several plants. Exploiting mechanical instabilities is the key to fast movement here. We use the snap-through an...

Digital electronics in fibres enable fabric-based machine-learning inference.

Nature communications
Digital devices are the essential building blocks of any modern electronic system. Fibres containing digital devices could enable fabrics with digital system capabilities for applications in physiological monitoring, human-computer interfaces, and on...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

International journal of medical informatics
BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive bacterial infection (IBI) in febrile infants compared to commonly used risk stratification criteria in recent studies. However, the black-box nature of ...