[HTML][HTML] Measurement, prediction, and control of individual heart rate responses to exercise—Basics and options for wearable devices
The use of wearable devices or “wearables” in the physical activity domain has been
increasing in the last years. These devices are used as training tools providing the user with …
increasing in the last years. These devices are used as training tools providing the user with …
[HTML][HTML] Heart rate modeling and prediction using autoregressive models and deep learning
Physiological time series are affected by many factors, making them highly nonlinear and
nonstationary. As a consequence, heart rate time series are often considered difficult to …
nonstationary. As a consequence, heart rate time series are often considered difficult to …
[HTML][HTML] Ambient intelligence systems for personalized sport training
J Vales-Alonso, P López-Matencio… - Sensors, 2010 - mdpi.com
Several research programs are tackling the use of Wireless Sensor Networks (WSN) at
specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project …
specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project …
Heart rate modeling and prediction of construction workers based on physical activity using deep learning
Construction projects require long working hours where workers are subjected to intensive
tasks such as hard manual labor, heavy weightlifting, and compulsive working postures …
tasks such as hard manual labor, heavy weightlifting, and compulsive working postures …
Heart rate prediction model based on physical activities using evolutionary neural network
F Xiao, Y Chen, M Yuchi, M Ding… - 2010 Fourth International …, 2010 - ieeexplore.ieee.org
Physical activity (PA) can influence heart rate (HR). But the relationship between HR and PA
is hard to describe. In our previous works, HR prediction models based on PA were …
is hard to describe. In our previous works, HR prediction models based on PA were …
Heart rate prediction based on cycling cadence using feedforward neural network
It is important to monitor heart rate during cycling. By monitoring heart rate during cycling,
cyclists can control the cycling session such as cycling cadence to determine the intensity of …
cyclists can control the cycling session such as cycling cadence to determine the intensity of …
[PDF][PDF] Classification of normal and pathological heart signal variability using machine learning techniques
The guide Heart rate signals provide valuable information for assessing the state of
autonomic nervous system that control functioning of heart. Heart rate variability analysis is …
autonomic nervous system that control functioning of heart. Heart rate variability analysis is …
Temporal Modeling of Instantaneous Interbeat Interval based on Physical Activity
Heartbeat serves as a vital sign of health, aiding the diagnosis of various health issues. The
autonomic nervous system (ANS) is responsible for regulating heartbeat, and physical …
autonomic nervous system (ANS) is responsible for regulating heartbeat, and physical …
The prediction and error correction of physiological sign during exercise using Bayesian combined predictor and naive Bayesian classifier
H Zhang, B Wen, J Liu, Y Zeng - IEEE Systems Journal, 2019 - ieeexplore.ieee.org
Physiological signs monitored by wearable devices can reflect human body burden and
exercise intensity. Due to the risk, avoidance of excessive intensity of exercise, energy …
exercise intensity. Due to the risk, avoidance of excessive intensity of exercise, energy …
A context-aware running route recommender learning from user histories using artificial neural networks
S Knoch, A Chapko, A Emrich… - … workshop on database …, 2012 - ieeexplore.ieee.org
So far, several websites exist where runners can request route information. Those systems
are rather complex and lack a mobile-specific design. Thus, we propose a mobile running …
are rather complex and lack a mobile-specific design. Thus, we propose a mobile running …