scholarly journals Human care system for heart-rate and human-movement trajectory in home and its application to detect mental disease

2012 ◽  
Author(s):  
Yutaka Hata ◽  
Seigo Kanazawa ◽  
Maki Endo ◽  
Naoki Tsuchiya ◽  
Hiroshi Nakajima
Keyword(s):  
Heart Rate ◽  
Mental Disease ◽  
Human Movement ◽  
Movement Trajectory ◽  
Human Care ◽  
Care System

Multi Human Movement Trajectory Extraction by Thermal Sensor

2014 ◽  
pp. 35-49
Author(s):  
Masato Kuki ◽  
Hiroshi Nakajima ◽  
Naoki Tsuchiya ◽  
Junichi Tanaka ◽  
Yutaka Hata
Keyword(s):  
Human Movement ◽  
Thermal Sensor ◽  
Movement Trajectory

scholarly journals Measuring of dependency between heart rate, respiratory rate and the human movement

2013 ◽  
Vol 46 (28) ◽  
pp. 292-297 ◽  
Author(s):  
M. Augustynek ◽  
D. Friedmannova ◽  
M. Cmielova
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Human Movement

Development of Stress Management System for Prevention of a Mental Disease using Smart Finger Plethysmogram Measurement

2014 ◽  
Vol 4 (2) ◽  
pp. 66-74
Author(s):  
Hidehiko Hayashi ◽  
Akinori Minazuki
Keyword(s):  
Heart Rate ◽  
Mental Disorders ◽  
Stress Management ◽  
Management System ◽  
Mental Disease ◽  
Modern Society ◽  
Daily Basis ◽  
The Unconscious ◽  
Risk Levels ◽  
Stress Levels

In this modern society, with its multitude of stressors that people encounter on a daily basis, a characteristic of mental disorders is that there is a risk of developing them at the unconscious level, and even if the patient were to detect the condition, they are difficult to treat. Furthermore, while there are tests that evaluate the level of stress, these tests still have many elements. Therefore, it is extremely important to be able to objectively assess ones stress levels, as well as to raise awareness of and pay attention to internal signals in order to control the level of risk, to create a mechanism which provides medical help. Thus, this study aims to visualize the internal signals through the heart rate which is affected by stress, develop a system to provide assistance in returning stress to normal levels, and assisting in helping patients manage their own risk levels.

Consideration of Stress Coping Support System for Prevention of Mental Disease Using Smart Heart Rate Monitor

2019 ◽  
pp. 31-45
Author(s):  
Hidehiko Hayashi ◽  
Akinori Minazuki
Keyword(s):  
Heart Rate ◽  
Support System ◽  
Industrial Revolution ◽  
Mental Disease ◽  
Modern Society ◽  
Stress Coping ◽  
Heart Rate Monitor ◽  
The Unconscious ◽  
Fourth Industrial Revolution ◽  
Number Of Patients

In recent years, there has been a significant increase in the number of patients suffering from mood disorders in Japan, reaching 1.041 million in 2008. In 2014, the number of patients reached 1.116 million, the highest number recorded in the past. In modern society with the fourth industrial revolution, with its multitude of stressors that we encounter on a daily life, a characteristic of mental disorders is that there is a risk to increase them at the unconscious level, and even if the patient were to detect the condition, they are difficult to treat. Therefore, in everyday life, it is desirable to always measure the stress and detect the early signature before they get worse. Thus, this study aims to develop stress coping support system using smart finger plethysmogram measurement, visualizing the internal signals through the heart rate which is affected by stress.

scholarly journals Making the Coupled Gaussian Process Dynamical Model Modular and Scalable with Variational Approximations

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 724 ◽  
Author(s):  
Dmytro Velychko ◽  
Benjamin Knopp ◽  
Dominik Endres
Keyword(s):  
Gaussian Process ◽  
Body Movement ◽  
Human Movement ◽  
Dynamical Model ◽  
Variational Approximation ◽  
Movement Trajectory ◽  
Training Time ◽  
Variational Approximations ◽  
Natural Movement ◽  
Gaussian Process Dynamical Model

We describe a sparse, variational posterior approximation to the Coupled Gaussian Process Dynamical Model (CGPDM), which is a latent space coupled dynamical model in discrete time. The purpose of the approximation is threefold: first, to reduce training time of the model; second, to enable modular re-use of learned dynamics; and, third, to store these learned dynamics compactly. Our target applications here are human movement primitive (MP) models, where an MP is a reusable spatiotemporal component, or “module” of a human full-body movement. Besides re-usability of learned MPs, compactness is crucial, to allow for the storage of a large library of movements. We first derive the variational approximation, illustrate it on toy data, test its predictions against a range of other MP models and finally compare movements produced by the model against human perceptual expectations. We show that the variational CGPDM outperforms several other MP models on movement trajectory prediction. Furthermore, human observers find its movements nearly indistinguishable from replays of natural movement recordings for a very compact parameterization of the approximation.

scholarly journals Heart Rate Methods Can Be Valid for Estimating Intensity Spectrums of Oxygen Uptake in Field Exercise

2021 ◽  
Vol 12 ◽  
Author(s):  
Jane Salier Eriksson ◽  
Karin S. E. Olsson ◽  
Hans Rosdahl ◽  
Peter Schantz
Keyword(s):  
Heart Rate ◽  
Oxygen Uptake ◽  
Human Movement ◽  
Large Individual ◽  
Regression Equations ◽  
Normal Cycle ◽  
Submaximal Work ◽  
And Performance ◽  
Ergometer Cycling ◽  
Field Exercise

PurposeQuantifying intensities of physical activities through measuring oxygen uptake (V̇O2) is of importance for understanding the relation between human movement, health and performance. This can in principle be estimated by the heart rate (HR) method, based on the linear relationship between HR and V̇O2 established in the laboratory. It needs, however, to be explored whether HR methods, based on HR-V̇O2 relationships determined in the laboratory, are valid for estimating spectrums of V̇O2 in field exercise. We hereby initiate such studies, and use cycle commuting as the form of exercise.MethodsTen male and ten female commuter cyclists underwent measurements of HR and V̇O2 while performing ergometer cycling in a laboratory and a normal cycle commute in the metropolitan area of Stockholm County, Sweden. Two models of individual HR-V̇O2 relationships were established in the laboratory through linear regression equations. Model 1 included three submaximal work rates, whereas model 2 also involved a maximal work rate. The HR-V̇O2 regression equations of the two models were then used to estimate V̇O2 at six positions of field HR: five means of quintiles and the mean of the whole commute. The estimations obtained were for both models compared with the measured V̇O2.ResultsThe measured quintile range during commuting cycling was about 45–80% of V̇O2max. Overall, there was a high resemblance between the estimated and measured V̇O2, without any significant absolute differences in either males or females (range of all differences: −0.03–0.20 L⋅min–1). Simultaneously, rather large individual differences were noted.ConclusionThe present HR methods are valid at group level for estimating V̇O2 of cycle commuting characterized by relatively wide spectrums of exercise intensities. To further the understanding of the external validity of the HR method, there is a need for studying other forms of field exercises.

scholarly journals Scaling of heart rate with breathing frequency and body mass in cetaceans

2021 ◽  
Vol 376 (1830) ◽  
pp. 20200223 ◽  
Author(s):  
Ashley M. Blawas ◽  
Douglas P. Nowacek ◽  
Julie Rocho-Levine ◽  
Todd R. Robeck ◽  
Andreas Fahlman
Keyword(s):  
Heart Rate ◽  
Body Mass ◽  
Marine Mammal ◽  
Metabolic Efficiency ◽  
Free Living ◽  
Cetacean Species ◽  
Sinus Arrhythmia ◽  
Human Care ◽  
Physical Laws ◽  
The Relationship

Plasticity in the cardiac function of a marine mammal facilitates rapid adjustments to the contrasting metabolic demands of breathing at the surface and diving during an extended apnea. By matching their heart rate ( f H ) to their immediate physiological needs, a marine mammal can improve its metabolic efficiency and maximize the proportion of time spent underwater. Respiratory sinus arrhythmia (RSA) is a known modulation of f H that is driven by respiration and has been suggested to increase cardiorespiratory efficiency. To investigate the presence of RSA in cetaceans and the relationship between f H , breathing rate ( f R ) and body mass ( M b ), we measured simultaneous f H and f R in five cetacean species in human care. We found that a higher f R was associated with a higher mean instantaneous f H (i f H ) and minimum i f H of the RSA. By contrast, f H scaled inversely with M b such that larger animals had lower mean and minimum i f H s of the RSA. There was a significant allometric relationship between maximum i f H of the RSA and M b , but not f R , which may indicate that this parameter is set by physical laws and not adjusted dynamically with physiological needs. RSA was significantly affected by f R and was greatly reduced with small increases in f R . Ultimately, these data show that surface f H s of cetaceans are complex and the f H patterns we observed are controlled by several factors. We suggest the importance of considering RSA when interpreting f H measurements and particularly how f R may drive f H changes that are important for efficient gas exchange. This article is part of the theme issue ‘Measuring physiology in free-living animals (Part I)’.

scholarly journals Can We Trust Inertial and Heart Rate Sensor Data from an APPLE Watch Device?

Proceedings ◽  
2020 ◽  
Vol 49 (1) ◽  
pp. 128
Author(s):  
Hugo G. Espinosa ◽  
David V. Thiel ◽  
Matthew Sorell ◽  
David Rowlands
Keyword(s):  
Heart Rate ◽  
Inertial Sensor ◽  
Pearson Correlation ◽  
Smart Phone ◽  
Human Movement ◽  
Stair Climbing ◽  
Sensor Data ◽  
Activity Monitors ◽  
Step Counting ◽  
Rate Sensor

The use of wearable technologies for the monitoring of human movement has increased considerably in the past few years, with applications to sports and other physical activities. Energy expenditure, walking and running distance, step count, and heart rate are some of the metrics provided by such devices via smart phone applications. Most of the research studies have involved validating the accuracy and reliability of the activity monitors by using the post-processed data from the device. The aim of this preliminary study was to determine if we can trust sensor data obtained from an Apple watch. This study evaluated the pre-processed data from the watch through step counting and heart rate measurements, and compared it with known validated devices (in-house 9DOF inertial sensor and Polar H10TM). Repeated activities (walking, jogging, and stair climbing) of varying duration and intensity were conducted by participants of varying age and body mass index (BMI). Pearson correlation (r > 0.95) and Bland–Altman statistical analyses were applied to the data to determine the level of agreement between the validated devices and the watch. The sensors from the Apple watch counted steps and measured heart rate with a minimum error and performed as expected.

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