scholarly journals Cluster-Analysis-Based User-Adaptive Fall Detection Using Fusion of Heart Rate Sensor and Accelerometer in a Wearable Device

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 40389-40401
Author(s):  
Young-Hoon Nho ◽  
Jong Gwan Lim ◽  
Dong-Soo Kwon
Keyword(s):  
Heart Rate ◽  
Cluster Analysis ◽  
Fall Detection ◽  
Wearable Device ◽  
Rate Sensor

EMFi material as wearable heart rate sensor for night time recordings

2010 ◽  
Author(s):  
Antti Vehkaoja ◽  
Timo Salpavaara ◽  
Jarmo Verho ◽  
Jukka Lekkala
Keyword(s):  
Heart Rate ◽  
Night Time ◽  
Rate Sensor

A Low-Power Heart Rate Sensor with Adaptive Heartbeat Locked Loop

2021 ◽  
Author(s):  
Zhouchen Ma ◽  
Cheng Chen ◽  
Min Wang ◽  
Yang Zhao ◽  
Liang Ying ◽  
...  
Keyword(s):  
Heart Rate ◽  
Low Power ◽  
Rate Sensor

Wearable Sensors and Their Metrics for Measuring Comprehensive Occupational Fatigue: A Scoping Review

2017 ◽  
Vol 61 (1) ◽  
pp. 1041-1045 ◽  
Author(s):  
Yibo Zhu ◽  
Rasik R Jankay ◽  
Laura C Pieratt ◽  
Ranjana K. Mehta
Keyword(s):  
Heart Rate ◽  
Scoping Review ◽  
Wearable Sensors ◽  
Health And Safety ◽  
Exclusion Criteria ◽  
Multidimensional Construct ◽  
Ovid Medline ◽  
Rate Sensor ◽  
Sleep Length ◽  
Occupational Fatigue

Extensive research has been conducted to study the effects of physical and sleep related fatigue on occupational health and safety. However, fatigue is a complex multidimensional construct, that is task- and occupation-dependent, and our knowledge on how to measure this complex construct is limited. A scoping review was conducted to: 1) review sensors and their metrics currently employed in occupational fatigue studies, 2) identify overlap between sensors and associated metrics that can be leveraged to assess comprehensive fatigue, 3) investigating the effectiveness of the sensors/metrics, and 4) recommended potential sensor/metric combinations to evaluate comprehensive fatigue. 512 unique abstracts were identified through Ovid-MEDLINE, MEDLINE, Embase and Cinal databases and application of the inclusion/exclusion criteria resulted in 27 articles that were included for the review. Heart rate sensors and actigraphs were identified to be the most suitable devices to study comprehensive fatigue. Heart rate trend within the heart rate sensor, and sleep length and sleep efficiency within actigraphs were found to be the most popular and reliable metrics for measuring occupational fatigue.

scholarly journals 962 Heartlight - Delivery Room Acquisition Time for a Novel Forehead Heart Rate Sensor for Newborn Resuscitation

2010 ◽  
Vol 68 ◽  
pp. 480-480
Author(s):  
C Ward ◽  
J Teoh ◽  
M Grubb ◽  
J Crowe ◽  
B Hayes-Gill ◽  
...  
Keyword(s):  
Heart Rate ◽  
Delivery Room ◽  
Acquisition Time ◽  
Newborn Resuscitation ◽  
Rate Sensor

scholarly journals Microcontroller Based Portable Incubator Monitoring Tool with Short Message Service (SMS) notifications

2021 ◽  
Vol 2111 (1) ◽  
pp. 012026
Author(s):  
Muhammad Irmansyah ◽  
Efrizon ◽  
Anggara Nasution ◽  
Era Madona
Keyword(s):  
Heart Rate ◽  
Short Message Service ◽  
Average Error ◽  
Short Message ◽  
Monitoring Tool ◽  
Premature Babies ◽  
Pulse Sensor ◽  
Message Service ◽  
Rate Sensor ◽  
Weight Sensor

Abstract The aim of this research was applied a microcontroller, temperature sensor, weight sensor, heart rate sensor and GSM module to monitoring and notification of the condition of premature babies in portable incubators. The hardware used consists of a DS18B20 sensor, Load Cell, Pulse Heart Rate Sensor, Buzzer, LCD and SIM800L Module. The results showed the Pulse sensor and DS18B20 sensor could measure and detect the baby’s heart rate and baby temperature. The result was on the LCD with an average error of 4.354% for heartrate and 1.437% for temperature. The loadcell sensor can detect weight with an error of 2.16%. The duration of sending SMS to Smartphone is 8s for each delivery. SMS was sent if the baby weak and critical condition.

Data processing techniques of hydraulic bed sensor and doppler radar for elder care

2017 ◽  
Author(s):  
◽  
Bo-Yu Su
Keyword(s):  
Heart Rate ◽  
Doppler Radar ◽  
Detection Method ◽  
Blood Pressure Measurement ◽  
Fall Detection ◽  
The United States ◽  
Heart Beat ◽  
Body Motion ◽  
Sensor Data ◽  
Heart Rate Monitoring

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Population aging is a common phenomenon in a society. The developed country like the United States, eldercare is becoming an important issue nowadays. There are many aspects we need to address for eldercare, including - circulatory system, alimentary system, nervous system and so on. In this research study, we focus on the heart rate monitoring and estimation using a hydraulic bed sensor. In addition, we also develop the fall detection technique using a Doppler radar. The hydraulic bed sensor for heart rate monitoring is placed under the mattress. The sensor system contains four tubes filled with water and uses the pressure sensor to obtain the Ballistocardiogram (BCG) signal. The BCG signal contains the information of heart beat, respiratory rate and body motion. Two algorithms are developed to process the bed sensor data. One uses the Hilbert transform and the other is based on the energy. By using the algorithms we developed, we can extract the heart beat information to estimate the heart rate. The system has been validated in a well controlled lab environment and a nursing house. In addition to the heart rate, the relative blood pressure measurement by using two features extracted from the bed sensor signal has also been developed and validated with 48 people data. The results show high correlation coefficient with the groundtruth. The Doppler radar for human fall detection is mounted in the ceiling. The radar senses the motion of an object and produces outputs based on the Doppler shift effect. We propose an effective method based on Wavelet Transform (WT) for fall vs. nonfall classification. The proposed fall detection classi er can distinguish between the fall and daily activities. The good performance of the proposed detection method has been validated through the data from the lab and in-home environments, with the falls from stunt actors and senior residents. To further improve the performance, we introduce an additional radar mounted on the wall. Based on the same detection method as when using one radar, we extract and concatenate the features from two radars for classification. The result shows outstanding improvement.

Prediction of Menstrual Cycle Phase by Wearable Heart Rate Sensor

2021 ◽  
pp. 1-15
Author(s):  
Junichiro Hayano ◽  
Emi Yuda
Keyword(s):  
Heart Rate ◽  
Menstrual Cycle ◽  
Technological Development ◽  
Unmet Need ◽  
Cycle Phase ◽  
Rate Data ◽  
Menstrual Cycle Phase ◽  
Heart Rate Data ◽  
Rate Sensor

The prediction of the menstrual cycle phase and fertility window by easily measurable bio-signals is an unmet need and such technological development will greatly contribute to women's QoL. Although many studies have reported differences in autonomic indices of heart rate variability (HRV) between follicular and luteal phases, they have not yet reached the level that can predict the menstrual cycle phases. The recent development of wearable sensors-enabled heart rate monitoring during daily life. The long-term heart rate data obtained by them carry plenty of information, and the information that can be extracted by conventional HRV analysis is only a limited part of it. This chapter introduces comprehensive analyses of long-term heart rate data that may be useful for revealing their associations with the menstrual cycle phase.

scholarly journals Heart rate sensor validation and seasonal and diurnal variation of body temperature and heart rate in domestic sheep

2019 ◽  
Vol 8 ◽  
pp. 100075 ◽  
Author(s):  
Boris Fuchs ◽  
Kristin Marie Sørheim ◽  
Matteo Chincarini ◽  
Emma Brunberg ◽  
Solveig Marie Stubsjøen ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Temperature ◽  
Diurnal Variation ◽  
Domestic Sheep ◽  
Sensor Validation ◽  
Seasonal And Diurnal Variation ◽  
Rate Sensor

scholarly journals Automatic guidance systems in agricultural machinery as a tool for drivers’ mental strain and workload relief 

2017 ◽  
Vol 63 (Special Issue) ◽  
pp. S66-S72
Author(s):  
Kvíz Zděnek ◽  
Kroulík Milan
Keyword(s):  
Heart Rate ◽  
Soil Tillage ◽  
Steering Wheel ◽  
Special Device ◽  
Agricultural Machinery ◽  
Mental Strain ◽  
Significant Difference ◽  
Automatic Guidance ◽  
Guidance Systems ◽  
Rate Sensor

This article evaluates agricultural operator´s stress, mental strain and generally fighting with driving difficulties during operating agricultural machinery sets by means of a heart rate indicator. Different drivers driving different tractors with implements were chosen and evaluated during different field jobs, namely soil tillage and sowing. Machinery position on the field was precisely monitored by a GPS receiver and the heart beat rate was observed by means of a chest belt special device with a heart rate sensor. The output data from the sensors were monitored during conventional manual steering of the tractor-implement set and also when using the complete automatic guidance steering without any driver´s intervention to steering wheel – all by using the DGPS guidance signal. The data were further processed with a special software for the heart rate sensor and detailed statistical evaluation was performed. All described trials were measured at different farms in the Czech Republic. The final outcomes from the experiment showed a statistically significant difference between two experimental variants and confirm our hypothesis that the guidance systems bring a great benefit for drivers concerning mental strain and relief of their workload.

Objective evaluation of water-bed massage using heart rate sensor and accelerometer

2016 ◽  
Vol 52 (3-4) ◽  
pp. 927-934
Author(s):  
Akihito Seki ◽  
Changqin Quan ◽  
Zhiwei Luo ◽  
Tomoyuki Shimozono ◽  
Kazuaki Miyata
Keyword(s):  
Heart Rate ◽  
Objective Evaluation ◽  
Rate Sensor
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