Unconstrained Monitoring of Biological Signals Using an Aortic Pulse Wave Sensor

Hagiyama, Naoki; Mito, Akihisa; Hirano, Hirohiko; Soh, Zu; Fujita, Etsunori; Ogura, Yuichiro; Uchikawa, Ryuichi; Kaneko, Shigehiko; Nakamura, Ryuji; Saeki, Noboru; Kawamoto, Masashi; Yoshizumi, Masao; Tsuji, Toshio

doi:10.1109/embc.2018.8513291

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…This material acts as an oscillator with a centre frequency of approximately 20 Hz and, through the phenomenon of stochastic resonance, allows both the filtering of the acoustic signal around 20 Hz for the removal of artifacts and the maximum coupling of mechanical impedance between the subject’s trunk and the sensor. This technique allows to reduce to a minimum the number of undetected beats with consequent improvement of the reliability of the analysis [ 53 , 54 ].…”

Section: Methodsmentioning

confidence: 99%

“…The cardiac signal is filtered to eliminate the noise components due to respiration or movement artifacts: the information on the vibration due to the heartbeat is contained in signals around 20 Hz [ 53 , 54 ] which are therefore passband filtered from 10 to 30 Hz. In order for this signal to take on the wave form of the cardiac cycle (having a frequency close to 1 Hz), it is further passband filtered between 0.8 and 2 Hz ( Figure 1 ).…”

Section: Methodsmentioning

confidence: 99%

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On-Road Detection of Driver Fatigue and Drowsiness during Medium-Distance Journeys

Salvati

D’Amore

Fiorentino

et al. 2021

Entropy

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Background: The detection of driver fatigue as a cause of sleepiness is a key technology capable of preventing fatal accidents. This research uses a fatigue-related sleepiness detection algorithm based on the analysis of the pulse rate variability generated by the heartbeat and validates the proposed method by comparing it with an objective indicator of sleepiness (PERCLOS). Methods: changes in alert conditions affect the autonomic nervous system (ANS) and therefore heart rate variability (HRV), modulated in the form of a wave and monitored to detect long-term changes in the driver’s condition using real-time control. Results: the performance of the algorithm was evaluated through an experiment carried out in a road vehicle. In this experiment, data was recorded by three participants during different driving sessions and their conditions of fatigue and sleepiness were documented on both a subjective and objective basis. The validation of the results through PERCLOS showed a 63% adherence to the experimental findings. Conclusions: the present study confirms the possibility of continuously monitoring the driver’s status through the detection of the activation/deactivation states of the ANS based on HRV. The proposed method can help prevent accidents caused by drowsiness while driving.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

On-Road Detection of Driver Fatigue and Drowsiness during Medium-Distance Journeys

Salvati

D’Amore

Fiorentino

et al. 2021

Entropy

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“…It is widely used in wireless networking process which consumes only low power with more number of bandwidths can be formed in it. UWB remote sensing can also helps in detecting the problems arising in respiratory functions as well as the cardiac counts occurs.In [2] , This paper relates about the monitoring of signals by using the aortic blood vessesls to take out organic signals from arterial waves. The sensor is fixed near to the heart valve that detects the blocks or any other problem arises in the human body.…”

Section: Literature Surveymentioning

confidence: 99%

“…Dr. R. Puviarasi [2] ,Department of ECE, Saveetha school of engineering, Saveetha Institute of Medical and technical sciences…”

Section: Output Of Heart Beat Figure 8: Output Of Heart Valuementioning

confidence: 99%

Heart Rate Monitoring System using Pulse Sensor with Data Stored on Server

Vinodhini,

Puviarasi

2019

IJEAT

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This project is about Heart rate monitoring using pulse sensor in which the data is stored in the server for the later on use. The pulse sensor is connected to the server using Wi-Fi module (Node MCU) to track patients health . The data are sent to server using http protocol. It is like a small device which can be fixed to any atmosphere. It is a less bulky and a portable WiFi module and the person can be connected to their android mobile using Wi-Fi hot spot settings.

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Unconstrained Vital Sign Monitoring System Using an Aortic Pulse Wave Sensor

Hagiyama

Hirano

Mito

et al. 2019

Sci Rep

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This paper proposes a novel unconstrained monitoring system that measures heart and respiratory rates and evaluates autonomic nervous activity based on heart rate variability. The proposed system measures the aortic pulse waves (APWs) of a patient via an APW sensor that comprises a single microphone integrated into a mattress. Vital signs (i.e., heart rate, respiratory rate) and autonomic nervous activity were analyzed using the measured APWs. In an experiment with supine and seated participants, vital signs calculated by the proposed system were compared with vital signs measured with commercial devices, and we obtained the correlations of r > 0.8 for the heart rates, r > 0.7 for the respiratory rates, and r > 0.8 for the heart rate variability indices. These results indicate that the proposed system can produce accurate vital sign measurements. In addition, we performed the experiment of image stimulus presentation and explored the relationships between the self-reported psychological states evoked by the stimulus and the measured vital signs. The results indicated that vital signs reflect psychological states. In conclusion, the proposed system demonstrated its ability to monitor health conditions by actions as simple as sitting or lying on the APW sensor.

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Unconstrained Monitoring of Biological Signals Using an Aortic Pulse Wave Sensor

Cited by 7 publications

References 5 publications

On-Road Detection of Driver Fatigue and Drowsiness during Medium-Distance Journeys

On-Road Detection of Driver Fatigue and Drowsiness during Medium-Distance Journeys

Heart Rate Monitoring System using Pulse Sensor with Data Stored on Server

Unconstrained Vital Sign Monitoring System Using an Aortic Pulse Wave Sensor

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