scholarly journals MEMS-Based Pulse Wave Sensor Utilizing a Piezoresistive Cantilever

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1052 ◽  
Author(s):  
Thanh-Vinh Nguyen ◽  
Yuya Mizuki ◽  
Takuya Tsukagoshi ◽  
Tomoyuki Takahata ◽  
Masaaki Ichiki ◽  
...  
Keyword(s):  
Microelectromechanical Systems ◽  
Pulse Wave ◽  
Blood Pressure Measurement ◽  
Pressure Change ◽  
Chamber Pressure ◽  
Breath Holding ◽  
Wave Measurement ◽  
Air Chamber ◽  
Pulse Waves ◽  
The Subject

This paper reports on a microelectromechanical systems (MEMS)-based sensor for pulse wave measurement. The sensor consists of an air chamber with a thin membrane and a 300-nm thick piezoresistive cantilever placed inside the chamber. When the membrane of the chamber is in contact with the skin above a vessel of a subject, the pulse wave of the subject causes the membrane to deform, leading to a change in the chamber pressure. This pressure change results in bending of the cantilever and change in the resistance of the cantilever, hence the pulse wave of the subject can be measured by monitoring the resistance of the cantilever. In this paper, we report the sensor design and fabrication, and demonstrate the measurement of the pulse wave using the fabricated sensor. Finally, measurement of the pulse wave velocity (PWV) is demonstrated by simultaneously measuring pulse waves at two points using the two fabricated sensor devices. Furthermore, the effect of breath holding on PWV is investigated. We showed that the proposed sensor can be used to continuously measure the PWV for each pulse, which indicates the possibility of using the sensor for continuous blood pressure measurement.

scholarly journals Mask-Type Sensor for Pulse Wave and Respiration Measurements and Eye Blink Detection

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4895
Author(s):  
Thanh-Vinh Nguyen ◽  
Masaaki Ichiki
Keyword(s):  
Pulse Wave ◽  
Pressure Change ◽  
Frequency Component ◽  
High Frequency Component ◽  
Sensing Element ◽  
Eye Blink ◽  
Mask Type ◽  
Blink Detection ◽  
The Subject ◽  
Air Bag

This paper reports on a mask-type sensor for simultaneous pulse wave and respiration measurements and eye blink detection that uses only one sensing element. In the proposed sensor, a flexible air bag-shaped chamber whose inner pressure change can be measured by a microelectromechanical system-based piezoresistive cantilever was used as the sensing element. The air bag-shaped chamber is fabricated by wrapping a sponge pad with plastic film and polyimide tape. The polyimide tape has a hole to which the substrate with the piezoresistive cantilever adheres. By attaching the sensor device to a mask where it contacts the nose of the subject, the sensor can detect the pulses and eye blinks of the subject by detecting the vibration and displacement of the nose skin caused by these physiological parameters. Moreover, the respiration of the subject causes pressure changes in the space between the mask and the face of the subject as well as slight vibrations of the mask. Therefore, information about the respiration of the subject can be extracted from the sensor signal using either the low-frequency component (<1 Hz) or the high-frequency component (>100 Hz). This paper describes the sensor fabrication and provides demonstrations of the pulse wave and respiration measurements as well as eye blink detection using the fabricated sensor.

scholarly journals MEMS-Based Sensor for Simultaneous Measurement of Pulse Wave and Respiration Rate

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4942 ◽  
Author(s):  
Thanh-Vinh Nguyen ◽  
Masaaki Ichiki
Keyword(s):  
Respiration Rate ◽  
Microelectromechanical Systems ◽  
Pulse Wave ◽  
Vital Signs ◽  
Low Frequency ◽  
Sensing Element ◽  
Inner Pressure ◽  
Sensor Device ◽  
Frequency Components ◽  
The Subject

The continuous measurements of vital signs (body temperature, blood pressure, pulse wave, and respiration rate) are important in many applications across various fields, including healthcare and sports. To realize such measurements, wearable devices that cause minimal discomfort to the wearers are highly desired. Accordingly, a device that can measure multiple vital signs simultaneously using a single sensing element is important in order to reduce the number of devices attached to the wearer’s body, thereby reducing user discomfort. Thus, in this study, we propose a device with a microelectromechanical systems (MEMS)-based pressure sensor that can simultaneously measure the blood pulse wave and respiration rate using only one sensing element. In particular, in the proposed device, a thin silicone tube, whose inner pressure can be measured via a piezoresistive cantilever, is attached to the nose pad of a pair of eyeglasses. On wearing the eyeglasses, the tube of sensor device is in contact with the area above the angular artery and nasal cavity of the subject, and thus, both pulse wave and breath of the subject cause the tube’s inner pressure to change. We experimentally show that it is possible to extract information related to pulse wave and respiration as the low-frequency and high-frequency components of the sensor signal, respectively.

scholarly journals A Robust Beat-to-Beat Artifact Detection Algorithm for Pulse Wave

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qihan Hu ◽  
Xintao Deng ◽  
Xin Liu ◽  
Aiguo Wang ◽  
Cuiwei Yang
Keyword(s):  
Pulse Wave ◽  
Smart Cities ◽  
Detection Algorithm ◽  
Wearable Devices ◽  
Segmentation Algorithm ◽  
Artifact Detection ◽  
Physiological Conditions ◽  
Physiological Signal ◽  
Pulse Waves ◽  
Complex Algorithm

With the rise of the concept of smart cities and healthcare, artificial intelligence helps people pay increasing attention to the health of themselves. People can wear a variety of wearable devices to monitor their physiological conditions. The pulse wave is a kind of physiological signal which is widely applied in the physiological monitoring system. However, the pulse wave is susceptible to artifacts, which prevents its popularization. In this work, we propose a novel beat-to-beat artifact detection algorithm, which performs pulse wave segmentation based on wavelet transform and then detects artifacts beat by beat based on the decision list. We verified our method on data acquired from different databases and compared with experts’ annotations. The segmentation algorithm achieved an accuracy of 96.13%. When it is applied to detect main peaks, the performance achieved an accuracy of 99.11%. After the previous segmentation algorithm, the artifact detection algorithm can detect beat-to-beat pulse waves and artifacts with an accuracy of 98.11%. The result indicated that the proposed method is robust for pulse waves of different patterns and could effectively detect the artifact without the complex algorithm. In summary, our proposed algorithm is capable of annotating pulse waves of various patterns and determining pulse wave quality. Since our method is developed and evaluated on the transmission-mode PPG data, it is more suitable for the devices and applications inside the hospitals instead of reflectance-mode PPG.

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