Non-invasive blood pressure data acquisition employing pulse transit time detection

2002 ◽  
Author(s):  
J. Kerola ◽  
V. Kontra ◽  
R. Sepponen
Keyword(s):  
Blood Pressure ◽  
Data Acquisition ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Pressure Data ◽  
Invasive Blood Pressure ◽  
Non Invasive ◽  
Blood Pressure Data

scholarly journals Continuous non-invasive blood pressure during continuous repositioning by pulse transit time

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Hieyong Jeong ◽  
Kayo Yoshimoto ◽  
Tianyi Wang ◽  
Takafumi Ohno ◽  
Kenji Yamada ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Invasive Blood Pressure ◽  
Non Invasive

scholarly journals Analyzing 24-Hour Blood Pressure Measurements with a Novel Cuffless Pulse Transit Time Device in Clinical Practice—Does the Software for Heartbeat Detection Matter?

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 361
Author(s):  
Leo Kilian ◽  
Philipp Krisai ◽  
Thenral Socrates ◽  
Christian Arranto ◽  
Otmar Pfister ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
Population Level ◽  
Raw Data ◽  
Invasive Blood Pressure ◽  
Individual Level ◽  
Non Invasive ◽  
The Individual ◽  
The Impact

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.

scholarly journals Artefacts in continuous overnight blood pressure assessment based on pulse transit time

2021 ◽  
Vol 7 (2) ◽  
pp. 843-846
Author(s):  
Dagmar Krefting ◽  
Tibor Kesztyüs ◽  
Henning Dathe
Keyword(s):  
Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Transit Time ◽  
Pulse Transit Time ◽  
High Potential ◽  
Sleep Disruption ◽  
Pressure Measurements ◽  
Short Article ◽  
Invasive Blood Pressure ◽  
Non Invasive

Abstract Continuous non-invasive blood pressure measurements bear a high potential. Particular in Somnology they allow to derive comfortably the systolic and diastolic blood pressure from an electrocardiogram and a synchronous photoplethysmogram without sleep disruption. In this short article some possible problems of this method are discussed along overnight recordings with a SOMNOtouch NIBP device.

scholarly journals Towards Continuous and Ambulatory Blood Pressure Monitoring: Methods for Efficient Data Acquisition for Pulse Transit Time Estimation

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7106
Author(s):  
Oludotun Ode ◽  
Lara Orlandic ◽  
Omer T. Inan
Keyword(s):  
Blood Pressure ◽  
Embedded System ◽  
Data Acquisition ◽  
Transit Time ◽  
Ambulatory Blood Pressure ◽  
Field Experiments ◽  
Control Method ◽  
Pulse Transit Time ◽  
Huffman Coding ◽  
Physiological Data

We developed a prototype for measuring physiological data for pulse transit time (PTT) estimation that will be used for ambulatory blood pressure (BP) monitoring. The device is comprised of an embedded system with multimodal sensors that streams high-throughput data to a custom Android application. The primary focus of this paper is on the hardware–software codesign that we developed to address the challenges associated with reliably recording data over Bluetooth on a resource-constrained platform. In particular, we developed a lossless compression algorithm that is based on optimally selective Huffman coding and Huffman prefixed coding, which yields virtually identical compression ratios to the standard algorithm, but with a 67–99% reduction in the size of the compression tables. In addition, we developed a hybrid software–hardware flow control method to eliminate microcontroller (MCU) interrupt-latency related data loss when multi-byte packets are sent from the phone to the embedded system via a Bluetooth module at baud rates exceeding 115,200 bit/s. The empirical error rate obtained with the proposed method with the baud rate set to 460,800 bit/s was identically equal to 0%. Our robust and computationally efficient physiological data acquisition system will enable field experiments that will drive the development of novel algorithms for PTT-based continuous BP monitoring.

scholarly journals Novel computation of pulse transit time from multi-channel PPG signals by wavelet transform

2016 ◽  
Vol 2 (1) ◽  
pp. 209-213 ◽  
Author(s):  
Alexandru-Gabriel Pielmuş ◽  
Maik Pflugradt ◽  
Timo Tigges ◽  
Michael Klum ◽  
Aarne Feldheiser ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Wavelet Transform ◽  
Transit Time ◽  
Sensor Node ◽  
Pulse Transit Time ◽  
Time Data ◽  
Dual Mode ◽  
Non Invasive ◽  
System Methodology ◽  
Biomedical Community

AbstractBeing able to accurately monitor blood pressure in a reliable, truly non-invasive manner is a highly sought after goal within the biomedical community. In this paper we propose and assess a system, methodology and algorithm for unobtrusively obtaining true pulse transit time data from readily accessible peripheral locations, such as the hand, using a highly synchronous body-sensor-network encompassing an electrocardiogram- and dual mode photoplethysmogram sensor node. The results suggest the feasibility of acquiring such data, which strongly correlates with the recorded reference blood pressure, and can therefore be further employed to track changes thereof.

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