Cor/log BAN BT a Wearable Battery Powered mHealth Data Logger and Telemetry Unit for Multiple Vital Sign Monitoring.

Hilbel, Thomas; Feilner, Sven; Struck, Matthias; Hofmann, Christian; Heinig, Andreas; Katus, Hugo A.

doi:10.22489/cinc.2016.080-163

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Hilbel et al, ( 24 ) present a wireless data logger system that allows seamless 24/7 monitoring of relevant vital sign parameters. CL covers the entire period of acute point of care inside the hospital and the recovery period, when first mobility is achieved and when the patient is released into an ambulatory or home care environment.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Villarreal¹,

Berbey-Alvarez²

2020

Acta Inform Med

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Introduction: Currently, with the widespread penetration of mobile devices with Internet access, including smartphones, they can allow specific and/or complementary activities in the health field as well as in other commercial sectors. Aim: This systematic review examined the impact of mHealth-based for cardiovascular research. The specific aims of the systematic review are to ( 1 ) classification of the studies according to the type of research (scientific articles and master’s and doctoral theses) and ( 2 ) relationship of studies with topics associated with cardiovascular diseases. Results: This review corresponds to information in scientific journals of high impact. This review intends to respond to the following question: How these research works have evaluated the performance of health mobile applications, with a special interest in cardiac issues? This review of these searches corresponds to an analysis by 14 categories, being these: 1) Scientific paper; 2) Doctoral Thesis; 3) Master thesis; 4) Telemedicine; 5) m-sssshealth, e-health; 6) cardiovascular, coronary diseases, heart failures, cardiopulmonary, cardiac rehabilitation; 7) rural health; 8) prevention and control, protection; 9) wearables; 10) mobile, web applications, app, smartphone, software, platform; 11) mhealth education, training, promotion, formative process; 12) self-management; 13) Multiple Vital Sign Monitoring, medical device, heart rate measurement, health care information systems; 14) health regulatory. It provides evidence of how some apps have been evaluated, and in some cases, the effectiveness of the estimated accuracy is not in line with the real situation. Conclusion: The analysis of these studies allows us to locate the sources of the development of mobile health projects. It also guides us to discover some needs that require new technology implementations.

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Section: Resultsmentioning

confidence: 99%

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Villarreal¹,

Berbey-Alvarez²

2020

Acta Inform Med

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“…In this expression, H(f i ) describes the information of amplitude and ∠ H(f i ) explains the phase information for CSI signal. The measured OFDM subcarriers contain the values of CSI packets and it can be shown in equation (2). [23].…”

Section: B Signal Modelmentioning

confidence: 99%

“…Several approaches for tracking human health and vital signs including breathing detection have been developed recently. Some of them include the use of smartphones and wearable sensor [1], [2], doppler radar [3], [4], Wi-Fi [5], ultra-wideband radar [6] and frequency modulated carriers [7]. Traditional techniques such as the received signal strength (RSS) provide a single frequency carrier power measurement with regards to full available Ashleibta is with James Watt School of Engineering, University of Glasgow, Glasgow,G12 8QQ, U.K.(E-mail: 2449786a@ student.gla.ac.uk Syed Aziz Shah, Associate Professor of Mobile Health.…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive RF Sensing for Detecting Breathing Abnormalities Using Software Defined Radios

et al. 2021

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The non-contact continuous monitoring of biomarkers comprising breathing detection and heart rate are essential vital signs to evaluate the general physical health of a patient. As compared to existing methods that need dedicated equipment (such as wearable sensors), the radio frequency (RF) signals can be synthesised to continuously monitor breathing rate in a contact-less setting. In this paper, we proposed the contact less breathing rate detection using universal software radio peripheral (USRP) platform without any wearable sensor. Our system leverage on the channel state information (CSI) to record the minute movement caused by breathing over orthogonal frequency division multiplexing (OFDM) in multiple sub-carriers. We presented a comparison of our breathing rate detection with wearable sensor (ground truth) results for single human subject. In this paper, we used wireless data to train, validate and test different machine learning (ML) algorithms to classify USRP data into normal, shallow and elevated breathing depending on the breathing rate. Although different ML models were developed using the K-Nearest Neighbor (KNN), Discriminant Analysis (DA), Naive Bayes (NB) and Decision Tree (DT) algorithms, however results showed KNN based model provided the highest accuracy for our data (91%) each time the trial was made. DT (17.131%), DA (59.72%) and NB (48.99%). Results presented in this paper showed that USRP based breathing rate is comparable to the wearable sensor demonstrating the potential application of our method to accurately monitor breathing rate of patients in primary or acute setting.

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Personalized medical alert system based on Internet of Things with DHIS2

Enciso-Quispe

Sarmiento

Zelaya-Policarpo

2018

2018 13th Iberian Conference on Information Systems and Technologies (CISTI)

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Cor/log BAN BT a Wearable Battery Powered mHealth Data Logger and Telemetry Unit for Multiple Vital Sign Monitoring.

Abstract: The wireless data logger system "Cor/log® BAN BT" (CL)

Cited by 3 publications

References 2 publications

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Non-Invasive RF Sensing for Detecting Breathing Abnormalities Using Software Defined Radios

Personalized medical alert system based on Internet of Things with DHIS2

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