Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

Bae, Tae Wuk; Kwon, Kee-Koo; Kim, Kyu Hyung

doi:10.3390/s20041089

Cited by 10 publications

(3 citation statements)

References 22 publications

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“…Table 2 shows the statistical characteristics of the patients on renal dialysis who participated in the clinical trial. In addition, the R-peak detection methods of [ 35 , 36 ], and [ 37 ] were applied to electrocardiogram signals of hemodialysis patients for HR calculation.…”

Section: Methodsmentioning

confidence: 99%

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation

Bae

Kim

Park

et al. 2022

IJERPH

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Intradialytic hypotension (IDH) is a common side effect that occurs during hemodialysis and poses a great risk for dialysis patients. Many studies have been conducted so far to predict IDH, but most of these could not be applied in real-time because they used only underlying patient information or static patient disease information. In this study, we propose a multilayer perceptron (MP)-based IDH prediction model using heart rate (HR) information corresponding to time-series information and static data of patients. This study aimed to validate whether HR differences and HR slope information affect real-time IDH prediction in patients undergoing hemodialysis. Clinical data were collected from 80 hemodialysis patients from 9 September to 17 October 2020, in the artificial kidney room at Yeungnam University Medical Center (YUMC), Daegu, South Korea. The patients typically underwent hemodialysis 12 times during this period, 1 to 2 h per session. Therefore, the HR difference and HR slope information within up to 1 h before IDH occurrence were used as time-series input data for the MP model. Among the MP models using the number and data length of different hidden layers, the model using 60 min of data before the occurrence of two layers and IDH showed maximum performance, with an accuracy of 81.5%, a true positive rate of 73.8%, and positive predictive value of 87.3%. This study aimed to predict IDH in real-time by continuously supplying HR information to MP models along with static data such as age, diabetes, hypertension, and ultrafiltration. The current MP model was implemented using relatively limited parameters; however, its performance may be further improved by adding additional parameters in the future, further enabling real-time IDH prediction to play a supporting role for medical staff.

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Section: Methodsmentioning

confidence: 99%

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation

Bae

Kim

Park

et al. 2022

IJERPH

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“…In [17] This study [18] compared the effectiveness of Self-Injection Locking (SIL) radar, a continuous-wave radar system, with traditional electrocardiogram (ECG) measurements in monitoring respiratory rate (RR) and heartbeat rate (HR) during the COVID-19 pandemic. The research involved 31 hospital staff members, and data obtained from SIL radar and ECG were simultaneously collected and analyzed.…”

Section: Framework and Algorithms Of Vital Signs Monitoringmentioning

confidence: 99%

Efficiency, Research, and Healthcare Economics: (Vital Threat Detection System) A Systematic Review

Aljuhani,

Alraigi,

Alotaibi

et al. 2024

IJCI

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Monitoring vital signs and detecting diseases like diabetes and cancer at an early stage are incredibly important for safeguarding patients' lives and ensuring a healthy environment. In this study, we present a comprehensive systematic review focusing on vital monitoring systems in diverse fields. We reviewed 85 articles spanning from 2019 to 2024. From the selected articles, our aim is to explore the frameworks and algorithms of vital signs monitoring, the latest techniques used in remote vital signs monitoring such as radar and smart watch, as well as the measurement of vital signs for heart rate and respiratory diseases. Also, we discuss the threats that may affect healthcare systems and how to secure against these threats. The findings emphasize the critical importance of acquiring continuous vital monitoring systems, which have immense potential for improving healthcare. These systems are crucial for early diagnosis and prediction of conditions that may negatively impact the patient's health. Additionally, it could be beneficial for doctors and healthcare staff by saving time and costs.

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“…Current advances in wireless technology have impacted health care significantly, and electrocardiogram (ECG) monitoring devices are no different. Improvements in traditional ECG recording and wireless technology have resulted in portable, interconnected and smart ECG recorders and eHealth networking [ 8 , 9 , 10 , 11 ]. The development of cost-effective non-invasive long-term ECG monitoring alternatives will reduce mortality in subjects at high risk for SCD [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies around the MUAC Line

Escalona

Mukhtar

McEneaney

et al. 2022

Sensors

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Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from −30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.

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Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

Cited by 10 publications

References 22 publications

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation

Efficiency, Research, and Healthcare Economics: (Vital Threat Detection System) A Systematic Review

Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies around the MUAC Line

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