scholarly journals MINIATURE MODULES FOR MULTI-LEAD ECG RECORDING

2008 ◽  
Vol 20 (04) ◽  
pp. 219-222 ◽  
Author(s):  
Yi-Li Tseng ◽  
Hung-Wei Chiu ◽  
Tsung-Hsien Lin ◽  
Fu-Shan Jaw
Keyword(s):  
Home Health Care ◽  
Care Service ◽  
Health Care Service ◽  
Pass Band ◽  
Portable Devices ◽  
Biomedical Signals ◽  
Ecg Signals ◽  
Offset Voltage ◽  
Remote Monitoring Systems ◽  
Electrocardiogram Ecg

Remote monitoring systems for home health care service have become one of the hottest topics recently. Biomedical signals recorded by portable devices can be wirelessly transmitted through the Internet. In this paper, a miniature signal-condition module for ambulatory recording of electrocardiogram (ECG) signals was designed with high input impedance, high common-mode rejection ratio (CMRR), low power, appropriate amplification and filtration, and automatic suppression of offset voltage. For early detection of acute myocardial infarction (AMI), this device is extended and 12-lead ECG recording is available. Due to the modular approach, the module is accommodated for other biomedical signals recording as well if the gain and pass-band of the module are modified.

scholarly journals Practices used by a home care team: implications for caregivers

2021 ◽  
Vol 74 (2) ◽  
Author(s):  
Yara Cardoso Silva ◽  
Kênia Lara Silva ◽  
Isabela Silva Câncio Velloso
Keyword(s):  
Health Care ◽  
Discourse Analysis ◽  
Qualitative Study ◽  
Home Care ◽  
Home Health Care ◽  
Care Service ◽  
Health Care Service ◽  
Home Health ◽  
Care Team ◽  
Power Relationship

ABSTRACT Objectives: to analyze the practices of a home care team and their implications for caregivers’ performance. Methods: qualitative study with data obtained from observation of 21 users, 30 caregivers and 6 professionals from the home health care service in a municipality in Minas Gerais, from February to June 2018. The material was analyzed from the perspective of discourse analysis according to Michel Foucault. Results: team interference upon caregivers is exercised by disciplinary practices and prescriptive, authoritative and surveilling behaviors. The team’s knowledge-power relationship determines caregivers’ acceptance through convincing or through difficulty of understanding assigned orientations. Educational practices would enable caregivers to be constituted as active, participative, empowered and reflective subjects. Final Considerations: team practices interfere with caregivers’ ways of acting and being and they have implications in objectification and subjectification processes.

scholarly journals Deep Convolutional Neural Network Based ECG Classification System Using Information Fusion and One-Hot Encoding Techniques

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jia Li ◽  
Yujuan Si ◽  
Tao Xu ◽  
Saibiao Jiang
Keyword(s):  
Cardiovascular Disease ◽  
Adaptive Learning ◽  
Portable Devices ◽  
Ecg Signals ◽  
Automatic Feature Extraction ◽  
Average Accuracy ◽  
Proposed Model ◽  
Home Health Monitoring ◽  
Predictive Rate ◽  
Electrocardiogram Ecg

Although convolutional neural networks (CNNs) can be used to classify electrocardiogram (ECG) beats in the diagnosis of cardiovascular disease, ECG signals are typically processed as one-dimensional signals while CNNs are better suited to multidimensional pattern or image recognition applications. In this study, the morphology and rhythm of heartbeats are fused into a two-dimensional information vector for subsequent processing by CNNs that include adaptive learning rate and biased dropout methods. The results demonstrate that the proposed CNN model is effective for detecting irregular heartbeats or arrhythmias via automatic feature extraction. When the proposed model was tested on the MIT-BIH arrhythmia database, the model achieved higher performance than other state-of-the-art methods for five and eight heartbeat categories (the average accuracy was 99.1% and 97%). In particular, the proposed system had better performance in terms of the sensitivity and positive predictive rate for V beats by more than 4.3% and 5.4%, respectively, and also for S beats by more than 22.6% and 25.9%, respectively, when compared to existing algorithms. It is anticipated that the proposed method will be suitable for implementation on portable devices for the e-home health monitoring of cardiovascular disease.

scholarly journals Experiences of Family Members in Caring of Stroke Patients: A Case Study in the Border Provinces of the Upper Northeast of Thailand

2021 ◽  
Vol 9 (G) ◽  
pp. 172-179
Author(s):  
Arunrat Utaisang ◽  
Chatkane Pearkao ◽  
Khunphitha Junsevg ◽  
Amornrat Sangsaikaew ◽  
Duangjai Boonkong ◽  
...  
Keyword(s):  
Health Care ◽  
Family Caregivers ◽  
Home Health Care ◽  
Health Care Services ◽  
Care Service ◽  
Health Care Service ◽  
Phenomenological Approach ◽  
Stroke Patients ◽  
Long Distance ◽  
Care Services

BACKGROUND: Stroke patients require continued care, which makes stroke family caregivers unlikely to anticipate the end of home health-care service. AIM: The objectives of this study aimed, therefore, to seek understanding of stroke family caregivers in relation to caring experience, problems and barriers, and needs of family caregivers in the context of border provinces of the upper northeast of Thailand. METHODS: The current study was based on the phenomenological approach. The study samples included 16 informants. Data collection, conducted between February and August 2020, was performed using in-depth interviews. The collected data then were analyzed using the van Manen’s approach. RESULTS: Experiences of the stroke family caregivers were reflected and fell in van Manen’s 4 points under 12 thematic categories: (1) Lived body including lack of knowledge, fatigue, and sense of obligation; (2) lived time including paying gratitude, uncertainty, and paying retribution; (3) lived space including just long distance, being isolated in the wide world and living in a remote area; and (4) lived relation including blood thicker than water, community network, and needs from health-care services. CONCLUSION: The findings may be exploited to develop health service preparedness for health outcome promotion for stroke patients and stroke family caregivers.

scholarly journals Home Health Care Service And Recent Applications in Turkey

2010 ◽  
Vol 20 (3) ◽  
pp. 153-158 ◽  
Author(s):  
Murat Altuntaş ◽  
Tevfik Tanju Yılmazer ◽  
Yusuf Adnan Güçlü ◽  
Kurtuluş Öngel
Keyword(s):  
Health Care ◽  
Home Health Care ◽  
Care Service ◽  
Health Care Service ◽  
Home Health

scholarly journals Computational Diagnostic Techniques for Electrocardiogram Signal Analysis

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6318
Author(s):  
Liping Xie ◽  
Zilong Li ◽  
Yihan Zhou ◽  
Yiliu He ◽  
Jiaxin Zhu
Keyword(s):  
Health Care Professionals ◽  
Signal Analysis ◽  
Cardiovascular Death ◽  
Diagnostic Techniques ◽  
Portable Devices ◽  
Ecg Signal ◽  
Great Success ◽  
Ecg Signals ◽  
Electrical Impulses ◽  
Electrocardiogram Ecg

Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina, myocardial infarction, and ischemic heart failure, are the leading cause of death globally. Early detection and treatment of CVDs significantly contribute to the prevention or delay of cardiovascular death. Electrocardiogram (ECG) records the electrical impulses generated by heart muscles, which reflect regular or irregular beating activity. Computer-aided techniques provide fast and accurate tools to identify CVDs using a patient’s ECG signal, which have achieved great success in recent years. Latest computational diagnostic techniques based on ECG signals for estimating CVDs conditions are summarized here. The procedure of ECG signals analysis is discussed in several subsections, including data preprocessing, feature engineering, classification, and application. In particular, the End-to-End models integrate feature extraction and classification into learning algorithms, which not only greatly simplifies the process of data analysis, but also shows excellent accuracy and robustness. Portable devices enable users to monitor their cardiovascular status at any time, bringing new scenarios as well as challenges to the application of ECG algorithms. Computational diagnostic techniques for ECG signal analysis show great potential for helping health care professionals, and their application in daily life benefits both patients and sub-healthy people.

scholarly journals A Hierarchical Method for Removal of Baseline Drift from Biomedical Signals: Application in ECG Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yurong Luo ◽  
Rosalyn H. Hargraves ◽  
Ashwin Belle ◽  
Ou Bai ◽  
Xuguang Qi ◽  
...  
Keyword(s):  
Separation Process ◽  
Electrode Impedance ◽  
Accurate Analysis ◽  
Baseline Drift ◽  
Biomedical Signals ◽  
Ecg Signals ◽  
Hierarchical Method ◽  
St Segment ◽  
Baseline Wander ◽  
Electrocardiogram Ecg

Noise can compromise the extraction of some fundamental and important features from biomedical signals and hence prohibit accurate analysis of these signals. Baseline wander in electrocardiogram (ECG) signals is one such example, which can be caused by factors such as respiration, variations in electrode impedance, and excessive body movements. Unless baseline wander is effectively removed, the accuracy of any feature extracted from the ECG, such as timing and duration of the ST-segment, is compromised. This paper approaches this filtering task from a novel standpoint by assuming that the ECG baseline wander comes from an independent and unknown source. The technique utilizes a hierarchical method including a blind source separation (BSS) step, in particular independent component analysis, to eliminate the effect of the baseline wander. We examine the specifics of the components causing the baseline wander and the factors that affect the separation process. Experimental results reveal the superiority of the proposed algorithm in removing the baseline wander.

scholarly journals A Patient Journey Map to Improve the Home Isolation Experience of Persons With Mild COVID-19: Design Research for Service Touchpoints of Artificial Intelligence in eHealth (Preprint)

2020 ◽  
Author(s):  
Qian He ◽  
Fei Du ◽  
Lianne W L Simonse
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Home Health Care ◽  
Design Research ◽  
Care Service ◽  
Negative Mood ◽  
Health Care Service ◽  
Community Support ◽  
Patient Journey ◽  
Ehealth Services

BACKGROUND In the context of the COVID-19 outbreak, 80% of the persons who are infected have mild symptoms and are required to self-recover at home. They have a strong demand for remote health care that, despite the great potential of artificial intelligence (AI), is not met by the current services of eHealth. Understanding the real needs of these persons is lacking. OBJECTIVE The aim of this paper is to contribute a fine-grained understanding of the home isolation experience of persons with mild COVID-19 symptoms to enhance AI in eHealth services. METHODS A design research method with a qualitative approach was used to map the patient journey. Data on the home isolation experiences of persons with mild COVID-19 symptoms was collected from the top-viewed personal video stories on YouTube and their comment threads. For the analysis, this data was transcribed, coded, and mapped into the patient journey map. RESULTS The key findings on the home isolation experience of persons with mild COVID-19 symptoms concerned (1) an awareness period before testing positive, (2) less typical and more personal symptoms, (3) a negative mood experience curve, (5) inadequate home health care service support for patients, and (6) benefits and drawbacks of social media support. CONCLUSIONS The design of the patient journey map and underlying insights on the home isolation experience of persons with mild COVID-19 symptoms serves health and information technology professionals in more effectively applying AI technology into eHealth services, for which three main service concepts are proposed: (1) trustworthy public health information to relieve stress, (2) personal COVID-19 health monitoring, and (3) community support.

Sign in / Sign up

Export Citation Format

Share Document