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computerized ecg machine fdx-6521  (Fukuda Denshi Co)

 
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    Fukuda Denshi Co computerized ecg machine fdx-6521
    Computerized Ecg Machine Fdx 6521, supplied by Fukuda Denshi Co, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/computerized+ecg+machine/recording+system+fdx+6521/pm21672307-30-7-11
    Average 90 stars, based on 1 article reviews
    computerized ecg machine fdx-6521 - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    Biomarker Discovery:

    Article Title: Prediction of atrial fibrillation after ischemic stroke using P-wave signal averaged electrocardiography.
    Article Snippet: The algorithm of he P wave-triggering system of FDX-6521 was the same as that of CM-3000 (Fukuda Denshi Co. Ltd.) [6].

    Article Title: Use of a new high-sensitivity assay for cardiac troponin T to stratify the risk of cardiovascular disease in outpatients with type-2 diabetes
    Article Snippet: Background Chronic elevation of cardiac troponin T (TnT) levels as measured by conventional assays is strongly associated with structural heart disease and cardiovascular events.. A new high-sensitivity assay for TnT makes it possible to measure concentrations more than a factor of 5 lower than the limits of detection of conventional assays.. We evaluated the utility of serum TnT as a risk marker of cardiovascular disease in 409 outpatients with type-2 diabetes mellitus (T2DM).

    Article Title: A novel signal-averaged electrocardiogram and an ambulatory-based signal-averaged electrocardiogram show strong correlations with conventional signal-averaged electrocardiogram in healthy subjects: A validation study.
    Article Snippet: Contents lists available at ScienceDirect Journal of Electrocardiology j ourna l homepage: www. jecgon l ine .com Resarch paper A novel signal-averaged electrocardiogram and an ambulatory-based signal-averaged electrocardiogram show strong correlations with conventional signal-averaged electrocardiogram in healthy subjects: A validation study Kenichi Hashimoto, MD, PhD a, Bonpei Takase, MD, PhD a, Masaaki Nagashima, MD, PhDb, Yuji Kasamaki, MD, PhD c, Hiroaki Shimabukuro d, Masayoshi Soma, MD, PhD e, Tomohiro Nakayama, MD, PhDb,⁎ a Department of Intensive Care Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan b Division of Laboratory Medicine, Department of Pathology and Microbiology, Nihon University School of Medicine, Tokyo, Japan c Department of General Medicine, Kanazawa Medical University Himi Municipal Hospital, Kanazawa, Japan d Department of Clinical Laboratory, Nihon University Itabashi Hospital, Japan e Division of General Medicine, Department of Medicine, Nihon University School of Medicine, Tokyo, Japan ⁎ Corresponding author at: Division of Laboratory Med and Microbiology, Nihon University School of Medicin Itabashi-ku, Tokyo 173-8610, Japan.. E-mail address: nakayama.tomohiro@nihon-u.ac.jp (T https://doi.org/10.1016/j.jelectrocard.2018.10.084 0022-0736/© 2018 Published by Elsevier Inc. a b s t r a c t a r t i c l e i n f o Keywords: Background: A novel signal-averaged electrocardiogram (SAECG) device and a novel ambulatory SAECG device are clinically available, but reference values have not been established.. This study aimed to validate the novel SAECG and the novel ambulatory-based SAECG devices by comparison with the conventional SAECG device.

    Article Title: High-frequency power within the QRS complex in ischemic cardiomyopathy patients with ventricular arrhythmias: Insights from a clinical study and computer simulation of cardiac fibrous tissue.
    Article Snippet: Accepted Manuscript High-frequency power within the QRS complex in ischemic cardiomyopathy patients with ventricular arrhythmias: Insights from a clinical study and computer simulation of cardiac fibrous tissue Takeshi Tsutsumi, Yoshiwo Okamoto, Nami Takano, Daisuke Wakatsuki, Takanobu Tohmaru, Toshiaki Nakajima PII: S0010-4825(17)30144-0 DOI: 10.1016/j.compbiomed.2017.05.022 Reference: CBM 2677 To appear in: Computers in Biology and Medicine Received Date: 13 October 2016 Revised Date: 18 May 2017 Accepted Date: 19 May 2017 Please cite this article as: T. Tsutsumi, Y. Okamoto, N. Takano, D. Wakatsuki, T. Tohmaru, T. Nakajima, High-frequency power within the QRS complex in ischemic cardiomyopathy patients with ventricular arrhythmias: Insights from a clinical study and computer simulation of cardiac fibrous tissue, Computers in Biology and Medicine (2017), doi: 10.1016/j.compbiomed.2017.05.022.. This is a PDF file of an unedited manuscript that has been accepted for publication.. As a service to our customers we are providing this early version of the manuscript.

    Article Title: Level of urinary liver-type fatty acid-binding protein is associated with cardiac markers and electrocardiographic abnormalities in type-2 diabetes with chronic kidney disease stage G1 and G2.
    Article Snippet: Urinary liver-type fatty acid-binding protein (L-FABP) reflects the degree of stress in proximal tubules of the kidney.. We examined the level of L-FABP in type-2 diabetes mellitus (T2DM) patients with chronic kidney disease (CKD) stage G1 and G2, and its relationship with cardiac markers and electrocardiographic (ECG) abnormalities.. T2DM patients whose estimated glomerular filtration rate (eGFR) was C60 mL/min/1.73 m were recruited [n = 276 (165 males), mean age 64 years].

    Article Title: "Frequency Power Profile within the QRS Complex in Patients with Lethal Ventricular Arrhythmias: An Approach to a New Risk Marker for Sudden Cardiac Death"
    Article Snippet: In 57 patients with L-VAs and 60 control cases, bipolar orthogonal X, Y, and Z leads were measured for 20 seconds through a band-pass filter with higher and lower edges of 300 Hz and 0.15 Hz using an FDX-6521 Cardio-Multi (Fukuda Denshi, Co. Ltd., Tokyo, Japan).



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    Twelve‐lead <t>ECG</t> showing a Brugada‐type ECG of coved type.
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    Image Search Results


    Data collection and labelling. In total, 72 647 12-lead electrocardiograms were retrospectively retrieved. Electrocardiograms with duplicate data ( n = 3111), incomplete information of age or age less than 18 years old ( n = 1673), absence of definite diagnosis ( n = 6759), and those not performed at China Medical University Hospital ( n = 567) were excluded. The remaining 60 537 electrocardiogram signals from 35 981 patients were included in this study.

    Journal: European Heart Journal. Digital Health

    Article Title: Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram

    doi: 10.1093/ehjdh/ztab029

    Figure Lengend Snippet: Data collection and labelling. In total, 72 647 12-lead electrocardiograms were retrospectively retrieved. Electrocardiograms with duplicate data ( n = 3111), incomplete information of age or age less than 18 years old ( n = 1673), absence of definite diagnosis ( n = 6759), and those not performed at China Medical University Hospital ( n = 567) were excluded. The remaining 60 537 electrocardiogram signals from 35 981 patients were included in this study.

    Article Snippet: The 12-lead ECG was recorded according to a standardized protocol and lead position at a sampling rate of 500 Hz using a computerized ECG machine (GE Healthcare MAC 2000/3500/5500, USA).

    Techniques: Biomarker Discovery

    Data set for training, validation, and testing of the LSTM model

    Journal: European Heart Journal. Digital Health

    Article Title: Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram

    doi: 10.1093/ehjdh/ztab029

    Figure Lengend Snippet: Data set for training, validation, and testing of the LSTM model

    Article Snippet: The 12-lead ECG was recorded according to a standardized protocol and lead position at a sampling rate of 500 Hz using a computerized ECG machine (GE Healthcare MAC 2000/3500/5500, USA).

    Techniques: Biomarker Discovery, Blocking Assay

    Two representative electrocardiograms in the external testing. ( A ) The long short-term memory model, all of the four cardiologists, one of the three emergency physicians, and the commercial algorithm correctly classified the electrocardiogram as second degree AV block and acute STEMI, whereas two emergency physicians and all of the three internists annotated either second degree AV block or ST-elevation myocardial infarction but not both for this electrocardiogram. ( B ) The long short-term memory model correctly classified the electrocardiogram as BIGEMINY and first degree AV block, while most doctors (8 of the 10 physicians) and the commercial algorithm only annotated BIGEMINY but not first degree AV block. Abbreviations for the electrocardiogram diagnoses as in <xref ref-type=Figure 2 . " width="100%" height="100%">

    Journal: European Heart Journal. Digital Health

    Article Title: Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram

    doi: 10.1093/ehjdh/ztab029

    Figure Lengend Snippet: Two representative electrocardiograms in the external testing. ( A ) The long short-term memory model, all of the four cardiologists, one of the three emergency physicians, and the commercial algorithm correctly classified the electrocardiogram as second degree AV block and acute STEMI, whereas two emergency physicians and all of the three internists annotated either second degree AV block or ST-elevation myocardial infarction but not both for this electrocardiogram. ( B ) The long short-term memory model correctly classified the electrocardiogram as BIGEMINY and first degree AV block, while most doctors (8 of the 10 physicians) and the commercial algorithm only annotated BIGEMINY but not first degree AV block. Abbreviations for the electrocardiogram diagnoses as in Figure 2 .

    Article Snippet: The 12-lead ECG was recorded according to a standardized protocol and lead position at a sampling rate of 500 Hz using a computerized ECG machine (GE Healthcare MAC 2000/3500/5500, USA).

    Techniques: Blocking Assay

    Performance of the long short-term memory model and different groups of board-certified doctors in detecting acute ST-elevation myocardial infarction and different heart rhythms. These are the accuracies and receiver operating characteristic curves in detecting ( A ) ST-elevation myocardial infarction ( B ) atrial fibrillation ( C ) complete heart block ( D ) paroxysmal supraventricular tachycardia of our artificial intelligence model and the results of a commercial algorithm and different groups of doctors in the comparative external tests. The orange line was the receiver operating characteristic curve of the long short-term memory model. The different colour points represent different groups of board-certified doctors. AI, artificial intelligence; CV, cardiologists; ER, emergency physicians; LSTM, long short-term memory; MR, internists; abbreviations for the electrocardiogram diagnoses are as in <xref ref-type=Figure 2 . Only the four important classes, discussed in the main text are shown here, the rest was presented in Supplementary material online, Figure S1 . " width="100%" height="100%">

    Journal: European Heart Journal. Digital Health

    Article Title: Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram

    doi: 10.1093/ehjdh/ztab029

    Figure Lengend Snippet: Performance of the long short-term memory model and different groups of board-certified doctors in detecting acute ST-elevation myocardial infarction and different heart rhythms. These are the accuracies and receiver operating characteristic curves in detecting ( A ) ST-elevation myocardial infarction ( B ) atrial fibrillation ( C ) complete heart block ( D ) paroxysmal supraventricular tachycardia of our artificial intelligence model and the results of a commercial algorithm and different groups of doctors in the comparative external tests. The orange line was the receiver operating characteristic curve of the long short-term memory model. The different colour points represent different groups of board-certified doctors. AI, artificial intelligence; CV, cardiologists; ER, emergency physicians; LSTM, long short-term memory; MR, internists; abbreviations for the electrocardiogram diagnoses are as in Figure 2 . Only the four important classes, discussed in the main text are shown here, the rest was presented in Supplementary material online, Figure S1 .

    Article Snippet: The 12-lead ECG was recorded according to a standardized protocol and lead position at a sampling rate of 500 Hz using a computerized ECG machine (GE Healthcare MAC 2000/3500/5500, USA).

    Techniques: Blocking Assay

    The representative ST-elevation myocardial infarction electrocardiogram images of false negative cases missed by humans and the computer in the external test. ( A ) The artificial intelligence model correctly annotated ST-elevation myocardial infarction, whereas one of the four cardiologists labelled ‘Not STEMI’ resulting in a false negative annotation. ( B ) All the four cardiologists correctly diagnosed ST-elevation myocardial infarction, while the artificial intelligence model annotated ‘Not STEMI’ and it was counted as a false negative.

    Journal: European Heart Journal. Digital Health

    Article Title: Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram

    doi: 10.1093/ehjdh/ztab029

    Figure Lengend Snippet: The representative ST-elevation myocardial infarction electrocardiogram images of false negative cases missed by humans and the computer in the external test. ( A ) The artificial intelligence model correctly annotated ST-elevation myocardial infarction, whereas one of the four cardiologists labelled ‘Not STEMI’ resulting in a false negative annotation. ( B ) All the four cardiologists correctly diagnosed ST-elevation myocardial infarction, while the artificial intelligence model annotated ‘Not STEMI’ and it was counted as a false negative.

    Article Snippet: The 12-lead ECG was recorded according to a standardized protocol and lead position at a sampling rate of 500 Hz using a computerized ECG machine (GE Healthcare MAC 2000/3500/5500, USA).

    Techniques:

    Twelve‐lead ECG showing a Brugada‐type ECG of coved type.

    Journal: Annals of Noninvasive Electrocardiology : The Official Journal of the International Society for Holter and Noninvasive Electrocardiology, Inc

    Article Title: Noninvasive Risk Stratification of Subjects with a Brugada‐Type Electrocardiogram and No History of Cardiac Arrest

    doi: 10.1111/j.1542-474X.2005.00055.x

    Figure Lengend Snippet: Twelve‐lead ECG showing a Brugada‐type ECG of coved type.

    Article Snippet: Analysis of ECG Parameters Mean QRS duration, maximal QTc interval, QT dispersion, and the amplitude of ST‐segment elevation were analyzed automatically using a computerized 12‐lead ECG machine (FDX‐6521, Fukuda Denshi Co., Tokyo, Japan).

    Techniques:

    A spontaneous change of ST segment consistent with the Brugada syndrome in ECG leads V1–V3 taken on July 22, 1999.

    Journal: Annals of Noninvasive Electrocardiology : The Official Journal of the International Society for Holter and Noninvasive Electrocardiology, Inc

    Article Title: Noninvasive Risk Stratification of Subjects with a Brugada‐Type Electrocardiogram and No History of Cardiac Arrest

    doi: 10.1111/j.1542-474X.2005.00055.x

    Figure Lengend Snippet: A spontaneous change of ST segment consistent with the Brugada syndrome in ECG leads V1–V3 taken on July 22, 1999.

    Article Snippet: Analysis of ECG Parameters Mean QRS duration, maximal QTc interval, QT dispersion, and the amplitude of ST‐segment elevation were analyzed automatically using a computerized 12‐lead ECG machine (FDX‐6521, Fukuda Denshi Co., Tokyo, Japan).

    Techniques: