Callegari et al., 2014 - Google Patents

EpiCare—A home care platform based on mobile cloud computing to assist epilepsy diagnosis

Callegari et al., 2014

View PDF
Document ID
134489432927457908
Author
Callegari D
Conte E
Ferreto T
Fernandes D
Moraes F
Burmeister F
Severino R
Publication year
Publication venue
2014 4th International Conference on Wireless Mobile Communication and Healthcare-Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH)

External Links

Snippet

Epilepsy is a neurological disorder that affects a significant percentage of the population. Currently, electroencephalogram exams (EEG) are considered a valuable tool to support epilepsy diagnosis. In order to obtain a more trustworthy diagnosis, it is frequently necessary …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402Electrocardiography, i.e. ECG
    • A61B5/0452Detecting specific parameters of the electrocardiograph cycle
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476Electroencephalography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4094Diagnosing or monitoring seizure diseases, e.g. epilepsy
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/22Health care, e.g. hospitals; Social work
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7232Signal processing specially adapted for physiological signals or for diagnostic purposes involving compression of the physiological signal, e.g. to extend the signal recording period
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/04012Analysis of electro-cardiograms, electro-encephalograms, electro-myograms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165Evaluating the state of mind, e.g. depression, anxiety
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring

Similar Documents

Publication Publication Date Title
Karpov et al. Extreme value theory inspires explainable machine learning approach for seizure detection
Husnain et al. AI-driven integrated hardware and software solution for EEG-based detection of depression and anxiety
Jahan et al. AI-based epileptic seizure detection and prediction in internet of healthcare things: a systematic review
Khowaja et al. Toward soft real-time stress detection using wrist-worn devices for human workspaces: SA Khowaja et al.
Gaurav et al. EEG based cognitive task classification using multifractal detrended fluctuation analysis
Kaur et al. Artificial intelligence in epilepsy
Grubov et al. Two-stage approach with combination of outlier detection method and deep learning enhances automatic epileptic seizure detection
US12076166B2 (en) Neural oscillation monitoring system
Shen et al. A physiology-based seizure detection system for multichannel EEG
JP2019500939A (en) Device, system and method for screening and monitoring of encephalopathy / delirium
Sameh et al. Digital phenotypes and digital biomarkers for health and diseases: a systematic review of machine learning approaches utilizing passive non-invasive signals collected via wearable devices and smartphones
Rajaguru et al. KNN classifier and K-Means clustering for robust classification of epilepsy from EEG signals. A detailed analysis
Olokodana et al. Real-time automatic seizure detection using ordinary kriging method in an edge-IoMT computing paradigm
Saini et al. An extensive review on development of EEG-based computer-aided diagnosis systems for epilepsy detection
Callegari et al. EpiCare—A home care platform based on mobile cloud computing to assist epilepsy diagnosis
Karri et al. A real-time cardiac arrhythmia classification using hybrid combination of delta modulation, 1D-CNN and blended LSTM
Bhagubai et al. Towards automated seizure detection with wearable eeg–grand challenge
Hassan et al. NeuroWave-Net: Enhancing epileptic seizure detection from EEG brain signals via advanced convolutional and long short-term memory networks.
Chicco et al. Ten quick tips for electrocardiogram (ECG) signal processing
Naregalkar et al. Artificial intelligence driven mental health diagnosis based on physiological signals
Shen et al. GA-SVM modeling of multiclass seizure detector in epilepsy analysis system using cloud computing
Kukhilava et al. Evaluation in eeg emotion recognition: state-of-the-art review and unified framework
Annadate et al. Harnessing deep learning for early detection of cardiac abnormalities
Rao et al. Machine learning framework for identification of abnormal EEG signal
Shen et al. Bio-signal analysis system design with support vector machines based on cloud computing service architecture