Schätz et al., 2020 - Google Patents
Sleep apnea detection with polysomnography and depth sensorsSchätz et al., 2020
View HTML- Document ID
- 9017515750109962957
- Author
- Schätz M
- Procházka A
- Kuchyňka J
- Vyšata O
- Publication year
- Publication venue
- Sensors
External Links
Snippet
This paper is devoted to proving two goals, to show that various depth sensors can be used to record breathing rate with the same accuracy as contact sensors used in polysomnography (PSG), in addition to proving that breathing signals from depth sensors …
- 208000000927 Sleep Apnea Syndrome 0 title abstract description 32
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-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
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
- G06Q50/24—Patient record management
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Negishi et al. | Contactless vital signs measurement system using RGB-thermal image sensors and its clinical screening test on patients with seasonal influenza | |
Procházka et al. | Microsoft kinect visual and depth sensors for breathing and heart rate analysis | |
Procházka et al. | Breathing analysis using thermal and depth imaging camera video records | |
Al-Naji et al. | Real time apnoea monitoring of children using the Microsoft Kinect sensor: a pilot study | |
Lim et al. | Developing a diagnostic decision support system for benign paroxysmal positional vertigo using a deep-learning model | |
Romano et al. | Non-contact respiratory monitoring using an RGB camera for real-world applications | |
Miller et al. | A validation study of a commercial wearable device to automatically detect and estimate sleep | |
Schätz et al. | Sleep apnea detection with polysomnography and depth sensors | |
Hochhausen et al. | Estimating respiratory rate in post-anesthesia care unit patients using infrared thermography: an observational study | |
Addison et al. | Noncontact respiratory monitoring using depth sensing cameras: A review of current literature | |
Ejupi et al. | Detection of talking in respiratory signals: A feasibility study using machine learning and wearable textile-based sensors | |
Peinado-Rubia et al. | Impaired balance in patients with fibromyalgia syndrome: Predictors of the impact of this disorder and balance confidence | |
Albani et al. | An integrated multi-sensor approach for the remote monitoring of Parkinson’s disease | |
Sun et al. | Respiration monitoring for premature neonates in NICU | |
Jeng et al. | A wrist sensor sleep posture monitoring system: An automatic labeling approach | |
Baccinelli et al. | Movidea: A software package for automatic video analysis of movements in infants at risk for neurodevelopmental disorders | |
Pfitzner et al. | Body weight estimation for dose-finding and health monitoring of lying, standing and walking patients based on RGB-D data | |
Stern et al. | In-bed posture classification using deep neural network | |
Tsai et al. | An automated sitting posture recognition system utilizing pressure sensors | |
Long et al. | Video-based actigraphy for monitoring wake and sleep in healthy infants: A laboratory study | |
De Sario et al. | Using AI to detect pain through facial expressions: a review | |
Li et al. | A vision-based system for in-sleep upper-body and head pose classification | |
Adamowicz et al. | Assessment of sit-to-stand transfers during daily life using an accelerometer on the lower back | |
Takahashi et al. | Estimation of respiratory rate from thermography using respiratory likelihood index | |
Molina-Rueda et al. | Test–Retest Reliability of a Conventional Gait Model for Registering Joint Angles during Initial Contact and Toe-Off in Healthy Subjects |