Qidwai et al., 2016 - Google Patents
Intelligent integrated instrumentation platform for monitoring long-term bedridden patientsQidwai et al., 2016
View PDF- Document ID
- 10574456686817848223
- Author
- Qidwai U
- Al-Sulaiti S
- Ahmed G
- Hegazy A
- Ilyas S
- Publication year
- Publication venue
- 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES)
External Links
Snippet
Stroke patients, as well as all those patients who are bed-bound for a long period of time, are highly susceptible to preventable secondary complications such as pressure ulcers or commonly known as bedsores. Such secondary complications may lead to progression of …
- 208000004210 Pressure Ulcer 0 abstract description 25
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
- G06F19/327—Management of hospital data, e.g. scheduling of medical staff or operation rooms, measuring the quality or efficiency of medical staff
-
- 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
- A61B5/1116—Determining posture transitions
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20220322972A1 (en) | Computer system and method for identifying a posture adopted by a subject | |
US20240046769A1 (en) | Patient risk notification system | |
US11710320B2 (en) | Patient video monitoring systems and methods for thermal detection of liquids | |
JP6053802B2 (en) | A monitoring system that monitors patients and detects patient delirium | |
Qidwai et al. | Intelligent integrated instrumentation platform for monitoring long-term bedridden patients | |
Ranasinghe et al. | Low cost and batteryless sensor-enabled radio frequency identification tag based approaches to identify patient bed entry and exit posture transitions | |
US20090099480A1 (en) | System and method for patient monitoring | |
Viriyavit et al. | Bed position classification by a neural network and bayesian network using noninvasive sensors for fall prevention | |
JP2015132963A (en) | Monitor system | |
JP2009279076A (en) | Monitoring system | |
JP3575979B2 (en) | Cared person observation device and method | |
Wai et al. | Sleeping patterns observation for bedsores and bed-side falls prevention | |
Kittipanya-Ngam et al. | Computer vision applications for patients monitoring system | |
US12133724B2 (en) | Machine vision to predict clinical patient parameters | |
Inoue et al. | Bed-exit prediction applying neural network combining bed position detection and patient posture estimation | |
JPWO2017183603A1 (en) | Monitored person monitoring system and monitored person monitoring method | |
Chen et al. | Sleep monitoring using an infrared thermal array sensor | |
CN110084081A (en) | A kind of tumble early warning realization method and system | |
Madokoro et al. | Prediction of bed-leaving behaviors using piezoelectric non-restraining sensors | |
Wai et al. | Lying posture classification for pressure ulcer prevention | |
Madokoro et al. | Bed-leaving detection using piezoelectric unrestrained sensors and its measurement system regarding QOL | |
Jacobs et al. | Increasing vigilance on the medical/surgical floor to improve patient safety | |
JP2020190889A (en) | Monitoring system for care-needing person | |
JP2020091628A (en) | Care recipient monitoring system | |
JP2009199565A (en) | Remote monitoring method for bedridden care-needing person and remote monitoring device for bedridden care-needing person |