Nothing Special   »   [go: up one dir, main page]

Warunsin et al., 2022 - Google Patents

Wristband fall detection system using deep learning

Warunsin et al., 2022

View PDF
Document ID
2743438234686855070
Author
Warunsin K
Phairoh T
Publication year
Publication venue
2022 7th international conference on computer and communication systems (ICCCS)

External Links

Snippet

Fall is one of the significant problems threatening older people. Ambient Assisted Living (AAL) is equipment and process for supporting older people's independent and safe living. AAL includes elderly fall detection. The life of older people will be safe if rescue comes to …
Continue reading at www.researchgate.net (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
    • G08SIGNALLING
    • G08BSIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00Alarms responsive to a single specified undesired or abnormal operating condition and not elsewhere provided for
    • G08B21/02Alarms for ensuring the safety of persons
    • G08B21/04Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0438Sensor means for detecting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Doukas et al. Emergency fall incidents detection in assisted living environments utilizing motion, sound, and visual perceptual components
Khan et al. Review of fall detection techniques: A data availability perspective
Koshmak et al. Challenges and issues in multisensor fusion approach for fall detection
Lara et al. A survey on human activity recognition using wearable sensors
Sannino et al. A supervised approach to automatically extract a set of rules to support fall detection in an mHealth system
Nandy et al. Detailed human activity recognition using wearable sensor and smartphones
Olsen et al. Smartphone accelerometer data used for detecting human emotions
Warunsin et al. Wristband fall detection system using deep learning
Shi et al. Fall Detection Algorithm Based on Triaxial Accelerometer and Magnetometer.
Ramachandran et al. Machine learning-based techniques for fall detection in geriatric healthcare systems
Abdelmoneem et al. A survey on multi-sensor fusion techniques in IoT for healthcare
Casilari et al. A wearable fall detection system using deep learning
Cahoolessur et al. Fall detection system using XGBoost and IoT
Hong et al. A low-cost real-time IoT human activity recognition system based on wearable sensor and the supervised learning algorithms
CN117409538A (en) Wireless fall-prevention alarm system and method for nursing
Zhang et al. A novel fuzzy logic algorithm for accurate fall detection of smart wristband
Rekha et al. Methodical activity recognition and monitoring of a person through smart phone and wireless sensors
Jansi et al. Remote monitoring of children with chronic illness using wearable vest
Parmar et al. A comprehensive survey of various approaches on human fall detection for elderly people
Pillai et al. Wearable sensor and machine learning model-based fall detection system for safety of elders and movement disorders
Rashidpour et al. Fall detection using adaptive neuro-fuzzy inference system
Kabir et al. Secure Your Steps: A Class-Based Ensemble Framework for Real-Time Fall Detection Using Deep Neural Networks
Liang et al. Multimodal monitoring of activities of daily living for elderly care
Sundaravadivel et al. Easy-assist: An intelligent haptic-based affective framework for assisted living
Ojetola Detection of human falls using wearable sensors