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Journal Article
Sensors (Switzerland), ISSN 1424-8220, 02/2014, Volume 14, Issue 2, pp. 2756 - 2775
We propose an automatic, privacy-preserving, fall detection method for indoor environments, based on the usage of the Microsoft Kinect((R)) depth sensor, in an... 
Kinect | Human recognition | Elderly care | Fall detection | Depth frame | ELECTROCHEMISTRY | CHEMISTRY, ANALYTICAL | INSTRUMENTS & INSTRUMENTATION | fall detection | human recognition | depth frame | elderly care
Journal Article
Neurocomputing, ISSN 0925-2312, 01/2013, Volume 100, pp. 144 - 152
Fall detection is a major challenge in the public health care domain, especially for the elderly, and reliable surveillance is a necessity to mitigate the... 
Patient monitoring | Healthcare | Visual surveillance | Vision-based systems | Fall detection | SYSTEM | VIDEO | IMPLEMENTATION | SENSOR | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms | Surveillance equipment | Statistics | Detectors
Journal Article
Pervasive and Mobile Computing, ISSN 1574-1192, 12/2012, Volume 8, Issue 6, pp. 883 - 899
Falls are a major cause of injuries and hospital admissions among elderly people. Thus, the caregiving process and the quality of life of older adults can be... 
Pervasive healthcare | Fall detection | Wearable sensors | COMPUTER SCIENCE, INFORMATION SYSTEMS | TRIAXIAL ACCELEROMETER | PEOPLE | TELECOMMUNICATIONS | Detectors
Journal Article
BioMedical Engineering Online, ISSN 1475-925X, 06/2016, Volume 15, Issue 1, p. 61
Pre-impact fall detection has been proposed to be an effective fall prevention strategy. In particular, it can help activate on-demand fall injury prevention... 
Pre-impact fall detection | Fall accidents | Fall prevention | SYSTEM | GAIT | ENGINEERING, BIOMEDICAL | IMPLEMENTATION | SENSOR | TRIAXIAL ACCELEROMETER | PEOPLE | DETECTION ALGORITHM | Mechanical Phenomena | Algorithms | Monitoring, Ambulatory - methods | Time Factors | Humans | Accidental Falls | Prevention | Falls (Accidents) | Usage | Research | Risk factors
Journal Article
BioMedical Engineering Online, ISSN 1475-925X, 07/2013, Volume 12, Issue 1, pp. 66 - 66
Since falls are a major public health problem among older people, the number of systems aimed at detecting them has increased dramatically over recent years.... 
Health care | Review | Assistive technology | Fall detection | Smart phones | FEAR | OLDER-PEOPLE | VIDEO | ENGINEERING, BIOMEDICAL | ACCELEROMETERS | SENSOR | Monitoring, Physiologic | Cell Phone | Humans | Accelerometry | Accidental Falls | Activities of daily living | Analysis | Machine learning | Aged | Public health | Biomedical engineering | Studies | Smartphones | Older people | Mortality | Trends | Injuries | Methods | Quality of life
Journal Article
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, ISSN 1094-687X, 08/2007, Volume 2007, pp. 1663 - 1666
Conference Proceeding
Journal of Geriatric Physical Therapy, ISSN 1539-8412, 10/2014, Volume 37, Issue 4, pp. 178 - 196
Journal Article
IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, 03/2015, Volume 62, Issue 3, pp. 865 - 875
We propose in this paper the use of Wavelet transform (WT) to detect human falls using a ceiling mounted Doppler range control radar. The radar senses any... 
Wavelet transforms | Time-frequency analysis | Radar detection | fall detection | wavelet | classifier | Feature extraction | Doppler radar | Classifier | ENGINEERING, BIOMEDICAL | Monitoring, Physiologic | Algorithms | Wavelet Analysis | Humans | Middle Aged | Radar | Adult | Female | Male | ROC Curve | Accidental Falls | Analysis | Doppler effect | Wavelet | Ceilings | Mathematical analysis | Classification
Journal Article
Medical Engineering and Physics, ISSN 1350-4533, 2016, Volume 39, pp. 12 - 22
Journal Article