AIMC Topic: Accidental Falls

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Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Studies in health technology and informatics Aug 21, 2019
Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity...
Machine Learning Risk Factors Risk Assessment Humans Missouri Accidental Falls Home Care Services
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Scoring Patient Fall Reports Using Quality Rubric and Machine Learning.

Studies in health technology and informatics Aug 21, 2019
Patient falls, a subcategory of patient safety events, cause further harm and anxiety to patients in healthcare systems. Patient fall reports are a valuable resource to identify safety issues that demand further attention. Still, the main challenge f...
Patient Safety Accidental Falls Writing Humans Machine Learning
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Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2019
OBJECTIVE: Geriatric syndromes such as functional disability and lack of social support are often not encoded in electronic health records (EHRs), thus obscuring the identification of vulnerable older adults in need of additional medical and social s...
Social Support Accidental Falls Frail Elderly Electronic Health Records International Classification of Diseases Aged Humans Urinary Incontinence Neural Networks, Computer Mobility Limitation Models, Statistical Natural Language Processing Health Equity
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Fall Detection for the Elderly Based on 3-Axis Accelerometer and Depth Sensor Fusion with Random Forest Classifier.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
In this paper, we propose a new fall detection method that combines 3-axis accelerometer and depth sensors. By combining vision and acceleration-derived features we managed to minimize the false detection rate that is considerably higher when the dec...
Acceleration Monitoring, Ambulatory Accelerometry Algorithms Humans Machine Learning Accidental Falls
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Deep Learning based Gait Abnormality Detection using Wearable Sensor System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Gait is an extraordinary complex function of human body that involves the activation of entire visceral nervous system, making human gait definite to various functional abnormalities. Diagnosis and treatment of such disorders prior to their developme...
Humans Deep Learning Accidental Falls Wearable Electronic Devices Gait Analysis
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Bed-Exit Prediction Applying Neural Network Combining Bed Position Detection and Patient Posture Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The work of a nurse involves tasks that can lead to serious accidents with a single mistake or miss, and thus nurses are exposed to high stress. In particular, injections, pre-medications, tube connections, and falling are factors that lead to seriou...
Posture Activities of Daily Living Movement Beds Aged Humans Risk Assessment Neural Networks, Computer Accidental Falls
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[Support for Patients and Their Family Using Artificial Intelligence].

Brain and nerve = Shinkei kenkyu no shinpo Jul 1, 2019
For patients with dementia and their family, artificial intelligence (AI) has been utilized to support diagnosis and evaluation. In addition, communication robots equipped with AI offer a way to maintain the cognitive functions of patients with demen...
Robotics Accidental Falls Communication Humans Dementia Artificial Intelligence Quality of Life Cognition
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Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

Medical care Jul 1, 2019
BACKGROUND: Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. Here we examine the potential utility o...
Aged Male Risk Assessment Electronic Health Records Female Accidental Falls Emergency Service, Hospital Humans Machine Learning Algorithms Retrospective Studies
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Pre-Impact Fall Detection Using 3D Convolutional Neural Network.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jun 1, 2019
Early fall detection is an important issue during gait rehabilitation training. This paper proposes an approach for pre-impact fall detection during gait rehabilitation training based on a 3D convolutional neural network (CNN). Firstly, pre-training ...
Accidental Falls Algorithms Gait Humans Female Rehabilitation Neural Networks, Computer Male
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Robot-based assessment of sitting and standing balance: preliminary results in Parkinson's disease.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jun 1, 2019
Postural responses to unstable conditions or perturbations are important predictors of the risk of falling and can reveal balance deficits in people with neurological disorders, such as Parkinson's Disease (PD). However, there is a lack of evidences ...
Middle Aged Humans Sitting Position Robotics Accidental Falls Female Aged Postural Balance Parkinson Disease Male Standing Position
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