AIMC Topic: Accidental Falls

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A New Approach to Fall Detection Based on Improved Dual Parallel Channels Convolutional Neural Network.

Sensors (Basel, Switzerland) Jun 24, 2019
Falls are the major cause of fatal and non-fatal injury among people aged more than 65 years. Due to the grave consequences of the occurrence of falls, it is necessary to conduct thorough research on falls. This paper presents a method for the study ...
Discriminant Analysis Electromyography Pattern Recognition, Automated Accidental Falls Support Vector Machine Humans Neural Networks, Computer
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Fast and automatic assessment of fall risk by coupling machine learning algorithms with a depth camera to monitor simple balance tasks.

Journal of neuroengineering and rehabilitation Jun 11, 2019
BACKGROUND: Falls in the elderly constitute a major health issue associated to population ageing. Current clinical tests evaluating fall risk mostly consist in assessing balance abilities. The devices used for these tests can be expensive or inconven...
Humans Machine Learning Female Aged Accidental Falls Aged, 80 and over Postural Balance Wearable Electronic Devices Adult Exercise Therapy Male
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Accelerometer-Based Human Fall Detection Using Convolutional Neural Networks.

Sensors (Basel, Switzerland) Apr 6, 2019
Human falls are a global public health issue resulting in over 37.3 million severe injuries and 646,000 deaths yearly. Falls result in direct financial cost to health systems and indirectly to society productivity. Unsurprisingly, human fall detectio...
Neural Networks, Computer Machine Learning Algorithms Humans Deep Learning Accidental Falls Biosensing Techniques
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Development of a Strategy to Predict and Detect Falls Using Wearable Sensors.

Journal of medical systems Apr 4, 2019
Falls are a prevalent problem in actual society. Some falls result in injuries and the cost associated with their treatment is high. This is a complex problem that requires several steps in order to be tackled. Firstly, it is crucial to develop strat...
Humans Neural Networks, Computer Algorithms Female Principal Component Analysis Gait Locomotion Accidental Falls Wearable Electronic Devices ROC Curve Young Adult Adult Male
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Falls Risk Classification of Older Adults Using Deep Neural Networks and Transfer Learning.

IEEE journal of biomedical and health informatics Mar 27, 2019
Prior research in falls risk classification using inertial sensors has relied on the use of engineered features, which has resulted in a feature space containing hundreds of features that are likely redundant and possibly irrelevant. In this paper, w...
Signal Processing, Computer-Assisted Accelerometry Adult Male Middle Aged ROC Curve Smartphone Accidental Falls Adolescent Aged Aged, 80 and over Young Adult Humans Neural Networks, Computer Female
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Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches.

Journal of biomedical informatics Jan 9, 2019
BACKGROUND: Natural language processing (NLP) of health-related data is still an expertise demanding, and resource expensive process. We created a novel, open source rapid clinical text mining system called NimbleMiner. NimbleMiner combines several m...
Humans Machine Learning Natural Language Processing Electronic Health Records Data Mining Accidental Falls
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A prototype of knowledge-based patient safety event reporting and learning system.

BMC medical informatics and decision making Dec 7, 2018
BACKGROUND: Patient falls, the most common safety events resulting in adverse patient outcomes, impose significant costs and have become a great burden to the healthcare community. Current patient fall reporting systems remain in the early stage that...
Information Storage and Retrieval Patient Safety Humans Accidental Falls Knowledge Bases
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Use of a robotic walking aid in rehabilitation to reduce fear of falling is feasible and acceptable from the end user's perspective: A randomised comparative study.

Maturitas Nov 17, 2018
Objectives To determine the acceptability and feasibility of the use of a robotic walking aid to support the work of physiotherapists in reducing fear of falling in the rehabilitation of elderly patients with 'psychomotor disadaptation' (the most sev...
Attitude of Health Personnel Accidental Falls Robotics Exercise Therapy Fear Aged, 80 and over Walking Patient Acceptance of Health Care Male Humans Feasibility Studies Surveys and Questionnaires Psychomotor Disorders Female Aged
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Economic benefits of microprocessor controlled prosthetic knees: a modeling study.

Journal of neuroengineering and rehabilitation Sep 5, 2018
BACKGROUND: Advanced prosthetic knees allow for more dynamic movements and improved quality of life, but payers have recently started questioning their value. To answer this question, the differential clinical outcomes and cost of microprocessor-cont...
Quality of Life Accidental Falls United States Humans Robotics Knee Prosthesis Medicare Amputees Cost-Benefit Analysis Microcomputers Prosthesis Design
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Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

Scientific reports May 8, 2018
In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clinical, demographic and neuroimaging data from two independent initiatives (University of Michigan and Tel Aviv Sourasky Medical Center). Using machine l...
Neuroimaging Accidental Falls Aged Gait Disorders, Neurologic Postural Balance Logistic Models Male Humans Gait Support Vector Machine Models, Theoretical Middle Aged Machine Learning Parkinson Disease Female
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