AIMC Topic: 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...
Patient Safety Accidental Falls Knowledge Bases Information Storage and Retrieval Humans
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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...
Feasibility Studies Female Exercise Therapy Fear Aged Humans Aged, 80 and over Accidental Falls Male Robotics Surveys and Questionnaires Walking Patient Acceptance of Health Care Attitude of Health Personnel Psychomotor Disorders
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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...
United States Robotics Amputees Humans Quality of Life Accidental Falls Knee Prosthesis Microcomputers Prosthesis Design Medicare Cost-Benefit Analysis
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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...
Gait Neuroimaging Gait Disorders, Neurologic Support Vector Machine Parkinson Disease Postural Balance Aged Male Middle Aged Accidental Falls Logistic Models Models, Theoretical Humans Machine Learning Female
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Identifying Falls Risk Screenings Not Documented with Administrative Codes Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Quality reporting that relies on coded administrative data alone may not completely and accurately depict providers' performance. To assess this concern with a test case, we developed and evaluated a natural language processing (NLP) approach to iden...
Natural Language Processing Humans Information Storage and Retrieval Algorithms Risk Assessment Clinical Coding Electronic Health Records Accidental Falls Mass Screening
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Deep Learning for Fall Detection: Three-Dimensional CNN Combined With LSTM on Video Kinematic Data.

IEEE journal of biomedical and health informatics Feb 20, 2018
Fall detection is an important public healthcare problem. Timely detection could enable instant delivery of medical service to the injured. A popular nonintrusive solution for fall detection is based on videos obtained through ambient camera, and the...
Accidental Falls Image Processing, Computer-Assisted Support Vector Machine Neural Networks, Computer Humans Video Recording Biomechanical Phenomena Human Activities Deep Learning
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On the Comparison of Wearable Sensor Data Fusion to a Single Sensor Machine Learning Technique in Fall Detection.

Sensors (Basel, Switzerland) Feb 14, 2018
In the context of the ageing global population, researchers and scientists have tried to find solutions to many challenges faced by older people. Falls, the leading cause of injury among elderly, are usually severe enough to require immediate medical...
Algorithms Humans Accidental Falls Machine Learning Wearable Electronic Devices
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An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.

Sensors (Basel, Switzerland) Dec 22, 2017
The fixed-size non-overlapping sliding window (FNSW) and fixed-size overlapping sliding window (FOSW) approaches are the most commonly used data-segmentation techniques in machine learning-based fall detection using accelerometer sensors. However, th...
Accidental Falls Humans Support Vector Machine Machine Learning Accelerometry Algorithms
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A robotic system for delivering novel real-time, movement dependent perturbations.

Gait & posture Sep 1, 2017
Perturbations are often used to study movement control and balance, especially in the context of falling. Most often, discrete perturbations defined prior to the experiment are used to mimic external disturbances to balance. However, the largest prop...
Adult Biomechanical Phenomena Male Accidental Falls Computer Systems Robotics Humans Female Young Adult Postural Balance Movement
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Validation of accuracy of SVM-based fall detection system using real-world fall and non-fall datasets.

PloS one Jul 5, 2017
Falls are a major cause of injuries and deaths in older adults. Even when no injury occurs, about half of all older adults who fall are unable to get up without assistance. The extended period of lying on the floor often leads to medical complication...
Humans Algorithms Reproducibility of Results Monitoring, Ambulatory Accidental Falls Aged Support Vector Machine Accelerometry Aged, 80 and over Activities of Daily Living Health Services for the Aged Adult
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