Exploration of Machine Learning to Identify Community Dwelling Older Adults with Balance Dysfunction Using Short Duration Accelerometer Data

Keyphrases

• Older Adults 100%
• Community-dwelling Older Adults 100%
• Machine Learning 100%
• Accelerometer Data 100%
• Balance Dysfunction 100%
• Fall Risk 60%
• Balance Function 60%
• Wearable Sensors 40%
• Motor Tests 40%
• Early Intervention 20%
• Knee 20%
• Reflexive 20%
• Area under the Receiver Operating Characteristic Curve 20%
• Early Diagnosis 20%
• Older Women 20%
• Health Care Costs 20%
• Normal Walking 20%
• Fall-related Injuries 20%
• Falls in Older Adults 20%
• Automated Identification 20%
• Machine Learning Techniques 20%
• Postural Response 20%
• Significant Risk Factors 20%
• Early Treatment 20%
• Fall Incidence 20%
• Supervised Machine Learning 20%
• Community-dwelling Older Women 20%
• Adverse Outcomes 20%
• Machine Algorithm 20%
• Data Sensors 20%
• Objective Identification 20%
• Injurious Falls 20%
• Validation Accuracy 20%
• Instrumented Treadmill 20%
• Gradient Boosting Machine 20%
• Wearable Data 20%
• Test Identification 20%

Medicine and Dentistry

• Community-Dwelling Older Adults 100%
• Accelerometer 100%
• Wearable Sensor 100%
• Motor Control 66%
• Health Care Cost 33%
• Injury 33%
• Early Diagnosis 33%
• Early Intervention 33%
• Hip 33%
• Cross-Validation 33%
• Knee 33%
• Adverse Outcome 33%

Nursing and Health Professions

• Accelerometer 100%
• Wearables 100%
• Early Intervention 33%
• Injury 33%
• Early Diagnosis 33%
• Receiver Operating Characteristic 33%
• Health Care Cost 33%
• Area under the Curve 33%
• Adverse Outcome 33%
• Supervised Machine Learning 33%