Development of Fall Prediction Model for Older Adults by Analysis of Walking Patterns Based on Multi-faceted Biosignal Data
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Gait analysis
研究概览
简要总结
This study aimed to develop a fall prediction model for older adults by measuring the multi-faceted biosignal data to classify the walking patterns and by identifying causal relationships with the variables that affect the fall.
详细描述
This study aimed to develop a fall prediction model by measuring the multi-paceted biosignal data for the elderly's physical function and walking to classify the walking patterns of the elderly, and by identifying causal relationships and influences with the variables that affect the fall.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 65 Years 至 84 Years（Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Community seniors aged 65 to 84 years
- •A person who has no history of central nervous system disease
排除标准
- •Older adults who are unable to walk independently due to vision loss, fractures, etc.
- •An elderly person who had musculoskeletal history that could cause problems in the function of the lower extremities, such as fractures, within three months before recruitment;
- •In case it is difficult to understand the task due to severe cognitive impairment (Korean simplified mental health examination, K-MMSE score 10 or less)
- •In the event of a serious mental illness, such as schizophrenia or bipolar disorder;
- •In case of severe dizziness and difficulty in pedestrian inspection
- •Persons not eligible for examination
结局指标
主要结局
Gait analysis
时间窗: 1 hour
Gait analysis is a process of measuring and evaluating the walking patterns of patients by using surface electromyograph and motion analysis system. All participants perform overground walking to assess the change of kinematic, kinetic and muscle activation using a motion analysis and surface EMG
次要结局
- 10 meter walk test (10MWT)(5 minutes)
- Change on metabolic energy expenditure(15 minutes)
- Change on muscle activity(30 minutes)
- Short Physical Performance Battery (SPPB)(5 minutes)
- 6 minutes walking test (6MWT)(6 minutes)
- Fall Efficacy Scale (FES)(5 minutes)
- The Timed Up and Go test (TUG)(5 minutes)
- Change on brain activity(30 minutes)
- Four Square Step Test (FSST)(5 minutes)
- Modified Bathel index (MBI)(5 minutes)
研究者
Yun-Hee Kim
Principal Investigator
Samsung Medical Center