Do extreme values of daily-life gait characteristics provide more information about fall risk than median values?
about
A mobile cloud-based Parkinson's disease assessment system for home-based monitoring.Sit-to-Stand Transition Reveals Acute Fall Risk in Activities of Daily Living.Wearable-Sensor-Based Classification Models of Faller Status in Older AdultsDaily-Life Gait Quality as Predictor of Falls in Older People: A 1-Year Prospective Cohort Study.Fall-related gait characteristics on the treadmill and in daily lifeMotor Performance and Physical Activity as Predictors of Prospective Falls in Community-Dwelling Older Adults by Frailty Level: Application of Wearable Technology.Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features.Comparison between clinical gait and daily-life gait assessments of fall risk in older people.Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry.The effects of unexpected mechanical perturbations during treadmill walking on spatiotemporal gait parameters, and the dynamic stability measures by which to quantify postural response.
P2860
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P2860
Do extreme values of daily-life gait characteristics provide more information about fall risk than median values?
description
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name
Do extreme values of daily-lif ...... fall risk than median values?
@en
type
label
Do extreme values of daily-lif ...... fall risk than median values?
@en
prefLabel
Do extreme values of daily-lif ...... fall risk than median values?
@en
P2860
P50
P356
P1476
Do extreme values of daily-lif ...... fall risk than median values?
@en
P2860
P356
10.2196/RESPROT.3931
P50
P577
2015-01-05T00:00:00Z