Effects of smartphone use during walking on kinetic gait parameters: Preliminary results of a crossover study on an instrumented treadmill

2020 ◽  
Vol 81 ◽  
pp. 82
Author(s):  
S. Durstberger ◽  
W. Klaus ◽  
P. Putz
Keyword(s):  
Crossover Study ◽  
Preliminary Results ◽  
Gait Parameters ◽  
Smartphone Use

Assessment of handwashing practices with chemical and microbiologic methods: Preliminary results from a prospective crossover study

2002 ◽  
Vol 30 (6) ◽  
pp. 334-340 ◽  
Author(s):  
Carlo Marena ◽  
Lorenzo Lodola ◽  
Marco Zecca ◽  
Anna Bulgheroni ◽  
Edoardo Carretto ◽  
...  
Keyword(s):  
Crossover Study ◽  
Preliminary Results

scholarly journals Cerebellar rTMS for postural instability in progressive supranuclear palsy: preliminary results from a crossover study

2021 ◽  
Vol 14 (6) ◽  
pp. 1620
Author(s):  
Marian Dale ◽  
Austin Prewitt ◽  
Graham Harker ◽  
Alex Stevens ◽  
Patty Carlson-Kuhta ◽  
...  
Keyword(s):  
Crossover Study ◽  
Progressive Supranuclear Palsy ◽  
Postural Instability ◽  
Preliminary Results

scholarly journals Using Embedded Sensors in Independent Living to Predict Gait Changes and Falls

2016 ◽  
Vol 39 (1) ◽  
pp. 78-94 ◽  
Author(s):  
Lorraine J. Phillips ◽  
Chelsea B. DeRoche ◽  
Marilyn Rantz ◽  
Gregory L. Alexander ◽  
Marjorie Skubic ◽  
...  
Keyword(s):  
Big Data ◽  
Gait Speed ◽  
Independent Living ◽  
Stride Length ◽  
Embedded Sensors ◽  
Sensor Systems ◽  
Preliminary Results ◽  
Gait Parameters ◽  
Cumulative Change ◽  
Over Time

This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents’ Kinect-recorded gait parameters. Over a period of 3 to 48 months, we analyzed gait parameters continuously collected for residents who actually fell ( n = 13) and those who did not fall ( n = 10). We analyzed associations between participants’ fall events ( n = 69) and pre-fall changes in in-home gait speed and stride length ( n = 2,070). Preliminary results indicate that a cumulative change in speed over time is associated with the probability of a fall ( p < .0001). The odds of a resident falling within 3 weeks after a cumulative change of 2.54 cm/s is 4.22 times the odds of a resident falling within 3 weeks after no change in in-home gait speed. Results demonstrate using sensors to measure in-home gait parameters associated with the occurrence of future falls.

scholarly journals Influences of Smartphone Use While Walking on Gait Parameters

2016 ◽  
Vol 6 (1) ◽  
pp. 35-39 ◽  
Author(s):  
AOI NAKAMURA ◽  
SHIN MURATA ◽  
KOUHEI IIDA ◽  
TOSHIKI IUCHI ◽  
KEITA SUZUKI ◽  
...  
Keyword(s):  
Gait Parameters ◽  
Smartphone Use
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