Accelerometry-Based Gait Characteristics Evaluated Using a Smartphone and Their Association with Fall Risk in People with Chronic Stroke

Isho, Takuya; Tashiro, Hideyuki; Usuda, Shigeru

doi:10.1016/j.jstrokecerebrovasdis.2015.02.004

Cited by 50 publications

(55 citation statements)

References 40 publications

(46 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reliability of an acceleration measurement device similar to the PGR, i.e., the smartphone, has been evaluated in post-stroke patients by several authors23, 24 ) . The previous studies comparable to the present investigation have calculated the reliability of smartphone-based gait analysis tools.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Retraction: Intra-rater and inter-rater reliability of the portable gait rhythmogram in post-stroke patients

et al. 2017

View full text Add to dashboard Cite

[Purpose] Gait analysis, such as portable gait rhythmogram (PGR) provides objective information that helps in the quantitative evaluation of human locomotion. The purpose of this study was to assess the reliability of PGR in post-stroke patients. [Subjects and Methods] Two raters (A and B) examined 44 post-stroke patients. To assess intra-rater reliability, rater A tested subjects on three separate occasions (Days 1, 2, and 3). To assess inter-rater reliability, raters A and B independently tested participants on the same occasion (Day 3). [Results] There was no significant systematic bias between test occasions or raters. Intraclass correlation coefficient values were 0.93−0.97 for intra-rater reliability at both the comfortable speed and maximum speed, and 0.97−0.98 (comfortable speed) and 0.87−0.99 (maximum speed) for inter-rater reliability. The standard error was 1.25−1.49 (comfortable speed) and 1.62−1.77 (maximum speed) for intra-rater investigation, and 1.04−1.32 (comfortable speed) and 0.91−1.26 (maximum speed) for inter-rater investigation. At the 90% confidence level, the minimum detectable change ranged from 2.9−4.1%, and the error of an individual’s score at a given time point ranged from ±2.1−2.9%. [Conclusion] Based on this excellent reliability of the PGR in post-stroke patients, it can be recommended as a simple test of gait analysis in this population.

show abstract

Section: Discussionmentioning

confidence: 99%

“…(5) The excellent inter-rater reliability demonstrates that a 10-minute rest period can be used between the practice and recorded trials. Unlike accelerometry measurement using a smartphone23, 24 ) , the PGR does not currently allow such a rest period.…”

Section: Discussionmentioning

confidence: 99%

Retraction: Intra-rater and inter-rater reliability of the portable gait rhythmogram in post-stroke patients

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Mobile phones have not only been used to detect body movement and orientation but also to identify abnormal physical behaviour, and especially gait [12,[23][24][25], fall [26][27][28][29], movement transitions [30,31] and postural instability or balance [32][33][34]. Furthermore, specific activities of daily relevance such as sleeping have also been inferred by analyzing mobile phone usage patterns [35,36].…”

Section: Physical Activity Sensingmentioning

confidence: 99%

Human Behaviour Analysis through Smartphones

et al. 2018

View full text Add to dashboard Cite

Human behaviour analysis through smartphone devices has been an active field for more than a decade and there are still a lot of key aspects to be addressed. This paper surveys the state-of-the-art in human behaviour analysis based on smartphones. We categorise prior works into four main sensing modalities related to physical, cognitive, emotional and social behaviour. Finally, we conclude with the outcomes of this survey and we illustrate our ideas for future research in the area of human behaviour understanding.

show abstract

“…Slower walking speeds are associated with decreased quality of life, increased hospitalization and risk of death [4,5]. One common cause of falls in elderly populations and other clinical groups is the improper shifting of weight during forward walking [6,7,8]. Elucidation of the factors that lead to instability for these populations necessitates investigations into both the active control and passive mechanisms that enable healthy humans to maintain gait stability across a range of walking speeds.…”

Section: Introductionmentioning

confidence: 99%

Upper body and ankle strategies compensate for reduced lateral stability at very slow walking speeds

Best

2020

Preprint

View full text Add to dashboard Cite

At the typical walking speeds of healthy humans, step placement seems to be the primary strategy to maintain gait stability, with ankle torques and upper body momentum providing additional compensation. The average walking speeds of populations with an increased risk of falling, however, are much slower and may require differing control strategies. The purpose of this study was to analyze mediolateral gait stability and the contributions of the different control strategies at very slow walking speeds. We analyzed an open dataset including kinematics and kinetics from eight healthy subjects walking at speeds from 0.1 to 0.6 m/s as well as a self-selected speed. As gait speed slowed, we found that the margin of stability decreased linearly. Increased lateral excursions of the extrapolated centre of mass, caused by increased lateral excursions of the trunk, were not compensated for by an equivalent increase in the lateral centre of pressure, leading to decreased margin of stability. Additionally, both the ankle eversion torque and hip abduction torque at the minimum margin of stability event increased at the same rate as gait speed slowed. These results suggest that the contributions of both the ankle and the upper body to stability are more crucial than stepping at slow speeds, which have important implications for populations with slow gait and limited motor function.

show abstract

Accelerometry-Based Gait Characteristics Evaluated Using a Smartphone and Their Association with Fall Risk in People with Chronic Stroke

Cited by 50 publications

References 40 publications

Retraction: Intra-rater and inter-rater reliability of the portable gait rhythmogram in post-stroke patients

Retraction: Intra-rater and inter-rater reliability of the portable gait rhythmogram in post-stroke patients

Human Behaviour Analysis through Smartphones

Upper body and ankle strategies compensate for reduced lateral stability at very slow walking speeds

Contact Info

Product

Resources

About