Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty

Aminian, Kamiar; Rezakhanlou, Karen; Andres, Eduardo De; Fritsch, Carlo; Leyvraz, Pierre-François; Robert, Philippe

doi:10.1007/bf02513368

Cited by 149 publications

(105 citation statements)

References 15 publications

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“…However, these approaches do not yield an exact identification of individual stride cycles such as required for the analysis of mean electromyography (EMG) signals or angular joint movements. Successive foot contacts can be detected from accelerations of the thigh, foot or shank [14,15]. However, this detection is not always easy [15], and, even if foot contacts are successfully detected, it may not always be possible or practical to mount accelerometers on both legs.…”

Section: Introductionmentioning

confidence: 99%

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

2003

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Section: Introductionmentioning

confidence: 99%

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

2003

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“…Average gait speed of approximately 1 m/s three months after surgery were also reported in [30]. According to [31] the greatest improvements in gait speed are observed within the first three months post-op.…”

Section: Discussionmentioning

confidence: 78%

Assessment of Gait Symmetry and Gait Normality Using Inertial Sensors: In-Lab and In-Situ Evaluation

Sant'Anna

Wickström

Eklund

et al. 2013

Biomedical Engineering Systems and Technologies

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Abstract. Quantitative gait analysis is a powerful tool for the assessment of a number of physical and cognitive conditions. Unfortunately, the costs involved in providing in-lab 3D kinematic analysis to all patients is prohibitive. Inertial sensors such as accelerometers and gyroscopes may complement in-lab analysis by providing cheaper gait analysis systems that can be deployed anywhere. The present study investigates the use of inertial sensors to quantify gait symmetry and gait normality. The system was evaluated in-lab, against 3D kinematic measurements; and also in-situ, against clinical assessments of hip-replacement patients. Results show that the system not only correlates well with kinematic measurements but it also corroborates various quantitative and qualitative measures of recovery and health status of hip-replacement patients.

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“…In order to evaluate the performance of the proposed method with regards to previous approaches, a peakdetection based method for detecting HS and TO was implemented [28]. This method was chosen over a more recent work [6] because it is based on the same principles but seems to be less dependent on optimizing parameters, and therefore more robust to different data sets.…”

Section: Experimental Set-upmentioning

confidence: 99%

“…This method was chosen over a more recent work [6] because it is based on the same principles but seems to be less dependent on optimizing parameters, and therefore more robust to different data sets. The method presented in [28] was implemented with a slight modification in order to cope with difference in sensor placement. At each iteration, the interval used to narrow down on the location of the peaks was changed to a window ten-samplewide centered at the previous peak location.…”

Section: Experimental Set-upmentioning

confidence: 99%

A Linguistic Approach to the Analysis of Accelerometer Data for Gait Analysis

Sant'Anna¹,

Wickström²

2010

Mechatronic Systems and Control

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There is evidence that many cognitive conditions affect the human motor system. Gait analysis has lately been used as a means of studying this physical-cognitive correlation. The development of gait analysis systems, able to record and analyze gait during normal daily activities and in uncontrolled environment, is an important addition to this area of research. Lately, linguistic approaches have been studied as means to achieve activity classification from vision sensors. The present work aims to extend the linguistic approach to achieve quantitative analysis of gait from accelerometer data. The proposed method can be used to extend the Human Activity Language framework to include the analysis of inertial sensors such as accelerometers. Results show that the proposed method is more accurate and robust than previous methods and can be used to extract a number of clinically relevant gait measurements. A novel symmetry index is presented to exemplify how the proposed method is able to extract more information from accelerometer signals than previous methods.

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Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty

Cited by 149 publications

References 15 publications

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking

Assessment of Gait Symmetry and Gait Normality Using Inertial Sensors: In-Lab and In-Situ Evaluation

A Linguistic Approach to the Analysis of Accelerometer Data for Gait Analysis

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