Literature DB >> 26609406

Reliability of the step phase detection using inertial measurement units: pilot study.

Salvatore Sessa1, Massimiliano Zecca2, Luca Bartolomeo1, Takamichi Takashima3, Hiroshi Fujimoto4, Atsuo Takanishi5.   

Abstract

The use of inertial sensors for the gait event detection during a long-distance walking, for example, on different surfaces and with different walking patterns, is important to evaluate the human locomotion. Previous studies demonstrated that gyroscopes on the shank or foot are more reliable than accelerometers and magnetometers for the event detection in case of normal walking. However, these studies did not link the events with the temporal parameters used in the clinical practice; furthermore, they did not clearly verify the optimal position for the sensors depending on walking patterns and surface conditions. The event detection quality of the sensors is compared with video, used as ground truth, according to the parameters proposed by the Gait and Clinical Movement Analysis Society. Additionally, the performance of the sensor on the foot is compared with the one on the shank. The comparison is performed considering both normal walking and deviations to the walking pattern, on different ground surfaces and with or without constraints on movements. The preliminary results show that the proposed methodology allows reliable detection of gait events, even in case of abnormal footfall and in slipping surface conditions, and that the optimal location to place the sensors is the shank.

Entities:  

Keywords:  abnormal footfall condition; gait analysis; gait event detection; human locomotion; inertial measurement units; inertial sensors; inertial systems; long-distance walking; reliability; sensor placement; slipping surface condition; step phase detection

Year:  2015        PMID: 26609406      PMCID: PMC4611174          DOI: 10.1049/htl.2014.0103

Source DB:  PubMed          Journal:  Healthc Technol Lett        ISSN: 2053-3713


  15 in total

1.  Gait phase detection and discrimination between walking-jogging activities using hidden Markov models applied to foot motion data from a gyroscope.

Authors:  Andrea Mannini; Angelo Maria Sabatini
Journal:  Gait Posture       Date:  2012-07-15       Impact factor: 2.840

2.  Hierarchical information fusion for global displacement estimation in microsensor motion capture.

Authors:  Xiaoli Meng; Zhi-Qiang Zhang; Jian-Kang Wu; Wai-Choong Wong
Journal:  IEEE Trans Biomed Eng       Date:  2013-02-22       Impact factor: 4.538

3.  Quantitative gait evaluation in the clinic.

Authors:  J L Robinson; G L Smidt
Journal:  Phys Ther       Date:  1981-03

4.  A clinical method of quantitative gait analysis. Suggestion from the field.

Authors:  K Cerny
Journal:  Phys Ther       Date:  1983-07

5.  A practical gait analysis system using gyroscopes.

Authors:  K Tong; M H Granat
Journal:  Med Eng Phys       Date:  1999-03       Impact factor: 2.242

6.  Basic gait parameters: reference data for normal subjects, 10-79 years of age.

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Journal:  J Rehabil Res Dev       Date:  1993

Review 7.  Tools for observational gait analysis in patients with stroke: a systematic review.

Authors:  Francesco Ferrarello; Valeria Anna Maria Bianchi; Marco Baccini; Gaia Rubbieri; Enrico Mossello; Maria Chiara Cavallini; Niccolò Marchionni; Mauro Di Bari
Journal:  Phys Ther       Date:  2013-06-27

8.  Epidemic of fractures during period of snow and ice.

Authors:  Z A Rális
Journal:  Br Med J (Clin Res Ed)       Date:  1981-02-21

Review 9.  Automatic fall monitoring: a review.

Authors:  Natthapon Pannurat; Surapa Thiemjarus; Ekawit Nantajeewarawat
Journal:  Sensors (Basel)       Date:  2014-07-18       Impact factor: 3.576

10.  Pedestrian navigation based on a waist-worn inertial sensor.

Authors:  Juan Carlos Alvarez; Diego Alvarez; Antonio López; Rafael C González
Journal:  Sensors (Basel)       Date:  2012-08-03       Impact factor: 3.576

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  2 in total

1.  Development of a Non-Contacting Muscular Activity Measurement System for Evaluating Knee Extensors Training in Real-Time.

Authors:  Zixi Gu; Shengxu Liu; Sarah Cosentino; Atsuo Takanishi
Journal:  Sensors (Basel)       Date:  2022-06-19       Impact factor: 3.847

2.  A Personalized Approach to Improve Walking Detection in Real-Life Settings: Application to Children with Cerebral Palsy.

Authors:  Lena Carcreff; Anisoara Paraschiv-Ionescu; Corinna N Gerber; Christopher J Newman; Stéphane Armand; Kamiar Aminian
Journal:  Sensors (Basel)       Date:  2019-12-03       Impact factor: 3.576

  2 in total

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