Literature DB >> 25831990

Head and pelvis stride-to-stride oscillations in gait: validation and interpretation of measurements from wearable accelerometers.

Matthew A D Brodie1, Tim R Beijer, Colleen G Canning, Stephen R Lord.   

Abstract

Unstable gait is a risk factor for falls. Wearable accelerometers enable remote monitoring of daily walking. Here, new methods for measuring stride-to-stride oscillations are validated against optical motion capture, normative data determined, and dependency on walking speed investigated. Walks by 13 young people (mean age 32 years) at fast, usual, and slow speeds were completed. Accelerometers were attached to the head and pelvis and stride-to-stride oscillation velocity and displacement were measured. Continuous tilt corrections were applied, filter cut-offs scaled by step frequency, and thresholds optimized using optical motion capture as a reference. Oscillations depended on walking speed, accelerometer placement, and measurement axis. Vertical oscillations increased with walking speed (Pearson's r = 0.78-0.89) and were the most accurate (1.4-2.3% error). Mediolateral or anterioposterior oscillations were less accurate (5.9-19.5% error) and had more complex relationships with walking speed (increasing, decreasing, uncorrelated, and/or 'U-shaped' minimum at usual speed). In healthy gait, the head and pelvis undergo regular oscillations, measurable with accelerometers. The results suggest head oscillations in the transverse plane are attenuated by the trunk, and there may be advantages in minimizing stride-to-stride oscillations that coincide with self-selected usual pace. These methods may prove useful for remote assessment of changing health, mental status, and/or fall risk.

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Mesh:

Year:  2015        PMID: 25831990     DOI: 10.1088/0967-3334/36/5/857

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  11 in total

1.  Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different.

Authors:  Matthew A D Brodie; Milou J M Coppens; Stephen R Lord; Nigel H Lovell; Yves J Gschwind; Stephen J Redmond; Michael Benjamin Del Rosario; Kejia Wang; Daina L Sturnieks; Michela Persiani; Kim Delbaere
Journal:  Med Biol Eng Comput       Date:  2015-08-06       Impact factor: 2.602

2.  IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms.

Authors:  Gerasimos Bastas; Joshua J Fleck; Richard A Peters; Karl E Zelik
Journal:  Gait Posture       Date:  2018-05-22       Impact factor: 2.840

Review 3.  Objective falls-risk prediction using wearable technologies amongst patients with and without neurogenic gait alterations: a narrative review of clinical feasibility.

Authors:  Callum M W Betteridge; Pragadesh Natarajan; R Dineth Fonseka; Daniel Ho; Ralph Mobbs; Wen Jie Choy
Journal:  Mhealth       Date:  2021-10-20

4.  Pain, balance, and mobility in people 1 year after total knee arthroplasty: a non-randomized cross-sectional pilot study contrasting posterior-stabilized and medial-pivot designs.

Authors:  Cathy W T Lo; Matthew A Brodie; William W N Tsang; Stephen R Lord; Chun-Hoi Yan; Arnold Y L Wong
Journal:  Pilot Feasibility Stud       Date:  2022-06-28

5.  Quantification of upper body movements during gait in older adults and in those with Parkinson's disease: impact of acceleration realignment methodologies.

Authors:  Christopher Buckley; Brook Galna; Lynn Rochester; Claudia Mazzà
Journal:  Gait Posture       Date:  2016-12-02       Impact factor: 2.840

6.  Multi-Functional Soft Strain Sensors for Wearable Physiological Monitoring.

Authors:  Josie Hughes; Fumiya Iida
Journal:  Sensors (Basel)       Date:  2018-11-08       Impact factor: 3.576

7.  Assessment of a Robotic Walker in Older Adults With Parkinson's Disease in Daily Living Activities.

Authors:  Sergio D Sierra M; Daniel E Garcia A; Sophia Otálora; María Camila Arias-Castro; Alejandro Gómez-Rodas; Marcela Múnera; Carlos A Cifuentes
Journal:  Front Neurorobot       Date:  2021-12-14       Impact factor: 2.650

8.  Smart Eyeglasses: A Valid and Reliable Device to Assess Spatiotemporal Parameters during Gait.

Authors:  Justine Hellec; Frédéric Chorin; Andrea Castagnetti; Olivier Guérin; Serge S Colson
Journal:  Sensors (Basel)       Date:  2022-02-04       Impact factor: 3.576

9.  Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion.

Authors:  Evangelia-Regkina Symeonidou; Andrew D Nordin; W David Hairston; Daniel P Ferris
Journal:  Sensors (Basel)       Date:  2018-04-03       Impact factor: 3.576

10.  Evaluation of Physical Interaction during Walker-Assisted Gait with the AGoRA Walker: Strategies Based on Virtual Mechanical Stiffness.

Authors:  Sergio D Sierra M; Marcela Múnera; Thomas Provot; Maxime Bourgain; Carlos A Cifuentes
Journal:  Sensors (Basel)       Date:  2021-05-07       Impact factor: 3.576

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