Developing a motion language: Gait analysis from accelerometer sensor systems

Sant'Anna, Anita Pinheiro; Wickström, Nicholas

doi:10.4108/icst.pervasivehealth2009.5913

Cited by 10 publications

(2 citation statements)

References 43 publications

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“…Only after these validation tests more detailed, qualitative statements can be made. Until then the results will be compared to results, encountered during research in corresponding technical literature and the conclusions are also referring to comparisons to other research results in the same field, but on a general level [2], [7], [8]. For the pitch angle, acceleration and pressure this means to compare minimum and maximum values as well as curve structures.…”

Section: Discussionmentioning

confidence: 99%

A multimodal approach for insole motion measurement and analysis

Jagos

Oberzaucher

Reichel

et al. 2010

Procedia Engineering

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In order to perform long-term, low-effort gait analysis an instrumented shoe insole, equipped with an embedded data processing system, a variety of sensors and a wireless data transmission module has been developed. By using specially developed signal fusion algorithms, the sensor's raw data, like pressure, 3D tilt and acceleration, is processed to provide information about the user's gait or moving behaviour. This shoe insole will also form the basis of an "easy to use" balance training system for older people, in order to help decreasing their risk of falling. A set of early prototypes, in the form of two pairs of self-designed and crafted instrumented shoe insoles, has already been developed. For the validation of their functionality a small series of tests, with five users, already took place. A specific test battery was created, consisting of ten tasks, where the stability of gait and coordinative skills were observed. The tasks were compiled from state-of-the-art mobility test and fall assessment strategies. The tests should, on the one hand, prove the stability of the hardware (to endure such testing), the reliability of the wireless connection and should at the same time show, if the procedure of walking can be reproduced from the gathered data. On the other hand these tests were used for gathering gait data from different subjects, which will be used in the future for the training of classification algorithms. Furthermore there is the opportunity that such a wearable system can be used for sophisticated running analysis with qualitative parameters. By logging and/or wirelessly transmitting information about pressure distribution, the course of e.g. the COP and the pitch angle as well as quantitative parameters like time of action, cadence and the number of steps e.g. an activity protocol can be created.

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Section: Discussionmentioning

confidence: 99%

A multimodal approach for insole motion measurement and analysis

Jagos

Oberzaucher

Reichel

et al. 2010

Procedia Engineering

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“…For explicitly extracting such multiscale deterministic and stochastic information contents, we turn to and focus on the system's fundamental structural dependency among all observed gait time series. It is clear that such structural dependency is lost to a great degree in the so-called resultant acceleration signal [14,15]:…”

Section: Introductionmentioning

confidence: 99%

From Learning Gait Signatures of Many Individuals to Reconstructing Gait Dynamics of One Single Individual

Hsieh

Wang

2020

Front. Appl. Math. Stat.

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Based on the same databases, we computationally address two seemingly highly related, in fact drastically distinct, questions via computational data-driven algorithms: 1) how to precisely achieve the big task of differentiating gait signatures of many individuals and 2) how to reconstruct an individual's complex gait dynamics in full. Our brains can "effortlessly" resolve the first question, but will definitely fail in the second one because many fine temporal scale gait patterns surely escape our eyes. Based on accelerometers' 3D gait time series databases, we link the answers toward both questions via multiscale structural dependency within gait dynamics of our musculoskeletal system. Two types of dependency manifestations are explored. We first develop simple algorithmic computing called Principle System-State Analysis for the coarse dependency in implicit forms. Principle System-State Analysis is shown to be able to efficiently classifying among many subjects. We then develop a multiscale Local-1st-Global-2nd Coding Algorithm and a landmark computing algorithm. With both algorithms, we can precisely dissect rhythmic gait cycles, and then decompose each cycle into a series of cyclic gait phases. With proper color-coding and stacking, we reconstruct and represent an individual's gait dynamics via a 3D cylinder to collectively reveal universal deterministic and stochastic structural patterns on centisecond (10 milliseconds) scale across all rhythmic cycles. This 3D cylinder can serve as "passtensor" for authentication purposes related to clinical diagnoses and cybersecurity.

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Bibliography

2021

Human Motion Capture and Identification for Assistive Systems Design in Rehabilitation

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3 Jointtype enumeration. https://msdn.microsoft.com/en-us/library/microsoft.kinect .jointtype.aspx. Accessed: 2015-05-22. 4 Kinect for windows features. https://www.microsoft.com/en-us/kinectforwindows/ meetkinect/features.aspx. Accessed: 2015-05-22. 5 Rokoko smartsuit pro. https://www.rokoko.com/en?gclid=CjwKCAjw_47YBRBxEiwAYu KdwynSSU8rlweQF-R8QBmqMjHq_aEzrUOffS7E0CYpc2pRCkeV9LAZ-xoCrT4QAvD_ BwE. Accessed: 2018-05-20. 6 Tracking users with kinect skeletal tracking. https://msdn.microsoft.com/en-us/library/ jj131025.aspx. Accessed: 2015-05-22.

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Developing a motion language: Gait analysis from accelerometer sensor systems

Cited by 10 publications

References 43 publications

A multimodal approach for insole motion measurement and analysis

A multimodal approach for insole motion measurement and analysis

From Learning Gait Signatures of Many Individuals to Reconstructing Gait Dynamics of One Single Individual

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