Novel method for stride length estimation with body area network accelerometers

  title={Novel method for stride length estimation with body area network accelerometers},
  author={Eladio Martin},
  journal={2011 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems},
  • E. Martin
  • Published 7 March 2011
  • Computer Science
  • 2011 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems
Gait analysis using wireless accelerometers deployed as body area networks can provide valuable information for multiple health-related applications. Within this field, stride length estimation represents a difficult task. In this paper we present a novel method to estimate stride length through the application of the wavelet transform to the signal obtained from a wireless accelerometer on the waist. We also introduce a novel metric to determine the level of the wavelet transform detail… 

Figures and Tables from this paper

Integration of smartphones and webcam for the measure of spatio-temporal gait parameters

The accelerometer signal as captured by the 3D sensor embedded in one smartphone, and the position of colored markers derived by the webcam frames, are used for the computation of spatial-temporal parameters of gait.

Webcam and Smartphone for the Measure of Spatial-Temporal Parameters of Gait for Treadmill Use

The accelerometer signal captured by the 3D sensor embedded in one smartphone, and the position of coloured markers extracted from the analysis of the webcam frames, are used for the computation of spatial-temporal parameters of gait.

Adaptation of Customized Measurement of Stride Length in Smart Device

Exercise such as walking is helpful to manage one`s own weight and to counter life habit diseases such as obesity. Calorie consumption is usually calculated based on the distance walked. One way to

Measurement method of determining natural and unnatural gaits using autocorrelation coefficients

An algorithm that can determine whether human walking is natural or unnatural, by comparing the autocorrelation coefficients of the left and right foot is developed, which accurately distinguished natural and unnatural walking with 80% and 60% accuracy respectively.

Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review

A systematic review of current techniques for quantitative gait analysis is provided and key metrics for evaluating both existing and emerging methods for qualifying the gait features extracted from wearable sensors are proposed.

Estimation of gait stability based on accelerometer signals

An estimation of gait stability based on accelerometer signal is presented and shows that the stability decreases with age, as expected, since the authors' neuromotor system deteriorates with age.

Linking Computer Vision with Off-the-Shelf Accelerometry through Kinetic Energy for Precise Localization

This paper makes use of a single off-the-shelf accelerometer on the waist to precisely obtain the velocity of the user and links the accelerometry data with the computer vision part of the system, where it employs segmentation of local regions of motion in the motion history image to estimate movement.

Comparison and adaptation of step length and gait speed estimators from single belt worn accelerometer positioned on lateral side of the body

A user friendly position is proposed to place the accelerometer and six step length estimators are compared considering the proposed sensor placement in a preliminary database of healthy volunteers and a comparison shows that the adapted estimators improve the performance and reduce errors in respect of the original methods applied in the new sensor location.

Methods and models in signal processing for gait analysis using waist-worn accelerometer : a contribution to Parkinson's disease

Thesis has been developed in the framework of, and according to, the rules of the Erasmus Mundus Joint Doctorate on Interactive and Cognitive Environments EMJD ICE [FPA n° 2010-0012]



A Wearable Acceleration Sensor System for Gait Recognition

The preliminary results indicate that it is possible to recognize users based on their gait acceleration, and 1-nearest neighbor is used for individual identification.

Walking speed and slope estimation using shank-mounted inertial measurement units

This paper studied the feasibility of walking speed and slope estimation using shank-mounted inertial measurement units, and proposed a real-time stride-by-stride walking speed and slope estimation

A practical gait analysis system using gyroscopes.

A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU

This paper uses low-performance Micro-Electro-Mechanical inertial sensors attached to the foot of a person, and describes, implements and compares several of the most relevant algorithms for step detection, stride length, heading and position estimation.

Long-term unrestrained measurement of stride length and walking velocity utilizing a piezoelectric gyroscope

  • S. Miyazaki
  • Engineering
    IEEE Transactions on Biomedical Engineering
  • 1997
The purpose of this study was to develop a device with the following design criteria: lightweight, easy attachment, little hindrance to the natural gait pattern, sufficient memory to record for one day, and practicality in clinical use.

Pedestrian Dead Reckoning Based on Activity Recognition and Stride Assessment

This paper addressed an approach of low cost pedestrian dead reckoning by using different idea from traditional dead reckoning.Activity recognition using support vector machines(SVM) was realized by

Indoor Positioning System Using Accelerometry and High Accuracy Heading Sensors

The heading problem is resolved by using one deg/hour ring laser gyros and a tactical-grade IMU is used to provide accurate heading information, and accelerometers are used only for step occurrence detection.

A Step, Stride and Heading Determination for the Pedestrian Navigation System

Recently, several simple and cost-effective pedestrian navigation systems (PNS) have been introduced. These systems utilized accelerometers and gyros in order to determine step, stride and heading.