Difference between revisions of "Gait events"
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− | <div style="font-size: 140%;">'''Explanation of how to extract desired data from the given .mat | + | <div style="font-size: 140%;">'''Explanation of how to extract desired data from the given .mat or .txt files:'''</div> |
There are two matrices provided, namely, '''Indoor Experiment timings''' and '''Outdoor Experiment timings''' which contain the timing information of the activities and are included in a folder called Activity Timings.zip (download link below): | There are two matrices provided, namely, '''Indoor Experiment timings''' and '''Outdoor Experiment timings''' which contain the timing information of the activities and are included in a folder called Activity Timings.zip (download link below): | ||
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*accZ - data from Z - axis | *accZ - data from Z - axis | ||
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+ | '''Link to download timing information of the activities:''' [[File:Activity Timings.zip]] | ||
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<div style="font-size: 140%;">'''This page is under construction...More information to be added soon'''</div> | <div style="font-size: 140%;">'''This page is under construction...More information to be added soon'''</div> |
Revision as of 15:01, 30 May 2016
Gait Event Detection in Real-World Environments for Long-Term Applications
This is a placeholder for an automated service that will provide temporal estimation of gait events from accelerometer signals. The service would take accelerometer data (in the specified format) as input and provide the estimated events as output.
Until this service is implemented, please send your data in the specified format to siddhartha.khandelwal@hh.se and nicholas.wickstrom@hh.se.
Specifications
Activities: Walking and running
Placement of 3-axis Accelerometer: Anywhere around the ankle in any orientation.
Sensitivity of the Accelerometer: (+-) 4g or more. Please specify. Please also check if the accelerometer signal has saturated during intense activity such as running.
Sampling Frequency: Preferred - 128 Hz [A Sampling frequency of 50Hz and above is acceptable. Please specify.]
Input data: AccX, AccY, AccZ [Accelerometer signals from the X, Y and Z axes, respectively.]
Input data format: abc.mat or abc.csv [Data in Matlab format or comma separated text file.]
NOTE: The data should consist of ONLY walking and running segments of the signal. Segments corresponding to inactivity or any other activity should be removed from the signals prior to data submission.
MAREA (Movement Analysis in Real-world Environments using Accelerometers) Gait Database
The MAREA gait database comprises of gait activities in different real-world environments as shown in the table below. 20 healthy adults (12 males and 8 females, average age: 33.4 +- 7 years, average weight: 73.2 +- 10.9 kg, average height: 172.6 +- 9.5 cm) participated in the study that was approved by the Ethical Review Board of Lund, Sweden. Each subject had a 3-axes Shimmer3 (Shimmer Research, Dublin, Ireland) accelerometer (+- 8g) attached to their waist, left wrist and left and right ankles using elastic bands and velcro straps. Figure 1 shows the position and orientation of each accelerometer at the beginning of each experiment. The X and Y axes of the accelerometer positioned on the waist and the Y and Z axes of the accelerometers positioned on the left wrist and left ankle were aligned with the sagittal and transverse planes, respectively. The accelerometer on the right ankle was casually attached without any predefined alignment to simulate a daily life scenario. The subjects were provided shoes that were instrumented with piezo-electric force sensitive resistors (FSRs), fixed at the extreme ends of the sole in order to provide the ground truth values for HS and TO. The data from accelerometer and FSRs was sampled at a frequency of 128Hz, and the FSR output was stored locally on the Shimmer3 microSD card using an external expansion board. The accelerometer signals obtained from different body locations were synchronized manually. Timings of the switch from walking to running were noted down during the experiments, in order to segregate the dataset into walking and running segments.
Subjects | Environment | Activity | Speed | Duration | Short Description |
---|---|---|---|---|---|
11 | Treadmill (flat) | Walk & run | 4km/hr - 8km/hr; increasing in steps
of 0.4km/hr every minute |
10 min | Start walking and switch to
running at self-selected speed |
Treadmill (slope) | Walk | Self-selected | 12 min | Treadmill is set to (5, 0, 10, 0, 15, 0) degree
inclinations with 2 mins at each angle | |
Indoor flat space | Walk & run | Self-selected | 6 min | Start walking and switch
to running after 3 mins | |
9 | Outdoor street | Walk & run | Self-selected | 6 min | Start walking and switch
to running after 3 mins |
There are two matrices provided, namely, Indoor Experiment timings and Outdoor Experiment timings which contain the timing information of the activities and are included in a folder called Activity Timings.zip (download link below):
- Indoor Experiment Timings: This 11(rows) x 8(columns) matrix consists of sample numbers corresponding to the start and end of an activity, for a given subject, for the Indoor Experiments, i.e.
- Treadmill (flat)
- Treadmill (slope)
- Indoor flat space.
The figure below explains how to extract the sample nos. corresponding to an activity for a given subject, from the Indoor Experiment timings matrix.
- Outdoor Experiment Timings: This 9(rows) x 3(columns) matrix consists of sample numbers corresponding to the start and end of an activity, for a given subject, for the Outdoor Street Experiments. The figure below explains how to extract the sample nos. corresponding to an activity for a given subject, from the Outdoor Experiment timings matrix.
The Subject data files are provided in two formats, namely, .mat format (Subject Data_mat format.zip) and .txt format Subject Data_txt format).zip. The naming convention of the files is: Sub<number>_<position>, where:
- <number>: stands for Subject number and ranges from 1 to 20.
- <position>: stands for the position of the accelerometer on the body as shown in Figure 1. The positions are:
- LF - Left Ankle
- RF - Right Ankle
- Wrist
- Waist
For each Subject file, eg. Sub5_RF, the accelerometer data from the 3 axis accelerometer is stored in 3 columns (separated using comma in the .txt files), each named as:
- accX - data from X - axis
- accY - data from Y - axis
- accZ - data from Z - axis
Link to download timing information of the activities: File:Activity Timings.zip