About this Dataset

MotionSense Dataset : Smartphone Sensor Data - HAR

MotionSense Dataset: Sensor Based Human Activity and Attribute Recognition

Context

This dataset includes time-series data generated by accelerometer and gyroscope sensors (attitude, gravity, userAcceleration, and rotationRate). It is collected with an iPhone 6s kept in the participant's front pocket using SensingKit which collects information from Core Motion framework on iOS devices. A total of 24 participants in a range of gender, age, weight, and height performed 6 activities in 15 trials in the same environment and conditions: downstairs, upstairs, walking, jogging, sitting, and standing. With this dataset, we aim to look for personal attributes fingerprints in time-series of sensor data, i.e. attribute-specific patterns that can be used to infer gender or personality of the data subjects in addition to their activities.

A simple code for importing dataset and to get your hands in

Content

For each participant, the study had been commenced by collecting their demographic (age and gender) and physically-related (height and weight) information. Then, we provided them with a dedicated smartphone (iPhone 6) and asked them to store it in their trousers' front pocket during the experiment. All the participant were asked to wear flat shoes. We then asked them to perform 6 different activities (walk downstairs, walk upstairs, sit, stand and jogging) around the Queen Mary University of London's Mile End campus. For each trial, the researcher set up the phone and gave it to the current participants, then the researcher stood in a corner. Then, the participant pressed the start button of Crowdsense app and put it in their trousers' front pocket and performed the specified activity. We asked them to do it as natural as possible, like their everyday life. At the end of each trial, they took the phone out of their pocket and pressed the stop button. The exact places and routes for running all the activities are shown in the illustrative map in the following Figure.

As we can see, there are 15 trials:

Long trials: those with number 1 to 9 with around 2 to 3 minutes duration.
Short trials: those with number 11 to 16 that are around 30 seconds to 1 minutes duration.

There are 24 data subjects. The A_DeviceMotion_data folder contains time-series collected by both Accelerometer and Gyroscope for all 15 trials. For every trial we have a multivariate time-series. Thus, we have time-series with 12 features: attitude.roll, attitude.pitch, attitude.yaw, gravity.x, gravity.y, gravity.z, rotationRate.x, rotationRate.y, rotationRate.z, userAcceleration.x, userAcceleration.y, userAcceleration.z.

The accelerometer measures the sum of two acceleration vectors: gravity and user acceleration. User acceleration is the acceleration that the user imparts to the device. Because Core Motion is able to track a device’s attitude using both the gyroscope and the accelerometer, it can differentiate between gravity and user acceleration. A CMDeviceMotion object provides both measurements in the gravity and userAcceleration properties. (More info)

There are 6 different labels:

dws: downstairs
ups: upstairs
sit: sitting
std: standing
wlk: walking
jog: jogging

Acknowledgements

If you use this dataset, please cite the following paper:

@inproceedings{Malekzadeh:2019:MSD:3302505.3310068,

author = {Malekzadeh, Mohammad and Clegg, Richard G. and Cavallaro, Andrea and Haddadi, Hamed},

title = {Mobile Sensor Data Anonymization},

booktitle = {Proceedings of the International Conference on Internet of Things Design and Implementation},

series = {IoTDI '19},

year = {2019},

isbn = {978-1-4503-6283-2},

location = {Montreal, Quebec, Canada},
pages = {49--58},

numpages = {10},

url = {http://doi.acm.org/10.1145/3302505.3310068},

doi = {10.1145/3302505.3310068},

acmid = {3310068},

publisher = {ACM},

address = {New York, NY, USA},

keywords = {adversarial training, deep learning, edge computing, sensor data privacy, time series analysis},

}

@inproceedings{Malekzadeh:2018:PSD:3195258.3195260,

author = {Malekzadeh, Mohammad and Clegg, Richard G. and Cavallaro, Andrea and Haddadi, Hamed},

title = {Protecting Sensory Data Against Sensitive Inferences},

booktitle = {Proceedings of the 1st Workshop on Privacy by Design in Distributed Systems},

series = {W-P2DS'18},

year = {2018},

isbn = {978-1-4503-5654-1},

location = {Porto, Portugal},

pages = {2:1--2:6},

articleno = {2},

numpages = {6},

url = {http://doi.acm.org/10.1145/3195258.3195260},

doi = {10.1145/3195258.3195260},

acmid = {3195260},

publisher = {ACM},

address = {New York, NY, USA},

keywords = {Activity Recognition, Machine Learning, Privacy, Sensor Data, Time-Series Analysis},

}

Tables

Data Subjects Info

@kaggle.malekzadeh_motionsense_dataset.data_subjects_info

4.27 KB
24 rows
5 columns


CREATE TABLE data_subjects_info (
  "code" BIGINT,
  "weight" BIGINT,
  "height" BIGINT,
  "age" BIGINT,
  "gender" BIGINT
);

Sub 10

@kaggle.malekzadeh_motionsense_dataset.sub_10

731.41 KB
6111 rows
13 columns


CREATE TABLE sub_10 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 19

@kaggle.malekzadeh_motionsense_dataset.sub_19

632.62 KB
5295 rows
13 columns


CREATE TABLE sub_19 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 9

@kaggle.malekzadeh_motionsense_dataset.sub_9

570.86 KB
4754 rows
13 columns


CREATE TABLE sub_9 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 22

@kaggle.malekzadeh_motionsense_dataset.sub_22

593.91 KB
4948 rows
13 columns


CREATE TABLE sub_22 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 14

@kaggle.malekzadeh_motionsense_dataset.sub_14

563.99 KB
4695 rows
13 columns


CREATE TABLE sub_14 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 15

@kaggle.malekzadeh_motionsense_dataset.sub_15

589.18 KB
4906 rows
13 columns


CREATE TABLE sub_15 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 13

@kaggle.malekzadeh_motionsense_dataset.sub_13

450.38 KB
3782 rows
13 columns


CREATE TABLE sub_13 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 5

@kaggle.malekzadeh_motionsense_dataset.sub_5

457.41 KB
3841 rows
13 columns


CREATE TABLE sub_5 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 2

@kaggle.malekzadeh_motionsense_dataset.sub_2

672.13 KB
5614 rows
13 columns


CREATE TABLE sub_2 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 6

@kaggle.malekzadeh_motionsense_dataset.sub_6

620.8 KB
5176 rows
13 columns


CREATE TABLE sub_6 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 23

@kaggle.malekzadeh_motionsense_dataset.sub_23

652.15 KB
5441 rows
13 columns


CREATE TABLE sub_23 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 17

@kaggle.malekzadeh_motionsense_dataset.sub_17

560.74 KB
4665 rows
13 columns


CREATE TABLE sub_17 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 12

@kaggle.malekzadeh_motionsense_dataset.sub_12

583.22 KB
4860 rows
13 columns


CREATE TABLE sub_12 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 4

@kaggle.malekzadeh_motionsense_dataset.sub_4

639.37 KB
5336 rows
13 columns


CREATE TABLE sub_4 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 20

@kaggle.malekzadeh_motionsense_dataset.sub_20

601.87 KB
5014 rows
13 columns


CREATE TABLE sub_20 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 21

@kaggle.malekzadeh_motionsense_dataset.sub_21

753.39 KB
6304 rows
13 columns


CREATE TABLE sub_21 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 8

@kaggle.malekzadeh_motionsense_dataset.sub_8

577.68 KB
4828 rows
13 columns


CREATE TABLE sub_8 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 1

@kaggle.malekzadeh_motionsense_dataset.sub_1

522.4 KB
4340 rows
13 columns


CREATE TABLE sub_1 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 24

@kaggle.malekzadeh_motionsense_dataset.sub_24

485.26 KB
4076 rows
13 columns


CREATE TABLE sub_24 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 7

@kaggle.malekzadeh_motionsense_dataset.sub_7

585.64 KB
4883 rows
13 columns


CREATE TABLE sub_7 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 11

@kaggle.malekzadeh_motionsense_dataset.sub_11

586.71 KB
4889 rows
13 columns


CREATE TABLE sub_11 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 16

@kaggle.malekzadeh_motionsense_dataset.sub_16

652.57 KB
5446 rows
13 columns


CREATE TABLE sub_16 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 3

@kaggle.malekzadeh_motionsense_dataset.sub_3

621.92 KB
5194 rows
13 columns


CREATE TABLE sub_3 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);

Sub 18

@kaggle.malekzadeh_motionsense_dataset.sub_18

711.91 KB
5973 rows
13 columns


CREATE TABLE sub_18 (
  "unnamed_0" BIGINT,
  "attitude_roll" DOUBLE,
  "attitude_pitch" DOUBLE,
  "attitude_yaw" DOUBLE,
  "gravity_x" DOUBLE,
  "gravity_y" DOUBLE,
  "gravity_z" DOUBLE,
  "rotationrate_x" DOUBLE,
  "rotationrate_y" DOUBLE,
  "rotationrate_z" DOUBLE,
  "useracceleration_x" DOUBLE,
  "useracceleration_y" DOUBLE,
  "useracceleration_z" DOUBLE
);