
RecGym: Gym Workouts Recognition Dataset with IMU and Capacitive Sensor
Donated on 2/18/2025
The RecGym dataset is a collection of gym workouts with IMU and Capacitive sensors, designed for research and development in recommendation systems and fitness applications. The data set records ten volunteers' gym sessions with a sensing unit composed of an IMU sensor (columns of A_x, A_y, A_z, G_x, G_y, G_z) and a Body Capacitance sensor (column of C_1). The sensing units were worn at three positions: on the wrist, in the pocket, and on the calf, with a sampling rate of 20 Hz. The data set contains the motion signals of twelve activities, including eleven workouts: Adductor, ArmCurl, BenchPress, LegCurl, LegPress, Riding, RopeSkipping, Running, Squat, StairsClimber, Walking, and a "Null" activity when the volunteer hangs around between different workouts session. Each participant performed the above-listed workouts for five sessions in five days (each session lasts around one hour). Altogether, fifty sessions of normalized gym workout data are presented in this data set.
Dataset Characteristics
Time-Series
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Real
# Instances
4432070
# Features
11
Dataset Information
Has Missing Values?
No
Introductory Paper
By Sizhen Bian, V. F. Rey, Siyu Yuan, P. Lukowicz. 2025
Published in 7th International Conference on Activity and Behavior Computing
Variables Table
Variable Name | Role | Type | Description | Units | Missing Values |
---|---|---|---|---|---|
Object | Feature | Binary | no | ||
Workout | Feature | Categorical | no | ||
Position | Feature | Categorical | no | ||
A_x | Feature | Continuous | no | ||
A_y | Feature | Continuous | no | ||
A_z | Feature | Continuous | no | ||
G_x | Feature | Continuous | no | ||
G_y | Feature | Continuous | no | ||
G_z | Feature | Continuous | no | ||
C_1 | Feature | Continuous | no |
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Dataset Files
File | Size |
---|---|
RecGym.csv | 453 MB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset recgym_gym_workouts_recognition_dataset_with_imu_and_capacitive_sensor = fetch_ucirepo(id=1128) # data (as pandas dataframes) X = recgym_gym_workouts_recognition_dataset_with_imu_and_capacitive_sensor.data.features y = recgym_gym_workouts_recognition_dataset_with_imu_and_capacitive_sensor.data.targets # metadata print(recgym_gym_workouts_recognition_dataset_with_imu_and_capacitive_sensor.metadata) # variable information print(recgym_gym_workouts_recognition_dataset_with_imu_and_capacitive_sensor.variables)
Bian, S. & Lukowicz, P. (2025). RecGym: Gym Workouts Recognition Dataset with IMU and Capacitive Sensor [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5PW4K.
Creators
Sizhen Bian
Paul Lukowicz
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.