Human Activity Recognition Using 9-axis Accelerometer
Donated on 2/26/2026
Time-series human activity dataset from the study: “Application of Nine-Axis Accelerometer-Based Recognition of Daily Activities in Clinical Examination” (Physical Activity and Health, 2024). - Study Population: 30 healthy young adults (ages 19–23; 13M/17F). - Equipment: Five ActiGraph GT9X Link devices worn on the dominant wrist, non-dominant wrist, chest, hip, and thigh. - Data Specs: IMU signals recorded at 100 Hz. - Activities: Nine scripted activities (approx. 2 min each) including supine lying, standing, sitting, simulated eating, tooth brushing, simulated restroom use, walking, stair climbing, and running, plus an "other movements" interval. - Format: CSV files containing timestamps, temperature, and 9-axis data (accelerometer, gyroscope, and magnetometer). This dataset is ideal for benchmarking HAR (Human Activity Recognition) algorithms and wearable-based clinical monitoring workflows.
Dataset Characteristics
Time-Series
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Real
# Instances
10
# Features
-
Dataset Information
Has Missing Values?
No
Introductory Paper
By Takahiro Yamane, Moeka Kimura, Mizuki Morita. 2024
Published in Physical Activity and Health
Dataset Files
| File | Size |
|---|---|
| Activity annotation data_paah.313.csv | 5.9 KB |
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset human_activity_recognition_using_9_axis_accelerometer = fetch_ucirepo(id=1277) # data (as pandas dataframes) X = human_activity_recognition_using_9_axis_accelerometer.data.features y = human_activity_recognition_using_9_axis_accelerometer.data.targets # metadata print(human_activity_recognition_using_9_axis_accelerometer.metadata) # variable information print(human_activity_recognition_using_9_axis_accelerometer.variables)
Yamane, T., Kimura, M., Morita, M., Yamane, T., Kimura, M., & Morita, M. (2024). Human Activity Recognition Using 9-axis Accelerometer [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5NW3W.
Creators
Takahiro Yamane
Okayama University
Moeka Kimura
Okayama University
Mizuki Morita
mizuki@okayama-u.ac.jp
Okayama University
Takahiro Yamane
Moeka Kimura
Mizuki Morita
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.