HHAR: Heterogeneity Human Activity Recognition Dataset
Accelerometer and gyroscope data from nine users carrying eight phones and four watches at once: 33.7 million rows built to study device heterogeneity.
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Accelerometer and gyroscope data from nine users carrying eight phones and four watches at once: 33.7 million rows built to study device heterogeneity.
View Dataset396,602 rows and 33 columns of smartphone motion signals and labels; the publisher describes 20 participants with and without mobility disabilities.
View DatasetFive participants, eight physical-therapy exercises and three execution styles; 275,603 synchronized time points across five wearable sensor units.
View DatasetReal-time posture monitoring dataset from the MPU6050 6-axis sensor (3D gyroscope + 3D accelerometer) attached to the upper body, streaming wirelessly via Phyphox. Angular orientation values: Angle_X, Angle_Y, Angle_Z. Mendeley Data, March 2025 — DOI: 10.17632/ftn4rjnd6x.1. Used for LSTM-based posture classification and ergonomics.
View DatasetiPhone 6s accelerometer and gyroscope dataset from 24 subjects performing 6 activities (walking, jogging, stairs up/down, sitting, standing) at 50 Hz. CSV. Kaggle and GitHub. Used for human activity recognition (HAR) and mobile sensor privacy research. Imperial College London, 2018.
View DatasetMulti-site IMU dataset (chest, hands, knees) with heart rate and SpO2 recorded at 0.5 Hz during structured daily activities and a 3-minute step test. Raw + preprocessed IMU (accelerometer, gyroscope, quaternions) + demographic metadata. Zenodo, July 2025. Used for cardiorespiratory fitness (CRF) estimation and HAR.
View DatasetNovel multimodal HAR dataset for basketball training with synchronized IMU (accelerometer, gyroscope, angle, magnetic field at 200 Hz, MPU9250/WT901) + heart rate and skin surface temperature (1 Hz, Si1141 wrist sensor) across 14 activity classes. ArXiv 2025. Used for sports performance analysis and LLM-based coaching reports.
View DatasetWearable IoT dataset with 18 physical activities from 9 subjects wearing 3 IMUs and a heart rate monitor. 54 columns including temperature, acceleration, and gyroscope data. CSV format. Used for HAR, activity classification, and intensity estimation.
View DatasetOpen-access wearable gait dataset with 400 CSV files from 20 healthy participants across 5 smartphone orientations and 2 gait trial types. 100 Hz IMU sampling. Used for smartphone-based gait metric validation and wearable sensor accuracy studies.
View DatasetIMAD-DS captures multi-rate, multi-sensor signals from scaled industrial machines, including a robotic arm and a brushless motor, for anomaly detection research.
View DatasetWearable IMU dataset from 22 Parkinson's disease patients performing standardized motor tasks, with four inertial sensors (ankles, wrist, lower back) capturing freezing of gait (FoG) episodes, designed for algorithm development and clinical gait analysis.
View DatasetTime-series accelerometer and gyroscope data from smartphones and smartwatches carried by 51 subjects performing 18 activities, suitable for human activity recognition and motion-based biometrics.[web:119][web:123][web:137]
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