University of Puerto Rico-Mayagüez study "Indirect Estimation of Cardiorespiratory Fitness from Daily Activities Using Wearables". Per-subject IMUSubjectXX.csv and BiomarkersSubjectXX.csv plus SubjectsInfo.xlsx (age, sex, height, weight, BMI, fat %, resting HR/SpO2). Activity labels with MET values (rest 1.0 → bike 7.0).
This dataset was collected as part of the study "Indirect AI-Based Estimation of Cardiorespiratory Fitness from Daily Activities Using Wearables." It contains synchronized sensor data and physiological measurements from participants performing a structured sequence of daily activities. The dataset is designed to support research in human activity recognition (HAR) and indirect estimation of cardiorespiratory fitness, particularly through heart rate regression after a submaximal step test.
Participants wore a combination of inertial measurement units (IMUs) and biometric sensors in a controlled indoor environment. Each session followed a predefined activity protocol interleaving rest and effort, and a 3-minute step test to elicit a measurable cardiorespiratory response.
The dataset includes:
Raw and preprocessed IMU data from the chest, hands, and knees (quaternions, accelerometers, gyroscopes).
Frame-level activity labels aligned with the protocol (target level for HAR).
Biomarker data: heart rate and SpO₂ sampled at 0.5 Hz.
Demographic metadata (age, height, weight, gender, BMI, body fat %, etc.).
Step test heart rate (target variable for regression).
Verbatim fromZenodo· Licence: cc-by-4.0
No model in the hub reports results on this dataset yet.
Daily Activities Wearable Dataset for Cardiorespiratory Fitness (UPRM; IMU + HR + SpO2, n=67) [Data set]. (n.d.). https://doi.org/10.5281/zenodo.15857137
@misc{crfdailyactivitidaily,
title = {{Daily Activities Wearable Dataset for Cardiorespiratory Fitness (UPRM; IMU + HR + SpO2, n=67)}},
doi = {10.5281/zenodo.15857137}
}Cite the dated snapshot 2026-10 for a fixed, reproducible version. Please also cite the original publications listed above.
ChatPPG. (2026). Daily Activities Wearable Dataset for Cardiorespiratory Fitness (UPRM; IMU + HR + SpO2, n=67): dataset record (Version 2026-10) [Data set]. ChatPPG Research Hub. https://chatppg.com/research/datasets/crf-daily-activities-wearables
@misc{chatppg_dataset_crf_daily_activities_wearables,
author = {{ChatPPG}},
title = {{Daily Activities Wearable Dataset for Cardiorespiratory Fitness (UPRM; IMU + HR + SpO2, n=67): dataset record}},
year = {2026},
month = oct,
version = {2026-10},
howpublished = {\url{https://chatppg.com/research/datasets/crf-daily-activities-wearables}},
note = {ChatPPG Research Hub, Snapshot 2026-10, https://chatppg.com/research/snapshots/2026-10}
}cff-version: 1.2.0 message: "If you use this resource, please cite it as below." type: dataset title: "Daily Activities Wearable Dataset for Cardiorespiratory Fitness (UPRM; IMU + HR + SpO2, n=67): dataset record" authors: - name: "ChatPPG" url: "https://chatppg.com/research/datasets/crf-daily-activities-wearables" repository-artifact: "https://chatppg.com/research/snapshots/2026-10" version: "2026-10" date-released: "2026-10-31"
Record updated
Development and validation of an integrated wearable system for continuous cardiorespiratory monitoring using photoplethysmography and optical respiratory detectionSame task: Heart rateMedical & Biological Engineering & Computi · 2026
Prediction of acute mountain sickness from overnight pulse oximetry during ascent to Everest Base Camp: a field-based machine learning studySame task: SpO₂Frontiers in Physiology · 2026
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Simultaneous physiological measurements with five devices at different cognitive and physical loadsSame task: Heart ratePPG · ECG · IMU