Dataset

Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset)

PPGEDAIMUmagTempbaroZenodoCC BY 4.0Raw waveforms

This dataset was recorded with a Shimmer3 GSR+ unit on 11 subjects for on-device dehydration monitoring. It includes accelerometer, gyroscope, magnetometer, skin conductance, PPG, temperature and barometric pressure. Some recordings were made during Muslim fasting of up to 15 hours without food or water, with the time since last drink logged for each sample.

  • Published: Zenodo, 2022
  • Cohort: 11 subjects
  • Device: Shimmer3 GSR+
  • Label: time since last drink (fasting up to 15 hours)
  • License: CC BY 4.0
At a glance
Type
Dataset
Access
Not reported
Subjects
11
PPG sites
Ear
Setting
Not reported
Wrist
No
Raw waveforms
Yes
Updated
Oct 15, 2026

Original description

Body signals data such as accelerometer, gyroscope, magnetometer, galvanic skin response, photoplethysmography, temperature and barometric pressure were recorded for 11 subjects using Shimmer3 GSR unit. Some data were recorded while fasting for periods reaching 15 hours without water or food intake in Muslims' fasting time (starting fasting time for each subject sample is recorded in fastingTimes.csv for each subject from which last drinking time can be calculated and for the other non-fasting samples, drinking was done in the last hour before recording the sample, so the last drinking time was set to be 1 hour.

Verbatim fromDataCite· Licence: https://creativecommons.org/licenses/by/4.0/legalcode

Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset): ChatPPG research summary card

Key numbers

11
Subjects
10
Reference labels
DEHYDRATION, LAST DRINKING TIME, WEARABLE FM, DATASET

How it works

How Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset) works: Devices & body sites → Signals recorded → TasksDevices & body sites: Ear (PPG site). Signals recorded: Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset), 11 subjects, signals PPG, EDA, IMU, mag, Temperature, baro. Tasks: Hydration.Devices & body sitesEar: PPG siteEarPPG siteSignals recordedTowards On-Device Dehydration…11 subjectsPPGEDAxyzIMUmagTemperaturebaroTasksHydrationHydration

No model in the hub reports results on this dataset yet.

Reference labels
dehydration, last drinking time, wearable fm, dataset, dehydration, hydration, fasting, shimmer, zenodo, cc by
Device roles
Study wearable (IMU)

Models trained or evaluated on it

No model in the hub reports results on Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset) yet. Be the first: results submitted with a paper are added here.

Cite

@misc{shimmerdehydrationsabry2026,
  title = {{Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device's Data (Shimmer3 GSR+ raw dataset)}},
  year = {2026},
  howpublished = {Zenodo},
  doi = {10.5281/zenodo.7099266},
  url = {https://doi.org/10.5281/zenodo.7099266}
}

History

  1. Record updated