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MTHS

Introduced by Taha Samavati et al. in Efficient Deep Learning-based Estimation of the Vital Signs on Smartphones13 Apr 2022 archive 2025-07-28

the MTHS dataset contains 30Hz PPG signals obtained from 62 patients, including 35 men and 27 women. The ground truth data includes heart rate and oxygen saturation levels sampled at 1Hz. The HR and SPo2 measurement is obtained using a pulse oximeter (M70). An iPhone 5s was used to obtain the ppg recordings at 30 fps.

Benchmarks archive 2025-07-28

All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Heart rate estimation MTHS Residual FCN MAE [bpm, session-wise] 6.96 Efficient Deep Learning-based Estimation of the Vital... mahdifarvardin/medvse +1 1 Compare
SpO2 estimation MTHS Residual FCN MAE [bpm, session-wise] 1.34 Efficient Deep Learning-based Estimation of the Vital... mahdifarvardin/medvse +1 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 2. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Efficient Deep Learning-based Estimation of the Vital Signs on Smartphones 2 2 13 Apr 2022 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY-NC-ND

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • MTHS

1 variant name, as the archive lists them.

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