The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'PPG', 'Skin_Resistance', 'Skin_Conductance'}) and 3 missing columns ({'ECG_LA-RA', 'ECG_LL-RA', 'ECG_LL-LA'}).
This happened while the csv dataset builder was generating data using
zip://101_GSR/activity1.csv::/tmp/hf-datasets-cache/medium/datasets/45684934014911-config-parquet-and-info-SIR-Lab-MAD-Multimodal_Ph-04607106/hub/datasets--SIR-Lab--MAD-Multimodal_Physiological_and_Self-Reported_Dataset_for_Anxiety_Research/snapshots/8d8ff3f2ef8a2a6599e4bd4c4f6eabb53b2ad84e/Dataset sample.zip
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
time: string
Accel_X: double
Accel_Y: double
Accel_Z: double
Skin_Conductance: double
Skin_Resistance: double
PPG: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1087
to
{'time': Value('string'), 'Accel_X': Value('float64'), 'Accel_Y': Value('float64'), 'Accel_Z': Value('float64'), 'ECG_LA-RA': Value('float64'), 'ECG_LL-LA': Value('float64'), 'ECG_LL-RA': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 3 new columns ({'PPG', 'Skin_Resistance', 'Skin_Conductance'}) and 3 missing columns ({'ECG_LA-RA', 'ECG_LL-RA', 'ECG_LL-LA'}).
This happened while the csv dataset builder was generating data using
zip://101_GSR/activity1.csv::/tmp/hf-datasets-cache/medium/datasets/45684934014911-config-parquet-and-info-SIR-Lab-MAD-Multimodal_Ph-04607106/hub/datasets--SIR-Lab--MAD-Multimodal_Physiological_and_Self-Reported_Dataset_for_Anxiety_Research/snapshots/8d8ff3f2ef8a2a6599e4bd4c4f6eabb53b2ad84e/Dataset sample.zip
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
time string | Accel_X float64 | Accel_Y float64 | Accel_Z float64 | ECG_LA-RA float64 | ECG_LL-LA float64 | ECG_LL-RA float64 |
|---|---|---|---|---|---|---|
2022-09-05 18:41:01.000 | 2.521739 | -5.445652 | 6.336957 | -1.515275 | 0.105298 | -1.409978 |
2022-09-05 18:41:01.001 | 2.521739 | -5.445652 | 6.336957 | -1.520324 | -0.145325 | -1.665649 |
2022-09-05 18:41:01.002 | 2.521739 | -5.445652 | 6.336957 | -1.514915 | -0.635752 | -2.150667 |
2022-09-05 18:41:01.003 | 2.521739 | -5.456522 | 6.336957 | -1.617328 | -0.489345 | -2.106673 |
2022-09-05 18:41:01.004 | 2.521739 | -5.456522 | 6.326087 | -1.615164 | -0.545961 | -2.161125 |
2022-09-05 18:41:01.005 | 2.51087 | -5.467391 | 6.304348 | -1.587758 | -0.592119 | -2.179876 |
2022-09-05 18:41:01.006 | 2.521739 | -5.478261 | 6.293478 | -1.598215 | -0.370705 | -1.96892 |
2022-09-05 18:41:01.007 | 2.543478 | -5.5 | 6.293478 | -1.510948 | -0.591037 | -2.101985 |
2022-09-05 18:41:01.008 | 2.543478 | -5.51087 | 6.271739 | -1.489312 | -0.619525 | -2.108836 |
2022-09-05 18:41:01.009 | 2.554348 | -5.521739 | 6.23913 | -1.51816 | -0.140277 | -1.658437 |
2022-09-05 18:41:01.010 | 2.554348 | -5.521739 | 6.228261 | -1.515636 | -0.233313 | -1.748949 |
2022-09-05 18:41:01.011 | 2.554348 | -5.521739 | 6.217391 | -1.588118 | -0.196531 | -1.78465 |
2022-09-05 18:41:01.012 | 2.554348 | -5.543478 | 6.217391 | -1.477051 | -0.30832 | -1.785371 |
2022-09-05 18:41:01.013 | 2.532609 | -5.554348 | 6.217391 | -1.496524 | 0.662077 | -0.834447 |
2022-09-05 18:41:01.015 | 2.576087 | -5.554348 | 6.228261 | -1.474166 | 0.757277 | -0.716889 |
2022-09-05 18:41:01.016 | 2.565217 | -5.543478 | 6.217391 | -1.470921 | 0.5099 | -0.961021 |
2022-09-05 18:41:01.017 | 2.576087 | -5.543478 | 6.184783 | -1.47633 | 0.365657 | -1.110673 |
2022-09-05 18:41:01.018 | 2.565217 | -5.554348 | 6.163043 | -1.481018 | 0.23728 | -1.243737 |
2022-09-05 18:41:01.019 | 2.586957 | -5.565217 | 6.173913 | -1.503736 | -0.068516 | -1.572252 |
2022-09-05 18:41:01.020 | 2.586957 | -5.565217 | 6.163043 | -1.484984 | -0.406405 | -1.89139 |
2022-09-05 18:41:01.021 | 2.586957 | -5.576087 | 6.152174 | -1.512751 | -0.318778 | -1.831529 |
2022-09-05 18:41:01.022 | 2.586957 | -5.576087 | 6.141304 | -1.515636 | -0.196171 | -1.711807 |
2022-09-05 18:41:01.023 | 2.586957 | -5.576087 | 6.141304 | -1.505539 | 0.069597 | -1.435942 |
2022-09-05 18:41:01.024 | 2.576087 | -5.586957 | 6.130435 | -1.499048 | -0.194007 | -1.693055 |
2022-09-05 18:41:01.025 | 2.565217 | -5.608696 | 6.119565 | -1.5773 | -0.582022 | -2.159322 |
2022-09-05 18:41:01.026 | 2.565217 | -5.608696 | 6.108696 | -1.483542 | -0.677583 | -2.161125 |
2022-09-05 18:41:01.026 | 2.565217 | -5.619565 | 6.108696 | -1.500851 | -0.341857 | -1.842708 |
2022-09-05 18:41:01.027 | 2.554348 | -5.619565 | 6.108696 | -1.472002 | -0.71184 | -2.183843 |
2022-09-05 18:41:01.028 | 2.554348 | -5.630435 | 6.119565 | -1.475609 | -0.65234 | -2.127949 |
2022-09-05 18:41:01.029 | 2.532609 | -5.619565 | 6.119565 | -1.477772 | -0.454006 | -1.931778 |
2022-09-05 18:41:01.030 | 2.521739 | -5.630435 | 6.119565 | -1.478133 | -0.465906 | -1.944039 |
2022-09-05 18:41:01.031 | 2.51087 | -5.619565 | 6.097826 | -1.610115 | -0.172731 | -1.782847 |
2022-09-05 18:41:01.032 | 2.51087 | -5.619565 | 6.097826 | -1.60074 | -0.182107 | -1.782847 |
2022-09-05 18:41:01.033 | 2.521739 | -5.619565 | 6.097826 | -1.5892 | -0.408208 | -1.997409 |
2022-09-05 18:41:01.034 | 2.5 | -5.608696 | 6.086957 | -1.613361 | -0.302911 | -1.916272 |
2022-09-05 18:41:01.035 | 2.48913 | -5.619565 | 6.076087 | -1.525012 | 0.18391 | -1.341102 |
2022-09-05 18:41:01.037 | 2.478261 | -5.586957 | 6.076087 | -1.525012 | 0.465906 | -1.059106 |
2022-09-05 18:41:01.038 | 2.5 | -5.597826 | 6.076087 | -1.459021 | 0.505212 | -0.953809 |
2022-09-05 18:41:01.039 | 2.48913 | -5.586957 | 6.086957 | -1.47633 | 0.719774 | -0.756556 |
2022-09-05 18:41:01.040 | 2.478261 | -5.597826 | 6.086957 | -1.505539 | 0.490788 | -1.014751 |
2022-09-05 18:41:01.041 | 2.478261 | -5.586957 | 6.086957 | -1.514554 | -0.216725 | -1.73128 |
2022-09-05 18:41:01.042 | 2.478261 | -5.597826 | 6.097826 | -1.523209 | -0.191844 | -1.715052 |
2022-09-05 18:41:01.043 | 2.478261 | -5.586957 | 6.086957 | -1.494721 | -0.103134 | -1.597855 |
2022-09-05 18:41:01.044 | 2.48913 | -5.576087 | 6.097826 | -1.466954 | -0.292453 | -1.759407 |
2022-09-05 18:41:01.045 | 2.48913 | -5.554348 | 6.108696 | -1.469478 | -0.464824 | -1.934302 |
2022-09-05 18:41:01.046 | 2.48913 | -5.554348 | 6.097826 | -1.584152 | -0.212398 | -1.79655 |
2022-09-05 18:41:01.047 | 2.478261 | -5.554348 | 6.097826 | -1.597855 | -0.588152 | -2.186007 |
2022-09-05 18:41:01.048 | 2.478261 | -5.554348 | 6.119565 | -1.572252 | -0.618082 | -2.190334 |
2022-09-05 18:41:01.049 | 2.48913 | -5.543478 | 6.108696 | -1.483903 | -0.691286 | -2.175188 |
2022-09-05 18:41:01.050 | 2.48913 | -5.543478 | 6.119565 | -1.623818 | -0.357363 | -1.981181 |
2022-09-05 18:41:01.051 | 2.48913 | -5.554348 | 6.119565 | -1.628506 | -0.494033 | -2.12254 |
2022-09-05 18:41:01.052 | 2.48913 | -5.554348 | 6.119565 | -1.521766 | -0.273702 | -1.795468 |
2022-09-05 18:41:01.053 | 2.478261 | -5.554348 | 6.130435 | -1.601821 | -0.20158 | -1.803401 |
2022-09-05 18:41:01.054 | 2.478261 | -5.554348 | 6.130435 | -1.562876 | -0.547764 | -2.110639 |
2022-09-05 18:41:01.055 | 2.478261 | -5.543478 | 6.130435 | -1.622015 | -0.256753 | -1.878768 |
2022-09-05 18:41:01.056 | 2.478261 | -5.543478 | 6.141304 | -1.538354 | -0.530815 | -2.06917 |
2022-09-05 18:41:01.057 | 2.48913 | -5.532609 | 6.152174 | -1.52393 | -0.020555 | -1.544485 |
2022-09-05 18:41:01.058 | 2.478261 | -5.554348 | 6.152174 | -1.499048 | 0.512785 | -0.986263 |
2022-09-05 18:41:01.060 | 2.51087 | -5.532609 | 6.173913 | -1.501572 | 0.653783 | -0.84779 |
2022-09-05 18:41:01.061 | 2.521739 | -5.521739 | 6.163043 | -1.49436 | 0.448597 | -1.045764 |
2022-09-05 18:41:01.062 | 2.521739 | -5.532609 | 6.173913 | -1.486427 | 0.627819 | -0.858608 |
2022-09-05 18:41:01.063 | 2.51087 | -5.532609 | 6.173913 | -1.468396 | 0.005409 | -1.462987 |
2022-09-05 18:41:01.064 | 2.51087 | -5.532609 | 6.195652 | -1.467315 | -0.471315 | -1.938629 |
2022-09-05 18:41:01.065 | 2.521739 | -5.532609 | 6.184783 | -1.465872 | -0.151816 | -1.617688 |
2022-09-05 18:41:01.066 | 2.532609 | -5.532609 | 6.184783 | -1.459021 | -0.32635 | -1.785371 |
2022-09-05 18:41:01.067 | 2.543478 | -5.532609 | 6.195652 | -1.465511 | -0.492591 | -1.958102 |
2022-09-05 18:41:01.067 | 2.532609 | -5.521739 | 6.206522 | -1.468036 | -0.49836 | -1.966396 |
2022-09-05 18:41:01.068 | 2.543478 | -5.51087 | 6.217391 | -1.575858 | -0.349069 | -1.924926 |
2022-09-05 18:41:01.069 | 2.543478 | -5.51087 | 6.217391 | -1.487509 | -0.720134 | -2.207643 |
2022-09-05 18:41:01.070 | 2.543478 | -5.521739 | 6.206522 | -1.570088 | -0.555337 | -2.125424 |
2022-09-05 18:41:01.071 | 2.543478 | -5.51087 | 6.206522 | -1.573694 | -0.509179 | -2.082873 |
2022-09-05 18:41:01.072 | 2.543478 | -5.51087 | 6.217391 | -1.552779 | -0.651619 | -2.204398 |
2022-09-05 18:41:01.073 | 2.543478 | -5.51087 | 6.23913 | -1.563236 | -0.621688 | -2.184925 |
2022-09-05 18:41:01.074 | 2.532609 | -5.521739 | 6.25 | -1.631031 | -0.34979 | -1.980821 |
2022-09-05 18:41:01.075 | 2.532609 | -5.521739 | 6.26087 | -1.602903 | -0.149652 | -1.752556 |
2022-09-05 18:41:01.076 | 2.543478 | -5.532609 | 6.23913 | -1.636079 | -0.325269 | -1.961348 |
2022-09-05 18:41:01.077 | 2.543478 | -5.521739 | 6.23913 | -1.593167 | -0.128016 | -1.721183 |
2022-09-05 18:41:01.078 | 2.543478 | -5.521739 | 6.228261 | -1.488951 | -0.258917 | -1.747868 |
2022-09-05 18:41:01.079 | 2.543478 | -5.521739 | 6.228261 | -1.592806 | -0.056976 | -1.649782 |
2022-09-05 18:41:01.080 | 2.521739 | -5.543478 | 6.195652 | -1.483181 | 0.465906 | -1.017276 |
2022-09-05 18:41:01.082 | 2.51087 | -5.532609 | 6.195652 | -1.473805 | 0.425518 | -1.048288 |
2022-09-05 18:41:01.083 | 2.521739 | -5.532609 | 6.206522 | -1.474527 | 0.386933 | -1.087594 |
2022-09-05 18:41:01.084 | 2.543478 | -5.521739 | 6.206522 | -1.460824 | 0.280914 | -1.17991 |
2022-09-05 18:41:01.085 | 2.543478 | -5.532609 | 6.217391 | -1.450727 | -0.123689 | -1.574415 |
2022-09-05 18:41:01.086 | 2.543478 | -5.532609 | 6.217391 | -1.45866 | -0.544518 | -2.003178 |
2022-09-05 18:41:01.087 | 2.532609 | -5.532609 | 6.206522 | -1.565039 | -0.415781 | -1.980821 |
2022-09-05 18:41:01.088 | 2.521739 | -5.543478 | 6.195652 | -1.474887 | -0.483936 | -1.958823 |
2022-09-05 18:41:01.089 | 2.521739 | -5.543478 | 6.195652 | -1.50013 | -0.120443 | -1.620573 |
2022-09-05 18:41:01.090 | 2.543478 | -5.521739 | 6.184783 | -1.490033 | -0.116837 | -1.60687 |
2022-09-05 18:41:01.091 | 2.532609 | -5.532609 | 6.195652 | -1.552418 | -0.225019 | -1.777438 |
2022-09-05 18:41:01.092 | 2.521739 | -5.532609 | 6.206522 | -1.580545 | -0.583464 | -2.164009 |
2022-09-05 18:41:01.093 | 2.521739 | -5.532609 | 6.206522 | -1.489312 | -0.686237 | -2.175549 |
2022-09-05 18:41:01.094 | 2.51087 | -5.532609 | 6.195652 | -1.491836 | -0.336808 | -1.828644 |
2022-09-05 18:41:01.095 | 2.51087 | -5.532609 | 6.206522 | -1.603264 | -0.384408 | -1.987672 |
2022-09-05 18:41:01.096 | 2.51087 | -5.532609 | 6.206522 | -1.491836 | -0.630704 | -2.12254 |
2022-09-05 18:41:01.097 | 2.5 | -5.532609 | 6.206522 | -1.599297 | -0.179583 | -1.77888 |
2022-09-05 18:41:01.098 | 2.5 | -5.543478 | 6.228261 | -1.601821 | -0.146407 | -1.748228 |
2022-09-05 18:41:01.099 | 2.48913 | -5.543478 | 6.217391 | -1.492918 | -0.477085 | -1.970002 |
2022-09-05 18:41:01.100 | 2.48913 | -5.543478 | 6.206522 | -1.495081 | -0.300026 | -1.795107 |
2022-09-05 18:41:01.101 | 2.48913 | -5.532609 | 6.206522 | -1.484984 | -0.308681 | -1.793665 |
MAD: A Multimodal Physiological and Self-Reported Dataset for Anxiety Research
Overview
This dataset accompanies the IMWUT paper titled:
"MAD: A Multimodal Physiological and Self-Reported Dataset for Anxiety Research from a Low-to-Middle-Income Country."
The dataset captures physiological and self-reported responses from participants during a baseline condition and three anxiety-inducing activities (Speech, Group Discussion, Interview). Each activity consists of three phases:
- Anticipation β mental preparation before the task
- Activity β actual task performance
- Reflection β reflecting on task performance
Additionally, thinking data is included, representing participantsβ preparation time for the speech and group discussion activities.
Data was collected using Shimmer ECG and Shimmer GSR kits at a sampling rate of 1024 Hz.
Participant Information
- Participant IDs range from 101 to 119.
- Some participant IDs are skipped due to:
- Dummy participants included to simulate similar group settings in case participant refused to participate in the last minute. Their data is not shared.
- Sensor failures, leading to unusable or incomplete recordings.
Please note:
- GSR data from the following participants should be excluded due to battery/sensor failures:
[122, 123, 125, 126, 128, 129, 150, 170, 211]
Dataset Structure
MAD_dataset_root βββ Data.7z β βββ ParticipantID_ECG/ β β βββ baseline.csv β β βββ anticipation1.csv β β βββ thinking1.csv β β βββ activity1.csv β β βββ reflection1.csv β β βββ anticipation2.csv β β βββ thinking2.csv β β βββ activity2.csv β β βββ reflection2.csv β β βββ anticipation3.csv β β βββ activity3.csv β β βββ reflection3.csv β βββ ParticipantID_GSR/ β β βββ baseline.csv β β βββ anticipation1.csv β β βββ thinking1.csv β β βββ activity1.csv β β βββ reflection1.csv β β βββ anticipation2.csv β β βββ thinking2.csv β β βββ activity2.csv β β βββ reflection2.csv β β βββ anticipation3.csv β β βββ activity3.csv β β βββ reflection3.csv βββ Dataset_sample/ β βββ 101_ECG/ β βββ 101_GSR/ β βββ 107_ECG/ β βββ 107_GSR/ βββ Self_report.csv βββ ParticipantsDemographic.csv βββ readme.md
File Descriptions
1. Data.7z
This archive contains participant-wise physiological recordings in two subfolders:
ParticipantID_ECG/: ECG recordingsParticipantID_GSR/: GSR and PPG recordings
Each subfolder contains 12 .csv files representing various phases and tasks.
Columns:
- ECG Files:
time,Accel_X,Accel_Y,Accel_Z,ECG_LA-RA,ECG_LL-LA,ECG_LL-RA
- GSR Files:
time,Accel_X,Accel_Y,Accel_Z,Skin_Conductance,Skin_Resistance,PPG
2. Dataset_sample/
A small subset of the full dataset for preview/testing, includes:
- Data from Participant IDs:
101,107
3. Self_report.csv
Self-reported anxiety levels collected:
- Before the study: SPIN questionnaire
- After each phase of each activity: custom anxiety ratings
Key Columns:
P_Id: Participant IDSPIN_score: Pre-study social anxiety scorePBS: Pre-baseline stateATSx_y,ASx_y,RSx_y: Anxiety scores for anticipation, activity, and reflection phases across the 3 tasks.Responses for each phase of each activity:
ATS1_1toATS1_5β Anticipation phase (Speech)AS1_1toAS1_5β Activity phase (Speech)RS1_1toRS1_5β Reflection phase (Speech)ATS2_1toATS2_5β Anticipation phase (Group Discussion)AS2_1toAS2_5β Activity phase (Group Discussion)RS2_1toRS2_5β Reflection phase (Group Discussion)ATS3_1toATS3_5β Anticipation phase (Interview)AS3_1toAS3_5β Activity phase (Interview)RS3_1toRS3_5β Reflection phase (Interview)
Note on Scoring:
The following questions needs to be reverse-coded so that higher scores indicate higher anxiety:PBS, ATS1_1, ATS1_2, AP1_2, RP1_2, ATS2_1, ATS2_2, AP2_2, RP2_2, ATS3_1, ATS3_2, AP3_2, RP3_2, and PS
4. ParticipantsDemographic.csv
Contains demographic details of each participant:
- P_Id, Age, Gender, Location
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