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The dataset generation failed because of a cast error
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
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2022-09-05 18:41:01.001
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2022-09-05 18:41:01.002
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2022-09-05 18:41:01.007
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2022-09-05 18:41:01.008
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2022-09-05 18:41:01.009
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2022-09-05 18:41:01.010
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2022-09-05 18:41:01.013
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2022-09-05 18:41:01.015
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2022-09-05 18:41:01.018
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2022-09-05 18:41:01.019
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2022-09-05 18:41:01.020
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2022-09-05 18:41:01.021
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2022-09-05 18:41:01.022
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2022-09-05 18:41:01.023
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2022-09-05 18:41:01.026
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2022-09-05 18:41:01.026
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2022-09-05 18:41:01.027
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2022-09-05 18:41:01.028
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2022-09-05 18:41:01.029
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2022-09-05 18:41:01.030
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2022-09-05 18:41:01.100
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2022-09-05 18:41:01.101
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End of preview.

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 – mental preparation before the task
  • Activity – actual task performance
  • Reflection – reflecting on task performance

Additionally, thinking data is included, representing participants’ 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 β”œβ”€β”€ Data.7z β”‚ β”œβ”€β”€ ParticipantID_ECG/ β”‚ β”‚ β”œβ”€β”€ baseline.csv β”‚ β”‚ β”œβ”€β”€ anticipation1.csv β”‚ β”‚ β”œβ”€β”€ thinking1.csv β”‚ β”‚ β”œβ”€β”€ activity1.csv β”‚ β”‚ β”œβ”€β”€ reflection1.csv β”‚ β”‚ β”œβ”€β”€ anticipation2.csv β”‚ β”‚ β”œβ”€β”€ thinking2.csv β”‚ β”‚ β”œβ”€β”€ activity2.csv β”‚ β”‚ β”œβ”€β”€ reflection2.csv β”‚ β”‚ β”œβ”€β”€ anticipation3.csv β”‚ β”‚ β”œβ”€β”€ activity3.csv β”‚ β”‚ └── reflection3.csv β”‚ β”œβ”€β”€ ParticipantID_GSR/ β”‚ β”‚ β”œβ”€β”€ baseline.csv β”‚ β”‚ β”œβ”€β”€ anticipation1.csv β”‚ β”‚ β”œβ”€β”€ thinking1.csv β”‚ β”‚ β”œβ”€β”€ activity1.csv β”‚ β”‚ β”œβ”€β”€ reflection1.csv β”‚ β”‚ β”œβ”€β”€ anticipation2.csv β”‚ β”‚ β”œβ”€β”€ thinking2.csv β”‚ β”‚ β”œβ”€β”€ activity2.csv β”‚ β”‚ β”œβ”€β”€ reflection2.csv β”‚ β”‚ β”œβ”€β”€ anticipation3.csv β”‚ β”‚ β”œβ”€β”€ activity3.csv β”‚ β”‚ └── reflection3.csv β”œβ”€β”€ Dataset_sample/ β”‚ β”œβ”€β”€ 101_ECG/ β”‚ β”œβ”€β”€ 101_GSR/ β”‚ β”œβ”€β”€ 107_ECG/ β”‚ └── 107_GSR/ β”œβ”€β”€ Self_report.csv β”œβ”€β”€ ParticipantsDemographic.csv └── readme.md


File Descriptions

1. Data.7z

This archive contains participant-wise physiological recordings in two subfolders:

  • ParticipantID_ECG/: ECG recordings
  • ParticipantID_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 ID

  • SPIN_score: Pre-study social anxiety score

  • PBS: Pre-baseline state

  • ATSx_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_1 to ATS1_5 – Anticipation phase (Speech)

  • AS1_1 to AS1_5 – Activity phase (Speech)

  • RS1_1 to RS1_5 – Reflection phase (Speech)

  • ATS2_1 to ATS2_5 – Anticipation phase (Group Discussion)

  • AS2_1 to AS2_5 – Activity phase (Group Discussion)

  • RS2_1 to RS2_5 – Reflection phase (Group Discussion)

  • ATS3_1 to ATS3_5 – Anticipation phase (Interview)

  • AS3_1 to AS3_5 – Activity phase (Interview)

  • RS3_1 to RS3_5 – 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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