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Kirti0111
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emg-imu-fatigue-aware-gesture-dataset

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train

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      ("Could not convert ' 0.6026611' with type str: tried to convert to double", 'Conversion failed for column Avanti Sensor 1 (75923) ACC X (G) with type object')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1855, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 687, in wrapped
                  for item in generator(*args, **kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 191, in _generate_tables
                  pa_table = pa.Table.from_pandas(df)
                File "pyarrow/table.pxi", line 3874, in pyarrow.lib.Table.from_pandas
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in dataframe_to_arrays
                  arrays = [convert_column(c, f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 611, in <listcomp>
                  arrays = [convert_column(c, f)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 598, in convert_column
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 592, in convert_column
                  result = pa.array(col, type=type_, from_pandas=True, safe=safe)
                File "pyarrow/array.pxi", line 339, in pyarrow.lib.array
                File "pyarrow/array.pxi", line 85, in pyarrow.lib._ndarray_to_array
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: ("Could not convert ' 0.6026611' with type str: tried to convert to double", 'Conversion failed for column Avanti Sensor 1 (75923) ACC X (G) with type object')
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1428, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 989, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, 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 1898, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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Avanti Sensor 1 (75923) ACC X (G) float64	Avanti Sensor 1 (75923) ACC X Time Series (s) float64	Avanti Sensor 1 (75923) ACC Y (G) float64	Avanti Sensor 1 (75923) ACC Y Time Series (s) float64	Avanti Sensor 1 (75923) ACC Z (G) float64	Avanti Sensor 1 (75923) ACC Z Time Series (s) float64	Avanti Sensor 1 (75923) EMG 1 (mV) float64	Avanti Sensor 1 (75923) EMG 1 Time Series (s) float64	Avanti Sensor 1 (75923) GYRO X (deg/s) float64	Avanti Sensor 1 (75923) GYRO X Time Series (s) float64	Avanti Sensor 1 (75923) GYRO Y (deg/s) float64	Avanti Sensor 1 (75923) GYRO Y Time Series (s) float64	Avanti Sensor 1 (75923) GYRO Z (deg/s) float64	Avanti Sensor 1 (75923) GYRO Z Time Series (s) float64	Avanti Sensor 2 (75891) ACC X (G) float64	Avanti Sensor 2 (75891) ACC X Time Series (s) float64	Avanti Sensor 2 (75891) ACC Y (G) float64	Avanti Sensor 2 (75891) ACC Y Time Series (s) float64	Avanti Sensor 2 (75891) ACC Z (G) float64	Avanti Sensor 2 (75891) ACC Z Time Series (s) float64	Avanti Sensor 2 (75891) EMG 1 (mV) float64	Avanti Sensor 2 (75891) EMG 1 Time Series (s) float64	Avanti Sensor 2 (75891) GYRO X (deg/s) float64	Avanti Sensor 2 (75891) GYRO X Time Series (s) float64	Avanti Sensor 2 (75891) GYRO Y (deg/s) float64	Avanti Sensor 2 (75891) GYRO Y Time Series (s) float64	Avanti Sensor 2 (75891) GYRO Z (deg/s) float64	Avanti Sensor 2 (75891) GYRO Z Time Series (s) float64	Avanti Sensor 3 (76298) ACC X (G) float64	Avanti Sensor 3 (76298) ACC X Time Series (s) float64	Avanti Sensor 3 (76298) ACC Y (G) float64	Avanti Sensor 3 (76298) ACC Y Time Series (s) float64	Avanti Sensor 3 (76298) ACC Z (G) float64	Avanti Sensor 3 (76298) ACC Z Time Series (s) float64	Avanti Sensor 3 (76298) EMG 1 (mV) float64	Avanti Sensor 3 (76298) EMG 1 Time Series (s) float64	Avanti Sensor 3 (76298) GYRO X (deg/s) float64	Avanti Sensor 3 (76298) GYRO X Time Series (s) float64	Avanti Sensor 3 (76298) GYRO Y (deg/s) float64	Avanti Sensor 3 (76298) GYRO Y Time Series (s) float64	Avanti Sensor 3 (76298) GYRO Z (deg/s) float64	Avanti Sensor 3 (76298) GYRO Z Time Series (s) float64	Avanti Sensor 4 (76216) ACC X (G) float64	Avanti Sensor 4 (76216) ACC X Time Series (s) float64	Avanti Sensor 4 (76216) ACC Y (G) float64	Avanti Sensor 4 (76216) ACC Y Time Series (s) float64	Avanti Sensor 4 (76216) ACC Z (G) float64	Avanti Sensor 4 (76216) ACC Z Time Series (s) float64	Avanti Sensor 4 (76216) EMG 1 (mV) float64	Avanti Sensor 4 (76216) EMG 1 Time Series (s) float64	Avanti Sensor 4 (76216) GYRO X (deg/s) float64	Avanti Sensor 4 (76216) GYRO X Time Series (s) float64	Avanti Sensor 4 (76216) GYRO Y (deg/s) float64	Avanti Sensor 4 (76216) GYRO Y Time Series (s) float64	Avanti Sensor 4 (76216) GYRO Z (deg/s) float64	Avanti Sensor 4 (76216) GYRO Z Time Series (s) float64	Avanti Sensor 5 (76157) ACC X (G) float64	Avanti Sensor 5 (76157) ACC X Time Series (s) float64	Avanti Sensor 5 (76157) ACC Y (G) float64	Avanti Sensor 5 (76157) ACC Y Time Series (s) float64	Avanti Sensor 5 (76157) ACC Z (G) float64	Avanti Sensor 5 (76157) ACC Z Time Series (s) float64	Avanti Sensor 5 (76157) EMG 1 (mV) float64	Avanti Sensor 5 (76157) EMG 1 Time Series (s) float64	Avanti Sensor 5 (76157) GYRO X (deg/s) float64	Avanti Sensor 5 (76157) GYRO X Time Series (s) float64	Avanti Sensor 5 (76157) GYRO Y (deg/s) float64	Avanti Sensor 5 (76157) GYRO Y Time Series (s) float64	Avanti Sensor 5 (76157) GYRO Z (deg/s) float64	Avanti Sensor 5 (76157) GYRO Z Time Series (s) float64	Avanti Sensor 6 (76196) ACC X (G) float64	Avanti Sensor 6 (76196) ACC X Time Series (s) float64	Avanti Sensor 6 (76196) ACC Y (G) float64	Avanti Sensor 6 (76196) ACC Y Time Series (s) float64	Avanti Sensor 6 (76196) ACC Z (G) float64	Avanti Sensor 6 (76196) ACC Z Time Series (s) float64	Avanti Sensor 6 (76196) EMG 1 (mV) float64	Avanti Sensor 6 (76196) EMG 1 Time Series (s) float64	Avanti Sensor 6 (76196) GYRO X (deg/s) float64	Avanti Sensor 6 (76196) GYRO X Time Series (s) float64	Avanti Sensor 6 (76196) GYRO Y (deg/s) float64	Avanti Sensor 6 (76196) GYRO Y Time Series (s) float64	Avanti Sensor 6 (76196) GYRO Z (deg/s) float64	Avanti Sensor 6 (76196) GYRO Z Time Series (s) float64	Avanti Sensor 7 (76144) ACC X (G) float64	Avanti Sensor 7 (76144) ACC X Time Series (s) float64	Avanti Sensor 7 (76144) ACC Y (G) float64	Avanti Sensor 7 (76144) ACC Y Time Series (s) float64	Avanti Sensor 7 (76144) ACC Z (G) float64	Avanti Sensor 7 (76144) ACC Z Time Series (s) float64	Avanti Sensor 7 (76144) EMG 1 (mV) float64	Avanti Sensor 7 (76144) EMG 1 Time Series (s) float64	Avanti Sensor 7 (76144) GYRO X (deg/s) float64	Avanti Sensor 7 (76144) GYRO X Time Series (s) float64	Avanti Sensor 7 (76144) GYRO Y (deg/s) float64	Avanti Sensor 7 (76144) GYRO Y Time Series (s) float64	Avanti Sensor 7 (76144) GYRO Z (deg/s) float64	Avanti Sensor 7 (76144) GYRO Z Time Series (s) float64	Avanti Sensor 8 (76066) ACC X (G) float64	Avanti Sensor 8 (76066) ACC X Time Series (s) float64	Avanti Sensor 8 (76066) ACC Y (G) float64	Avanti 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0.641724	0.2025	0.62561	0.2025	0.381836	0.2025	0.003861	0.023824	-8.305344	0.2025	14.351145	0.2025	-2.396947	0.2025	0.354126	0.2025	0.742859	0.2025	0.502014	0.2025	-0.00621	0.023824	-12.969465	0.2025	10.473283	0.2025	-2.183206	0.2025	-0.35199	0.2025	0.650147	0.2025	0.623108	0.2025	-0.019806	0.023824	6.328244	0.2025	17.244274	0.2025	-2.030534	0.2025	-0.668335	0.2025	0.703491	0.2025	0.1297	0.2025	-0.002182	0.023824	-0.709924	0.2025	-2.045802	0.2025	-0.40458	0.2025	-0.617676	0.2025	0.731934	0.2025	-0.293701	0.2025	0.003189	0.023824	8.473283	0.2025	8.519084	0.2025	6.549618	0.2025	-0.323547	0.2025	0.79364	0.2025	-0.5354	0.2025	0.024338	0.023824	6.473282	0.2025	11.824428	0.2025	2.847328	0.2025	0.36084	0.2025	0.773315	0.2025	-0.557861	0.2025	-0.01091	0.023824	4.732824	0.2025	-5.67939	0.2025	-2.70229	0.2025	0.681702	0.2025	0.721375	0.2025	-0.068726	0.2025	0.028702	0.023824	-8.900764	0.2025	6.587786	0.2025	-3.557252	0.2025

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FATIGUE-GR: Fatigue-Aware Gesture Recognition Dataset

Overview

FATIGUE-GR is a multimodal dataset designed for fatigue-aware gesture recognition in extended human-computer interaction. The data was collected from 41 participants using Delsys Avanti EMG and IMU sensors while interacting in a virtual reality (VR) environment.

Participants played five VR games, each controlled by a distinct hand gesture: air tap, swipe, pinch, fist, and grab. Each game lasted up to 20 minutes, and participants reported their subjective fatigue every 20 seconds using the Borg CR scale (0–10).

The data collection was conducted in two sessions, with:

A 10-minute break between consecutive gestures, and
A minimum 2-hour gap between the two sessions to reduce carryover fatigue.

This setup allows researchers to analyze fatigue progression and gesture recognition over time in realistic VR interactions.

Data Contents

The dataset includes:

EMG, ACC, GYRO signals from Delsys Avanti sensors (8 sensors per participant)
Gesture label for each recording segment
Subjective fatigue scores reported every 20 seconds during each gesture session
Structured folders: Each participant has a directory containing gesture-wise CSV files
Formats: All data is stored in .csv format

Folder Structure

FATIGUE_GR_Dataset_CHECK_FINAL/
├── P1/
│   ├── Gesture_1.csv
│   ├── Gesture_2.csv
│   └── ...
├── P2/
│   └── ...
├── ...
└── Subjective_Data_new.csv

Gesture_*.csv: Contains time-series data for EMG, accelerometer, and gyroscope
Subjective_Data_new.csv: Contains participant IDs, gestures, and fatigue scores sampled every 20 seconds

License

This dataset is licensed under CC BY-NC-SA 4.0.
You are free to use it for non-commercial research purposes, provided you give appropriate credit and share any derivative works under the same terms.

Download

Hugging Face: https://huggingface.co/datasets/Kirti0111/emg-imu-fatigue-aware-gesture-dataset

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