Datasets:
File size: 2,513 Bytes
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license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- emg
- electromyography
- sensor
- tsfile
- modality:timeseries
- timeseries
- format:tsfile
pretty_name: Forearm EMG Sensor Dataset (TsFile)
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: data/anaselkhabbaz_sensor_dataset.tsfile
modality:
- tabular
- timeseries
---
# Forearm EMG Sensor Dataset (TsFile)
Apache TsFile version of [`AnasElkhabbaz/sensor_dataset`](https://huggingface.co/datasets/AnasElkhabbaz/sensor_dataset).
## Overview
Surface electromyography (EMG) recordings of the forearm, packaged in the
LeRobot v2.1 layout (`robot_type = None`). Each episode is one resting-state
recording trial of a subject, sampling three forearm muscle sensors over time.
- **Episodes:** 32 recording trials.
- **Frames:** 152,837 timesteps total, sampled at **~3.33 Hz** (each trial ≈ 1500 s).
- **Tasks:** 32, one per episode — each labelled `<Subject>_<Sex>_<N>_Rest`
(e.g. `Billy_Male_1_Rest`). `task_index` equals `episode_index`.
- **Sensors:** 3 forearm EMG channels — brachioradialis, flexor_carpi_radialis,
flexor_carpi_ulnaris.
- **Source format:** LeRobot v2.1 (no action and no video columns).
## Schema (TsFile structure)
- **Time** (INT64, milliseconds) — per-frame timestamp, restarts at 0 for each
episode (`round(timestamp * 1000)`; ~300 ms apart at 3.33 Hz).
- **episode_index** (TAG) — trial id (0–31). Query one trial with
`WHERE episode_index=0`.
- **task_index** (TAG) — task id (equals `episode_index`); maps to the subject /
trial label in `meta/tasks.jsonl`.
- **frame_index** (FIELD, INT64) — frame number within the episode.
- **sample_index** (FIELD, INT64) — the source global `index` column.
- **observation_state_0** (FIELD, FLOAT) — brachioradialis EMG.
- **observation_state_1** (FIELD, FLOAT) — flexor_carpi_radialis EMG.
- **observation_state_2** (FIELD, FLOAT) — flexor_carpi_ulnaris EMG.
The source `timestamp` column is dropped because it equals `Time / 1000`.
## Usage
Read the `.tsfile` file with the Apache TsFile Java or Python SDK.
```python
# pip install tsfile
from tsfile import TsFileReader
reader = TsFileReader("data/anaselkhabbaz_sensor_dataset.tsfile")
# query one trial: WHERE episode_index=0
```
## Source & license
- Original dataset: https://huggingface.co/datasets/AnasElkhabbaz/sensor_dataset
- Author / publisher: AnasElkhabbaz
- License: Apache-2.0 (inherited from the original dataset)
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