title: YAMS emoji: 🍠 colorFrom: purple colorTo: purple sdk: gradio sdk_version: 5.15.0 app_file: yams/main.py pinned: false license: mit

YAMS

Yet Another Motionsense Service utility

Code | PyPI | 🤗 Demo (UI only)

Quickstart

Pre-compiled version

• Download the latest release from here

Development

1. (optional) create a dedicated conda environment
   • conda create -n yams python=3.12
   • conda activate yams
2. Clone this repository
   • git clone https://github.com/SenSE-Lab-OSU/YAMS.git
   • cd yams
3. Install dependencies
   • pip install -r requirements.txt
4. Config liblsl
   • conda install -c conda-forge liblsl
5. Lauch YAMS
   • python -m yams

(Deprecated) Windows

Python 3.12 or newer is needed

1. Download setup scripts
   • Download the scripts/windows folder and save it in your desired folder
2. Run the installation script
   • Run the script by double-click the install.bat file
   • The script will perform any necessary setup
3. Start the app
   • by double-click the start_yams.bat file
   • Once the initialization is completed, you will see a messge similar to: * Running on local URL: http://127.0.0.1:7860
4. Access the application
   • Open a web browser and navigate to http://127.0.0.1:7860 or the URL displayed in the prompt.

(Deprecated) MacOS / Linux

1. Download scripts/unix to a desired location
2. Run run.sh to install and start the app

General usage

Download onboard data

Refer to Extract onboard data

Extract raw data

Refer to Data Extraction Feature

Emergency stop

Terminating data collection is also available in YAMS web app under bluetooth scanner - collection control - stop

To halt all on-going collection on the MotionSenSE wristbands,

• On windows, go to your folder where the setup scripts are located as in Quickstart-Windows part
• Locate and double-click emergency_stop.bat
• Wait until all operations are completed

Installation

• pip install -U yams-util
• python -m yams

Development guide

• Clone the repository
  • git clone https://github.com/SenSE-Lab-OSU/YAMS.git
• Install dependencies
  • pip install -r requirements.txt
• Launch the application
  • python -m yams
• Visit http://127.0.0.1:7860 (by default, check on-screen prompt)

Build guide

• Install pyinstaller via pip install pyinstaller
• Create .spec by pyi-makespec --collect-data=gradio_client --collect-data=gradio --collect-data=safehttpx --collect-data=groovy --onefile app.py
• Manually add the following in a = analysis ...

    module_collection_mode={
        'gradio': 'py',  # Collect gradio package as source .py files
    },

• Build the app: pyinstaller app.spec

MacOS

pyi-makespec --collect-data=gradio_client --collect-data=gradio --collect-data=safehttpx --collect-data=groovy --onefile --osx-bundle-identifier 'com.yams' --icon yams/resources/icons/yams.icns app.py

Instructions

(advanced) running data extraction in command line

Run from the project root:

python -m yams.data_extraction -i "data_in" -o "data_out"

All options:

Data type detection — the extractor scans the input folder and processes whichever file types are present:

A single run extracts all types present. Missing types are silently skipped.

Examples:

# Wristband (AC + PPG) — firmware auto-detected from uuid.txt
python -m yams.data_extraction -i "data/subject01" -o "out/subject01"

# Wristband on v4.7.0+ firmware (force if uuid.txt is absent or reports wrong version)
python -m yams.data_extraction -i "data/subject01" -o "out/subject01" --force_new_format

# ECG only folder (e.g. data/260708_ecg containing ecg*.bin)
python -m yams.data_extraction -i "data/260708_ecg" -o "out/ecg" --ignore_id

# Mixed folder with both wristband and ECG files
python -m yams.data_extraction -i "data/session01" -o "out/session01" --force_new_format --ignore_id

# Save as pickle, skip ID parsing
python -m yams.data_extraction -i "data/subject01" -o "out/subject01" --save_format pickle --ignore_id

# Batch extract a folder of zip archives
python -m yams.data_extraction -i "data_in" --mode batch

Notes:

• The device version is read automatically from uuid.txt. If v4.7.0+, the new binary layout (uint32 PPG, quaternion IMU, 32-bit counter at 512 Hz) is used for AC/PPG; otherwise the legacy layout is used. Use --force_new_format to override.
• ECG binary format (ecg*.bin) is always parsed the same way regardless of firmware version — it uses 12-byte CRC-validated frames with a 512 Hz sequence counter.
• ECG output columns: ECG (signed 18-bit ADC count), ETAG (0 = valid sample, 2 = leads off), PTAG, Counter, CDCT, Datetime.

Roadmap

• Device data transfer
• Device data post processing
  • format conversion
  • visualization
• simple data collection utilities
• LSL support
• Auto reconnect
• Selected file download
• Advanced device monitoring [ ] global state: active connection, active outlet, ctl status [ ] BAT monitoring [ ] storage monitoring

Acknowledgement

• Conceptualization: MPADA
• BT control adapted from MotionSenseHRV-BioImpedance-Interface .
• icon designed by Mihimihi