Research-grade Python SDK for combined EMG+IMU wearable sensors
Project description
Biokinesis-SDK SDK
Research-grade Python SDK for combined EMG+IMU wearable sensors.
Competes directly with Delsys Trigno — matches or exceeds: 2000 Hz EMG, 9-axis IMU at 148 Hz, 16-bit resolution, configurable bandwidth, bipolar differential EMG, LSL output, multi-format export, up to 16 sensors with hardware sync.
Installation
pip install -e .
Quick Start
from biokinesis_sdk.core.types import SensorConfig, FilterConfig, EMGFrame, IMUFrame
from biokinesis_sdk.orchestrator import Orchestrator
from biokinesis_sdk.export import ExportManager
import numpy as np
# Set up orchestrator with 2 sensors
orch = Orchestrator()
orch.add_sensor(SensorConfig(sensor_id=1, label="Biceps",
filter_config=FilterConfig.standard()))
orch.add_sensor(SensorConfig(sensor_id=2, label="Triceps",
filter_config=FilterConfig.standard()))
# Ingest EMG data
emg_data = np.random.randn(4000) * 500 # 2 seconds at 2 kHz, µV
timestamps = np.arange(4000) * 500.0 # µs timestamps
frame = EMGFrame(sensor_id=1, timestamps_us=timestamps,
data=emg_data, sample_rate=2000.0)
orch.ingest_emg(1, frame)
# Export all formats
data = orch.collect_all_data()
ExportManager.export_all(data, "./output", formats=["csv", "hdf5", "mat"])
Modules
| Module | Description |
|---|---|
biokinesis_sdk.emg.filters |
Butterworth bandpass (20–450 / 10–850 Hz), 50/60 Hz notch filter |
biokinesis_sdk.emg.features |
RMS, MAV, ZCR, iEMG, median/mean frequency, waveform length |
biokinesis_sdk.emg.analysis |
Muscle onset detection, MVC normalization, co-contraction index |
biokinesis_sdk.imu.preprocessing |
Raw unit conversion, calibration, gyro bias estimation |
biokinesis_sdk.imu.fusion |
Quaternion algebra, Madgwick AHRS (6-DOF / 9-DOF) |
biokinesis_sdk.imu.kinematics |
Euler angles, gravity compensation, joint angle estimation |
biokinesis_sdk.orchestrator |
16-sensor manager, µs sync, hardware triggers |
biokinesis_sdk.export |
CSV, HDF5, LSL, MATLAB .mat |
biokinesis_sdk.pipelines |
Gait analysis, fatigue monitoring, prosthetics control |
Running Tests
pip install -e ".[dev]"
python -m pytest tests/ -v
License
MIT
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