Main concepts

This section explains the ideas the Teslasuit Python API is built on — what each subsystem senses or does, and the vocabulary the rest of the reference assumes.

Haptics & EMS#

Programmable electrical stimulation through the suit's electrodes — at low power it produces tactile haptic sensations; at higher power it drives EMS (electrical muscle stimulation) for muscle contractions and functional electrical stimulation (FES).

• Concept — how the suit produces haptic and EMS stimulation
• API reference — the TsHapticPlayer class
• Example — play a haptic touch on the suit
• Body & channel map — which channels map to which body zones and muscles
• Data structures — haptic parameters and types

Mocap#

Full-body motion capture from the suit's inertial measurement units (IMUs): skeleton positions, bone orientations, and biomechanical joint angles, streamed in real time.

• Concept — what Mocap captures and how
• API reference — the TsMocap class
• Example — stream motion data
• Data structures — skeleton, raw IMU, and angle types

PPG#

Photoplethysmography — optical heart-rate sensing, with heart-rate variability (HRV) and raw pulse signals.

• Concept — what PPG measures and how
• API reference — the TsPpg class
• Read heart rate — read live heart rate from a PPG node
• Measure HRV — read the Mean inter-beat interval
• Data structures — heart-rate and HRV types