Biometry (PPG)
Biometry is TESLASUIT's physiological-measurement system, built on photoplethysmography (PPG). PPG is a non-invasive optical technique that measures blood-volume changes in microvascular tissue: a sensor emits light into the skin and measures how much is absorbed or reflected by the blood vessels. Because blood volume rises and falls with each heartbeat, the resulting signal carries the timing of the cardiac cycle. It is widely used in fitness and medical wearables to monitor heart rate and other cardiovascular parameters in real time.
A single PPG sensor sits on the outer right shoulder, where the deltoid ends, in the upper-right sleeve of the jacket. It uses multiple LED wavelengths (red, infrared, green, and blue; spectral range 455 to 955 nm) and samples at 200 frames per second, enough temporal resolution to resolve individual beats and beat-to-beat timing. See Hardware - Specifications for full sensor specs. From this signal TESLASUIT derives heart rate, heart-rate variability, and the raw pulse waveform.
In the Python API these are streamed and read through the TsPPG subsystem. For the exact field names, see PPG API and Core Data Structures.
Heart rate#
Heart rate (HR) is the number of beats per minute, calculated from the interval between successive beats (the inter-beat interval, IBI). It reflects the immediate state of the cardiovascular system, rising with exertion or stress and falling at rest.
During movement, signal artifacts can disrupt the optical measurement. An extrapolation algorithm estimates HR through those gaps so the stream stays continuous, and each value carries a validity flag showing whether it is a direct measurement or an estimate.
Heart-rate variability (HRV)#
HRV is the variation in time between consecutive beats, measured in milliseconds. It reflects how the autonomic nervous system regulates the heart, indicating the balance between its sympathetic (fight or flight) and parasympathetic (rest and digest) branches. Higher HRV generally indicates better adaptability and recovery; lower HRV can signal stress or fatigue. These are general trends, not validated clinical thresholds; TESLASUIT is not a medical device.
HRV is calculated from many inter-beat intervals, so a short buffering period follows sensor start-up before values become available.
Common HRV metrics fall into three families:
| Family | Metrics | What they capture |
|---|---|---|
| Time-domain | Mean IBI, SDNN, SDSD, RMSSD | Average beat interval, plus overall and short-term variability |
| Frequency-domain | LF/HF ratio | Low-frequency to high-frequency power ratio (LF/HF), an index of autonomic balance |
| Non-linear | SD1, SD2 | Short-term (SD1) and combined short and long-term (SD2) variability from the Poincaré plot |
Calibration#
Biometry calibration adapts the PPG parameters to the individual so heart-rate metrics are reliable for that person. It is available from suit firmware v4.5.6 onward and is performed in Control Center - Calibration.
Where this is used#
- Studio - Data Capturing: capturing, visualising, and exporting the PPG signal
- Control Center - Calibration: biometry calibration
- PPG API: the data fields and
TsPPGmethods in code - Read heart rate: stream live heart rate from a PPG node
- Measure HRV: read the Mean inter-beat interval from the PPG sensor