The AcqKnowledge Rate Detector is critical to the ability of AcqKnowledge to extract information from physiological data that has a degree of periodicity. Physiological data which can be investigated using Rate detection include:
Waveform | Metrics | Waveform Profile1 |
|---|---|---|
Airflow | Respiration Rate | smooth |
Blood Flow | Flow Peak, Flow Min, Flow Mean | smooth |
Blood Pressure | Systolic, Diastolic, Mean, dP/dt Max, dP/dt Min | smooth |
ECG | Heart Rate or Inter-Beat-Interval recording | spikey (high slew rate or sharp amplitude transitions) |
EGG (Electrogastrogram) | Peristolic contractions | smooth |
EMG | Zero Crossing or Mean Frequency analysis | spikey |
Goinometer (joint angle) | Repetitive motion/exercise | smooth |
Nerve | Spike counting, Frequency | spikey |
Pulse plethysmogram | Pulse Rate, Inter-Beat Interval, Volume | smooth |
Respiration | Respiration Rate | smooth |
Most physiological data which is periodic in nature is smoothly varying.
However, important data types that are “spikey” include ECG and EMG.
The AcqKnowledge Rate Detector incorporates a significant amount of flexibility to optimize performance when extracting data from periodic physiological waveforms. The Rate Detector Algorithm is a procedure whereby some special cyclic property of a waveform is determined by a search for waveform peaks or valleys. This application note explains the major component functionality of the Rate Detector algorithm that facilitates the search for these peaks and includes a discussion on signal conditioning methods that will help render optimal results when the Rate Detector tool is applied.
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