Table 3.

Examples of organizing BioMeTs into categories based on signal modalities to establish common performance characteristics (provides examples, not all‐inclusive list)

Physiological concept	Sensor	Verification	Analytical Validation
Step count	Accelerometer	Accuracy, precision, reliability of raw acceleration data by means of a shake table moving with known frequency and amplitude	Comparison of a step count data produced by an algorithm to a human rater counting steps
Blood pressure	Pressure sensor embedded in an inflatable air‐bladder cuff	Accuracy, precision, and reliability of pneumatic leakage, pressure transducer accuracy, and cuff durability	Comparison to an auscultatory standard or intra‐arterial blood pressure measurement with a predefined sample size with established validation criteria and reporting 97
HR by ECG method	Electrode	ECG: inputting a sine wave with known frequency and amplitude and measuring how closely the device reproduces this known signal; HR: comparing the performance of a new HR algorithm on ECG databases with known and validated feature labels as specified in the relevant international standards	Comparison of HR to a previously analytically validated heart rate monitor
SpO2 (measuring oxygenated and deoxygenated hemoglobin)	Light source and detector	Inputting a known optical signal and measuring how closely the device reproduces this signal	Comparison of pulse oximeter values (SpO2) against arterial blood samples (SaO2).
Body temperature:	Thermistor	Comparison to a probe under defined range of temperature	Comparison of a number of sequential measurements under defined conditions to a temperature measured in a specific location 98

BioMeTs, biometric monitoring technologies; ECG, echocardiogram; HR, heart rate.