Method and apparatus for generating assessments using physical activity and biometric parameters
The methods and apparatuses presented herein determine and/or improve the quality of one or more physiological assessment parameters, e.g., response-recovery rate, based on biometric signal(s) and/or motion signal(s) respectively output by one or more biometric and/or motion sensors. The disclosed methods and apparatuses also estimate a user's stride length based on a motion signal and a determined type of user motion, e.g., walking or running. The speed of the user may then be estimated based on the estimated stride length.
1. An assessment generation system configured to assess a fitness level of a subject, the system comprising one or more processing circuits configured to:
measure an average heart rate of the subject with a heart rate sensor worn by the subject over a period of time;
measure an average cadence of the subject with a cadence sensor worn by the subject over the period of time; and
calculate a ratio of the average heart rate to the average cadence with a processor operatively coupled to the heart rate sensor and the cadence sensor;
wherein the one or more processing circuits are further configured to determine a relative body temperature using the calculated ratio of the average heart rate to the average cadence, wherein the higher the calculated ratio the higher the relative body temperature.
2. The assessment generation system of claim 1 wherein the fitness level is inversely proportional to the ratio of the average heart rate to the average cadence.
3. An assessment generation system configured to evaluate an exercise activity comprising one or more sets of exercise repetitions performed by a user via at least one biometric sensor and at least one motion sensor comprised in a wearable monitoring device, the assessment generation system comprising:
one or more processing circuits configured to:
process a motion signal output by the at least one motion sensor and a biometric signal output by the at least one biometric sensor to identify a type of the exercise activity;
process the motion signal using the identified exercise activity to determine an exercise cadence;
process the biometric signal using the identified exercise activity to determine at least one biometric parameter;
wherein the one or more processing circuits are further configured to estimate at least one of:
a number of repetitions of the identified exercise activity using an integral of the exercise cadence; and
a number of sets of the identified exercise activity using a time-dependent change of the at least one biometric parameter.
4. The assessment generation system of claim 3 wherein the one or more processing circuits are further configured to estimate an intensity of the identified exercise activity using the integral of the exercise cadence and an integral of the at least one biometric parameter.
5. An assessment generation system configured to determine a blood pressure characteristic of a user using a device comprising a photoplethysmography sensor and a motion sensor, wherein the photoplethysmography sensor is proximal to at least some skin of the user, the assessment generation system comprising one or more processing circuits configured to:
screen data from the motion sensor to determine an integrity of data from the photoplethysmography sensor;
buffer a plurality of pulses, at least some of the buffered pulses having integrity;
generate an average pulse shape using the buffered plurality of pulses; and
determine the blood pressure characteristic using a waveform representation of the average pulse shape.
6. The assessment generation system of claim 5 wherein the one or more processing circuits screen the data from the motion sensor by determining whether a user cadence is below a threshold to determine the integrity of the data from the photoplethysmography sensor.
7. The assessment generation system of claim 5 wherein the one or more processing circuits generate the average pulse shape by averaging a spline representation of each of the buffered plurality of pulses to generate an average spline representation.
8. The assessment generation system of claim 5 wherein the one or more processing circuits are further configured to generate the waveform representation by computing at least one of an integral of the average pulse shape and a derivative of the average pulse shape.
9. An assessment generation system configured to determine a blood pressure characteristic of a user using a device comprising a photoplethysmography sensor and a motion sensor, wherein the photoplethysmography sensor is proximal to at least some skin of the user, the system comprising a processing circuit configured to:
screen data from the motion sensor to determine an integrity of data from the photoplethysmography sensor;
process the data from the photoplethysmography sensor, at least some processed data having integrity, to generate an average pulse shape;
compute at least one of an integral of the average pulse shape and a derivative of the average pulse shape; and
determine the blood pressure characteristic using the average pulse shape and at least one of the integral and the derivative.