Device-based activity classification using predictive feature analysis
Device-based activity classification using predictive feature analysis is described, including receiving a signal from a sensor coupled to a device, the sensor being configured to sense the signal over a time period, evaluating the signal to generate data, the data being further evaluated to select a classifier, invoking the classifier, the classifier being configured to evaluate a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter, and processing the data using the application and the feature interpreter to generate information associated with a biological state, the information being configured to display on an interface associated with the device.
1 . A method, comprising:
receiving a signal from a sensor coupled to a device, the sensor being configured to sense the signal over a time period;
evaluating the signal to generate data, the data being further evaluated to select a classifier;
invoking the classifier, the classifier being configured to evaluate a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter; and
processing the data using the application and the feature interpreter to generate information associated with a biological state, the information being configured to display on an interface associated with the device.
2 . The method of claim 1 , wherein the device is wearable.
3 . The method of claim 1 , wherein the signal is associated with a respiration rate.
4 . The method of claim 1 , wherein the signal is associated with a heart rate.
5 . The method of claim 1 , wherein the biological state comprises sleep.
6 . The method of claim 1 , wherein the biological state comprises sleep associated with rapid eye movement.
7 . The method of claim 1 , wherein the biological state comprises deep sleep.
8 . The method of claim 1 , wherein the biological state comprises light sleep.
9 . The method of claim 1 , wherein the sensor is configured to detect a measurement associated with bioimpedance.
10 . The method of claim 1 , wherein the sensor is configured to detect bioimpedance.
11 . The method of claim 1 , wherein the sensor is configured to detect resistance to an electrical current transmitted by the device into a biological structure.
12 . The method of claim 1 , wherein the sensor is configured to detect resistance to an electrical current transmitted by the device into tissue, the resistance comprising a measurement of magnitude and phase as the electrical current is transmitted through the tissue.
13 . The method of claim 1 , wherein the sensor comprises an electrode.
14 . The method of claim 1 , wherein the sensor comprises an electrode array.
15 . The method of claim 1 , wherein the classifier is configured to determine a state associated with sleep using the data, the data indicating a heart rate.
16 . The method of claim 1 , wherein the classifier is configured to determine a state associated with sleep using the data, the data indicating a heart rate and a respiration rate.
17 . The method of claim 1 , wherein the classifier is configured to determine a state associated with motion.
18 . The method of claim 1 , further comprising another sensor, the sensor being configured to detect bioimpedance and the another sensor being an accelerometer.
19 . A system, comprising:
a memory configured to store data associated with a signal detected by a sensor coupled to a device; and
a processor configured to receive the signal from the sensor, the sensor being configured to sense the signal over a time period, to evaluate the signal to generate data, the data being further evaluated to select a classifier, to invoke the classifier, the classifier being configured to evaluate a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter, and to process the data using the application and the feature interpreter to generate information associated with a biological state, the information being configured to display on an interface associated with the device.
20 . A computer readable medium including instructions for performing a method, the method comprising:
receiving a signal from a sensor coupled to a device, the sensor being configured to sense the signal over a time period;
evaluating the signal to generate data, the data being further evaluated to select a classifier;
invoking the classifier, the classifier being configured to evaluate a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter; and
processing the data using the application and the feature interpreter to generate information associated with a biological state, the information being configured to display on an interface associated with the device.