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Patent US0160022203
Inventor

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Much More than Average Length Specification


1 Independent Claims

  • Claim 2. The apparatus of claim 1, wherein the classification is performed using a machine learning classifier.
  • Claim 3. The apparatus of claim 1, wherein the plurality of statuses further include a not-worn status, during which the user is not wearing the wearable electronic device.
  • Claim 4. The apparatus of claim 1, wherein the apparatus is one of the wearable electronic device and a secondary electronic device to be coupled to the wearable electronic device.
  • Claim 5. The apparatus of claim 1, wherein one of the set of features is based on a combination of a quantification of a distribution of motion data along each of three axes for one of the one or more periods of time.
  • Claim 6. The apparatus of claim 1, wherein the classification of each of the periods of time is further based on photoplethysmography (PPG) data from a time window that includes that period of time, and wherein the PPG data is generated by a photoplethysmographic sensor in the wearable electronic device.
  • Claim 8. The apparatus of claim 1, wherein the instructions, when executed by the set of processors, also cause the apparatus further to: after the derivation of the user being in an asleep state, determine, for the periods of time during which the user is in the asleep state, another set of one or more statistical features of which at least one characterizes a distribution of movement of the user, and classify each of the periods of time, during which the user is in the asleep state, into one of a plurality of sleep stages of the user based on the another set of statistical features, wherein the sleep stages include a rapid eye movement (REM) stage and a plurality of non-REM stages.
  • Claim 9. The apparatus of claim 1, wherein the classification of each of the periods of time is further based on data generated by a set of additional sensors in the wearable electronic device, wherein the set includes one or more of the following: temperature sensorambient light sensorgalvanic skin response sensorcapacitive sensorhumidity sensorand sound sensor.
  • Claim 10. The apparatus of claim 1, wherein the set of motion sensors include an accelerometer.
  • Claim 11. A method for automatically detecting periods of sleep of a user of a wearable electronic device, the method comprising: obtaining a set of features for periods of time from motion data obtained from a set of one or more motion sensors in the wearable electronic device or data derived therefromclassifying each of the periods of time into one of a plurality of statuses of the user based on the set of features determined for the one or more periods of time, wherein the statuses are indicative of relative degrees of movement of the userand deriving blocks of time, each covering one or more of the periods of time, during which the user is in one of a plurality of states, wherein the states include an awake state and an asleep state.
  • Claim 21. A computer readable storage device that includes instructions that are for automatically detecting periods of sleep of a user of a wearable electronic device and that, when executed by one or more processors, cause the one or more processors to: obtain a set of features for periods of time from motion data obtained from a set of one or more motion sensors in the wearable electronic device or data derived therefromclassify each of the periods of time into one of a plurality of statuses of the user based on the set of features determined for the periods of time, wherein the statuses are indicative of relative degrees of movement of the userand derive blocks of time, each covering one or more of the periods of time, during which the user is in one of a plurality of states, wherein the states include an awake state and an asleep state.


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