A method of monitoring user activity using an inertial sensor, comprising: obtaining acceleration measurement data from an inertial sensor disposed in eyewear ; and processing the acceleration measurement data to determine an identification of a current user activity from a plurality of user activities, wherein the plurality of user activities are characterized by specific repeated human motions, wherein a repeated set of motions defines a motion cycle, and are determinable based on the acceleration measurement data , wherein an amount of time it takes to complete a motion cycle, defines the motion cycle's period, wherein a number of motion cycles occurring in a given unit of time, defines a motion cycle's cadence, wherein the processing comprises: determining events from the acceleration measurement data ; comparing the events to predetermined motion cycle cadences and/or motion cycle periods; determining whether the events occur in a proper time frame to identify a current user activity, wherein events occurring inside of a cadence window identify events indicative of a particular user activity, and wherein events occurring outside of the cadence window identify events contrary to the particular user activity; identifying a particular user activity when enough events indicative of the particular user activity are detected. obtaining acceleration measurement data from an inertial sensor disposed in eyewear ; and processing the acceleration measurement data to determine an identification of a current user activity from a plurality of user activities, wherein the plurality of user activities are characterized by specific repeated human motions, wherein a repeated set of motions defines a motion cycle, and are determinable based on the acceleration measurement data , wherein an amount of time it takes to complete a motion cycle, defines the motion cycle's period, wherein a number of motion cycles occurring in a given unit of time, defines a motion cycle's cadence, wherein the processing comprises: determining events from the acceleration measurement data ; comparing the events to predetermined motion cycle cadences and/or motion cycle periods; determining whether the events occur in a proper time frame to identify a current user activity, wherein events occurring inside of a cadence window identify events indicative of a particular user activity, and wherein events occurring outside of the cadence window identify events contrary to the particular user activity; identifying a particular user activity when enough events indicative of the particular user activity are detected. determining events from the acceleration measurement data ; comparing the events to predetermined motion cycle cadences and/or motion cycle periods; determining whether the events occur in a proper time frame to identify a current user activity, wherein events occurring inside of a cadence window identify events indicative of a particular user activity, and wherein events occurring outside of the cadence window identify events contrary to the particular user activity; identifying a particular user activity when enough events indicative of the particular user activity are detected. <EOS>