A unitary apparatus configured to be worn on a user, comprising: a processor; a sensor configured to capture motion data of the user; a non-transitory computer-readable medium comprising computer-executable instructions that when executed by the processor perform at least: capturing, from the sensor while being worn by the user, a data stream comprising one or more data points generated as a result of a motion of the user; transforming the one or more data points into a dataset representing a motion of the user; calculating one or more motion attributes from the dataset; determining, for each model of a plurality of energy expenditure models, a probability that an output of that model will output a best available estimate of an energy characteristic of the motion of the user by comparing the first set of one or more motion attributes from the dataset to a second set of one or more motion attributes of each model of the plurality of energy expenditure models; selecting an energy expenditure model, from the plurality of energy expenditure models, based on a determination that the energy expenditure model is associated with a highest probability of each of the probabilities; using the selected energy expenditure model and based on one or more individual-specific properties, calculating a value of oxygen consumption of the user; calculating an energy expenditure associated with the motion of the user based on the value of oxygen consumption; and determining, from the one or more motion attributes, and separately to the step of selecting an energy expenditure model, a motion classification of the user as comprising one of: running; walking; and another form of motion; and if the motion classification comprises one of running and walking, communicating one or more attributes to a running or walking model, respectively, and determining a speed of the user. a processor; a sensor configured to capture motion data of the user; a non-transitory computer-readable medium comprising computer-executable instructions that when executed by the processor perform at least: capturing, from the sensor while being worn by the user, a data stream comprising one or more data points generated as a result of a motion of the user; transforming the one or more data points into a dataset representing a motion of the user; calculating one or more motion attributes from the dataset; determining, for each model of a plurality of energy expenditure models, a probability that an output of that model will output a best available estimate of an energy characteristic of the motion of the user by comparing the first set of one or more motion attributes from the dataset to a second set of one or more motion attributes of each model of the plurality of energy expenditure models; selecting an energy expenditure model, from the plurality of energy expenditure models, based on a determination that the energy expenditure model is associated with a highest probability of each of the probabilities; using the selected energy expenditure model and based on one or more individual-specific properties, calculating a value of oxygen consumption of the user; calculating an energy expenditure associated with the motion of the user based on the value of oxygen consumption; and determining, from the one or more motion attributes, and separately to the step of selecting an energy expenditure model, a motion classification of the user as comprising one of: running; walking; and another form of motion; and if the motion classification comprises one of running and walking, communicating one or more attributes to a running or walking model, respectively, and determining a speed of the user. capturing, from the sensor while being worn by the user, a data stream comprising one or more data points generated as a result of a motion of the user; transforming the one or more data points into a dataset representing a motion of the user; calculating one or more motion attributes from the dataset; determining, for each model of a plurality of energy expenditure models, a probability that an output of that model will output a best available estimate of an energy characteristic of the motion of the user by comparing the first set of one or more motion attributes from the dataset to a second set of one or more motion attributes of each model of the plurality of energy expenditure models; selecting an energy expenditure model, from the plurality of energy expenditure models, based on a determination that the energy expenditure model is associated with a highest probability of each of the probabilities; using the selected energy expenditure model and based on one or more individual-specific properties, calculating a value of oxygen consumption of the user; calculating an energy expenditure associated with the motion of the user based on the value of oxygen consumption; and determining, from the one or more motion attributes, and separately to the step of selecting an energy expenditure model, a motion classification of the user as comprising one of: running; walking; and another form of motion; and if the motion classification comprises one of running and walking, communicating one or more attributes to a running or walking model, respectively, and determining a speed of the user.