In one embodiment, a method for generating a message to a friend of a user is provided, comprising: processing activity data of a first user measured by an activity monitoring device to update a value of an activity metric for the first user; identifying a change in an inequality relationship between the value of the activity metric for the first user and a value of the activity metric for a second user; in response to identifying the change in the inequality relationship, prompting the first user to generate a message to the second user.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

A method of determining a CRF level for a user of a fitness tracking system includes receiving activity data from at least one activity sensor carried by the user during a number of workouts, the activity data including distance data for each of the number of workouts, and then generating workout data based on the activity data. The method further includes storing the workout data in a memory, the memory further including demographic data for the user. When the an attribute of the workout data is less than a threshold number, the method includes determining a first CRF level for the user based on a first CRF model. When the attribute of the workout data is greater than the threshold number, the method includes determining a second CRF level for the user based on a second CRF model, and displaying the first and second CRF levels.

Embodiments are disclosed for an electrical bicycle detector for energy expenditure estimation. In an embodiment, a method comprises: determining heart rate energy expenditure of a user wearing or holding the device; determining work rate energy expenditure of a user wearing or holding the device; determining a probability that the user is riding an electrical bike based on the heart rate energy expenditure and the work rate energy expenditure; determining whether or not the probability meets a condition corresponding to a threshold probability; and in accordance with the probability meeting the condition corresponding to the threshold probability: adjusting the work rate energy expenditure; and generating fitness data based at least on the adjusted work rate energy expenditure.

Provided is a method of predicting a cardiopulmonary function comprising measuring motion of a cardiopulmonary function measurement-target person, by a motion sensor, determining a gait speed of the cardiopulmonary function measurement-target person according to the motion of the cardiopulmonary function measurement-target person, by a processor, and predicting a cardiopulmonary function index of the cardiopulmonary function measurement-target person, based on the gait speed of the cardiopulmonary function measurement-target person, by the processor.

Provided is a method of predicting a cardiopulmonary function comprising measuring motion of a cardiopulmonary function measurement-target person, by a motion sensor, determining a gait speed of the cardiopulmonary function measurement-target person according to the motion of the cardiopulmonary function measurement-target person, by a processor, and predicting a cardiopulmonary function index of the cardiopulmonary function measurement-target person, based on the gait speed of the cardiopulmonary function measurement-target person, by the processor.

Systems and methods are provided for testing the ability of an individual to lift objects under various conditions. During standard lifting tests, the average acceleration and velocity of each lift, as well as the distribution of force between the hands and feet of the patient, are electronically measured and recorded. These objective factors can then be used to determine whether the patient is exerting maximal effort, and to assess a patient's condition and progress during a rehabilitation program. In example embodiments, one or more components of the system are adjustable so as to accommodate users of various posture, mechanics, size and movement capabilities.

The present invention relates to a device for measuring grip strength including a basis; a cover coupled to the basis to form an enclosed pressure space separated from the outside; a cap disposed between the basis and the cover and configured to form a sensing space separated from the pressure space; magnets mounted on the cap or the basis to form a magnetic field; and a magnetic sensor for detecting change in the magnetic field. With this configuration, when measuring the grip strength of the user's hand, accuracy or sensitivity may be increased.

Aspects of the subject technology relate to communication device used as a power meter. The communication device includes circuitry to determine values of several forces and a processor. The processor determines a combined force by combining the determined values of the forces. The processor further determines a value of a power based on the s combined force, a speed and a loss factor. The communication device is used by a user to measure the power. The power is generated by the user when engaged in an activity, and the forces affect a movement of the user.

A driving system of a hybrid gait rehabilitation robot include: a driving unit that is connected to a footrest of the gait rehabilitation robot and transmits a driving force such that the robot operates at a preset speed; a speed detection unit that detects a gait speed of an occupant; and a control unit that controls a speed of the driving unit by comparing the detected speed of the speed detection unit with a speed applied by the driving unit. The driving unit transmits power toward the occupant, but the driving force of the occupant is not transmitted to the driving unit.