Patent ID: 11944436
Assignee: KOA HEALTH DIGITAL SOLUTIONS S.L.U.
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 8:
9. A method comprising:
receiving touch data points of a user of a smartphone, wherein each touch data point includes an X position value, a Y position value and an associated touch timestamp value;
segmenting the touch data points into discrete movements of a finger of the user on a screen of the smartphone;
receiving motion data points of the smartphone, wherein each motion data point includes an X movement value, a Y movement value, a Z movement value and an associated motion timestamp value;
segmenting the motion data points into non-overlapping time intervals, wherein at least a portion of a first time interval occurs concurrently with the touch data points as the finger of the user moves over the screen of the smartphone, and wherein values of touch features are generated from the touch data points that fall within the first time interval;
associating the first time interval with those discrete movements of the finger of the user that occur entirely within the first time interval;
calculating the values of touch features for each discrete movement within the first time interval;
calculating values of motion features associated with the first time interval;
normalizing the touch features and the motion features based on prior touch data points and motion data points previously acquired while the user was using the smartphone;
calculating a stress level value for each discrete movement within the first time interval by applying regression parameters to the normalized touch features and the normalized motion features, wherein the regression parameters are generated using a logistic regression model trained on touch data points and motion data points acquired from other users during time intervals identified by those other users as being associated with various levels of stress;
determining a stress score of the user during the first time interval based on the stress level values of the discrete movements within the first time interval; and
displaying an indication of how the stress score of the user has changed since the stress score of the user was last determined.