Apparatus and method for motor function characterization

A method of characterizing cognitive function of a user by analyzing an input by the user to a user interface of at least one computing device, the method comprising:

• receiving a sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a time duration associated with the user performing one or more typing tasks;
• determining, by at least one processor, a plurality of probability distributions of keystroke event intervals over at least some of the time duration, wherein each probability distribution of the plurality of probability distributions corresponds to a portion of the time duration, the plurality of probability distributions of keystroke event intervals comprises a first probability distribution relating to keystroke events included in a first portion of the time duration and a second probability distribution relating to keystroke events included in a second portion of the time duration, wherein determining a probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the time duration;
• and
• determining stability of cognitive function of the user at least in part by analyzing at least the first probability distribution and the second probability distribution to determine variation of keystroke event intervals over the time duration,
• receiving a second sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a second time duration;
• determining, by the at least one processor, a second plurality of probability distributions of keystroke event intervals over at least some of a second time duration, wherein each probability distribution of the second plurality of probability distributions corresponds to a portion of the second time duration, the second plurality of probability distributions of keystroke event intervals comprises a third probability distribution relating to keystroke events included in a first portion of the second time duration and a fourth probability distribution relating to keystroke events included in a second portion of the second time duration, wherein determining a second probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the second time duration;
• and
• determining a second stability of cognitive function of the user at least in part by analyzing at least the third probability distribution and the fourth probability distribution to determine variation of keystroke event intervals over the second time duration, wherein:
• identifying a change in the user's cognitive function between the time duration and the second time duration comprises determining a first feature related to variation in distribution spread among the plurality of probability distributions and a second feature related to variation in distribution spread among the second plurality of probability distributions and comparing at least the first feature and the second feature.

A method of characterizing cognitive function of a user by analyzing an input by the user to a user interface of at least one computing device, the method comprising:

• receiving a sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a time duration associated with the user performing one or more typing tasks;
• determining, by at least one processor, a plurality of probability distributions of keystroke event intervals over at least some of the time duration, wherein each probability distribution of the plurality of probability distributions corresponds to a portion of the time duration, the plurality of probability distributions of keystroke event intervals comprises a first probability distribution relating to keystroke events included in a first portion of the time duration and a second probability distribution relating to keystroke events included in a second portion of the time duration, wherein determining a probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the time duration;
• and
• determining stability of cognitive function of the user at least in part by analyzing at least the first probability distribution and the second probability distribution to determine variation of keystroke event intervals over the time duration,
• receiving a second sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a second time duration;
• determining, by the at least one processor, a second plurality of probability distributions of keystroke event intervals over at least some of a second time duration, wherein each probability distribution of the second plurality of probability distributions corresponds to a portion of the second time duration, the second plurality of probability distributions of keystroke event intervals comprises a third probability distribution relating to keystroke events included in a first portion of the second time duration and a fourth probability distribution relating to keystroke events included in a second portion of the second time duration, wherein determining a second probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the second time duration;
• and
• determining a second stability of cognitive function of the user at least in part by analyzing at least the third probability distribution and the fourth probability distribution to determine variation of keystroke event intervals over the second time duration, wherein:
• identifying a change in the user's cognitive function between the time duration and the second time duration comprises determining a difference between at least the first feature and the second feature.

A method of characterizing cognitive function of a user by analyzing an input by the user to a user interface of at least one computing device, the method comprising:

• receiving a sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a time duration associated with the user performing one or more typing tasks;
• determining, by at least one processor, a plurality of probability distributions of keystroke event intervals over at least some of the time duration, wherein each probability distribution of the plurality of probability distributions corresponds to a portion of the time duration, the plurality of probability distributions of keystroke event intervals comprises a first probability distribution relating to keystroke events included in a first portion of the time duration and a second probability distribution relating to keystroke events included in a second portion of the time duration, wherein determining a probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the time duration;
• and
• determining stability of cognitive function of the user at least in part by analyzing at least the first probability distribution and the second probability distribution to determine variation of keystroke event intervals over the time duration,
• receiving a second sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a second time duration;
• determining, by the at least one processor, a second plurality of probability distributions of keystroke event intervals over at least some of a second time duration, wherein each probability distribution of the second plurality of probability distributions corresponds to a portion of the second time duration, the second plurality of probability distributions of keystroke event intervals comprises a third probability distribution relating to keystroke events included in a first portion of the second time duration and a fourth probability distribution relating to keystroke events included in a second portion of the second time duration, wherein determining a second probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the second time duration;
• and
• determining a second stability of cognitive function of the user at least in part by analyzing at least the third probability distribution and the fourth probability distribution to determine variation of keystroke event intervals over the second time duration, wherein identifying a change in cognitive function between the time duration and the second time duration comprises identifying a measure of an increase in flight time when the user releases one key and presses a subsequent key based on comparing the plurality of probability distributions and the second plurality of probability distributions.

A method of characterizing cognitive function of a user by analyzing an input by the user to a user interface of at least one computing device, the method comprising:

• receiving a sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a time duration associated with the user performing one or more typing tasks;
• determining, by at least one processor, a plurality of probability distributions of keystroke event intervals over at least some of the time duration, wherein each probability distribution of the plurality of probability distributions corresponds to a portion of the time duration, the plurality of probability distributions of keystroke event intervals comprises a first probability distribution relating to keystroke events included in a first portion of the time duration and a second probability distribution relating to keystroke events included in a second portion of the time duration, wherein determining a probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the time duration;
• and
• determining stability of cognitive function of the user at least in part by analyzing at least the first probability distribution and the second probability distribution to determine variation of keystroke event intervals over the time duration,
• receiving a second sequence of keystroke events indicating that the user pressed at least a portion of the user interface over a second time duration;
• determining, by the at least one processor, a second plurality of probability distributions of keystroke event intervals over at least some of a second time duration, wherein each probability distribution of the second plurality of probability distributions corresponds to a portion of the second time duration, the second plurality of probability distributions of keystroke event intervals comprises a third probability distribution relating to keystroke events included in a first portion of the second time duration and a fourth probability distribution relating to keystroke events included in a second portion of the second time duration, wherein determining a second probability distribution of the plurality of probability distributions comprises identifying time intervals between keystroke events that occur within a corresponding portion of the second time duration;
• and
• determining a second stability of cognitive function of the user at least in part by analyzing at least the third probability distribution and the fourth probability distribution to determine variation of keystroke event intervals over the second time duration, further comprising:
• determining an average value for the plurality of probability distributions by averaging a plurality of median values, wherein each median value is a median keystroke event interval for a probability distribution of the plurality of probability distributions;
• determining a second average value for the second plurality of probability distributions by averaging a plurality of median values, wherein each median value is a median keystroke event interval for a probability distribution of the second plurality of probability distributions;
• determining a degree of similarity indicative of variation among the plurality of probability distributions by comparing the plurality of probability distributions to each other;
• determining a second degree of similarity indicative of variation among the plurality of probability distributions by comparing the second plurality of probability distributions to each other;
• identifying a feature vector based on the average value and the degree of similarity;
• and
• identifying a second feature vector based on the second average value and the second degree of similarity, and
• wherein identifying a change in the user's cognitive function between the time duration and the second time duration comprises determining a difference between the feature vector and the second feature vector.