Health monitoring system and appliance

An electronic device, comprising:

• a network interface;
• at least one computing device;
• and
• computer readable memory including instructions operable to be executed by the at least one computing device to perform a set of actions, configuring the at least one computing device to:
• access a digitized human vocal expression of a first user received in real-time from a first source converted from a time domain to a frequency domain;
• use the converted digitized human vocal expression to determine characteristics of the human vocal expression, by at least:
• detecting quiet time using identified pauses and length of pauses between words in speech in the human vocal expression, and
• determining how rapidly the first user is speaking in the human vocal expression using the detected quiet time;
• use natural language processing to:
• convert at least a portion of the digitized human vocal expression to text:
• detect violations of grammar rules in the text obtained from the human vocal expression to obtain detected grammar violations;
• and
• detect rapid changes in topic in the text obtained from the human vocal expression;
• compare the determined characteristics of the human vocal expression with baseline, historical characteristics of human vocal expressions associated with the first user to identify changes in human vocal expression characteristics of the first user as identified vocal changes, including changes in how rapidly the first user is speaking;
• weight, using a first weight, a first identified change, of the identified vocal changes, with respect to a first vocal expression characteristic of the first user;
• weight, using a second weight, a second identified change, of the identified vocal changes, with respect to a second vocal expression characteristic of the first user;
• weight, using a third weight, the detected grammar violations;
• weight the detected rapid changes in topic;
• infer a change in health status, the inferred change in health status comprising a post-traumatic stress disorder (PTSD) episode, of the first user based at least in part on:
• the weighted first identified change with respect to the first vocal expression characteristic of the first user, the first vocal characteristic comprising changes in how rapidly the first user is speaking,
• the weighted second identified change with respect to the second vocal expression characteristic of the first user,
• the weighted detected grammar violations, and
• the weighted detected rapid changes in topic;
• and
• based at least in part on the inferred change in health status, comprising the post-traumatic stress disorder (PTSD) episode of the first user, cause a first action is to be taken, the first action pertaining to operation of machinery.

A computer implemented method, comprising:

• accessing a digitized human vocal expression of a first user received in real-time from a first source converted from a time domain to a frequency domain;
• using the converted digitized human vocal expression to determine characteristics of the human vocal expression, by at least:
• detecting quiet time using identified pauses and length of pauses between words in speech in the human vocal expression, and
• determining how rapidly the first user is speaking in the human vocal expression using the detected quiet time;
• using natural language processing to:
• convert at least a portion of the digitized human vocal expression to text:
• detect violations of grammar rules in the text obtained from the human vocal expression to obtain detected grammar violations;
• and
• detect rapid changes in topic in the text obtained from the human vocal expression;
• comparing the determined characteristics of the human vocal expression with baseline, historical characteristics of human vocal expressions associated with the first user to identify changes in human vocal expression characteristics of the first user as identified vocal changes, including changes in how rapidly the first user is speaking;
• weighting, using a first weight, a first identified change, of the identified vocal changes, with respect to a first vocal expression characteristic of the first user, the first vocal characteristic comprising changes in how rapidly the first user is speaking,
• weighting, using a second weight, a second identified change, of the identified vocal changes, with respect to a second vocal expression characteristic of the first user;
• weighting, using a third weight, the detected grammar violations;
• and
• weighting the detected rapid changes in topic;
• inferring a change in health status, the inferred change in health status comprising a post-traumatic stress disorder (PTSD) episode, of the first user based at least in part on:
• the weighted first identified change with respect to the first vocal expression characteristic of the first user, the first vocal characteristic comprising changes in how rapidly the first user is speaking,
• the weighted second identified change with respect to the second vocal expression characteristic of the first user,
• the weighted detected grammar violations, and
• the weighted detected rapid changes in topic;
• and
• based at least in part on the inferred change in health status, comprising the post-traumatic stress disorder (PTSD) episode of the first user, cause a first action is to be taken, the first action pertaining to operation of machinery.